WorldWideScience

Sample records for selection bias measurement

  1. HMO marketing and selection bias: are TEFRA HMOs skimming?

    Science.gov (United States)

    Lichtenstein, R; Thomas, J W; Watkins, B; Puto, C; Lepkowski, J; Adams-Watson, J; Simone, B; Vest, D

    1992-04-01

    The research evidence indicates that health maintenance organizations (HMOs) participating in the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) At-Risk Program tend to experience favorable selection. Although favorable selection might result from patient decisions, a common conjecture is that it can be induced by HMOs through their marketing activities. The purpose of this study is to examine the relationship between HMO marketing strategies and selection bias in TEFRA At-Risk HMOs. A purposive sample of 22 HMOs that were actively marketing their TEFRA programs was selected and data on organizational characteristics, market area characteristics, and HMO marketing decisions were collected. To measure selection bias in these HMOs, the functional health status of approximately 300 enrollees in each HMO was compared to that of 300 non-enrolling beneficiaries in the same area. Three dependent variables, reflecting selection bias at the mean, the low health tail, and the high health tail of the health status distribution were created. Weighted least squares regressions were then used to identify relationships between marketing elements and selection bias. Subject to the statistical limitations of the study, our conclusion is that it is doubtful that HMO marketing decisions are responsible for the prevalence of favorable selection in HMO enrollment. It also appears unlikely that HMOs were differentially targeting healthy and unhealthy segments of the Medicare market.

  2. QUANTIFYING THE BIASES OF SPECTROSCOPICALLY SELECTED GRAVITATIONAL LENSES

    International Nuclear Information System (INIS)

    Arneson, Ryan A.; Brownstein, Joel R.; Bolton, Adam S.

    2012-01-01

    Spectroscopic selection has been the most productive technique for the selection of galaxy-scale strong gravitational lens systems with known redshifts. Statistically significant samples of strong lenses provide a powerful method for measuring the mass-density parameters of the lensing population, but results can only be generalized to the parent population if the lensing selection biases are sufficiently understood. We perform controlled Monte Carlo simulations of spectroscopic lens surveys in order to quantify the bias of lenses relative to parent galaxies in velocity dispersion, mass axis ratio, and mass-density profile. For parameters typical of the SLACS and BELLS surveys, we find (1) no significant mass axis ratio detection bias of lenses relative to parent galaxies; (2) a very small detection bias toward shallow mass-density profiles, which is likely negligible compared to other sources of uncertainty in this parameter; (3) a detection bias toward smaller Einstein radius for systems drawn from parent populations with group- and cluster-scale lensing masses; and (4) a lens-modeling bias toward larger velocity dispersions for systems drawn from parent samples with sub-arcsecond mean Einstein radii. This last finding indicates that the incorporation of velocity-dispersion upper limits of non-lenses is an important ingredient for unbiased analyses of spectroscopically selected lens samples. In general, we find that the completeness of spectroscopic lens surveys in the plane of Einstein radius and mass-density profile power-law index is quite uniform, up to a sharp drop in the region of large Einstein radius and steep mass-density profile, and hence that such surveys are ideally suited to the study of massive field galaxies.

  3. Biases in cost measurement for economic evaluation studies in health care.

    Science.gov (United States)

    Jacobs, P; Baladi, J F

    1996-01-01

    This paper addresses the issue of biases in cost measures which used in economic evaluation studies. The basic measure of hospital costs which is used by most investigators is unit cost. Focusing on this measure, a set of criteria which the basic measures must fulfil in order to approximate the marginal cost (MC) of a service for the relevant product, in the representative site, was identified. Then four distinct biases--a scale bias, a case mix bias, a methods bias and a site selection bias--each of which reflects the divergence of the unit cost measure from the desired MC measure, were identified. Measures are proposed for several of these biases and it is suggested how they can be corrected.

  4. The Selective Advantage of Synonymous Codon Usage Bias in Salmonella.

    Directory of Open Access Journals (Sweden)

    Gerrit Brandis

    2016-03-01

    Full Text Available The genetic code in mRNA is redundant, with 61 sense codons translated into 20 different amino acids. Individual amino acids are encoded by up to six different codons but within codon families some are used more frequently than others. This phenomenon is referred to as synonymous codon usage bias. The genomes of free-living unicellular organisms such as bacteria have an extreme codon usage bias and the degree of bias differs between genes within the same genome. The strong positive correlation between codon usage bias and gene expression levels in many microorganisms is attributed to selection for translational efficiency. However, this putative selective advantage has never been measured in bacteria and theoretical estimates vary widely. By systematically exchanging optimal codons for synonymous codons in the tuf genes we quantified the selective advantage of biased codon usage in highly expressed genes to be in the range 0.2-4.2 x 10-4 per codon per generation. These data quantify for the first time the potential for selection on synonymous codon choice to drive genome-wide sequence evolution in bacteria, and in particular to optimize the sequences of highly expressed genes. This quantification may have predictive applications in the design of synthetic genes and for heterologous gene expression in biotechnology.

  5. Apparent directional selection by biased pleiotropic mutation.

    Science.gov (United States)

    Tanaka, Yoshinari

    2010-07-01

    Pleiotropic effects of deleterious mutations are considered to be among the factors responsible for genetic constraints on evolution by long-term directional selection acting on a quantitative trait. If pleiotropic phenotypic effects are biased in a particular direction, mutations generate apparent directional selection, which refers to the covariance between fitness and the trait owing to a linear association between the number of mutations possessed by individuals and the genotypic values of the trait. The present analysis has shown how the equilibrium mean value of the trait is determined by a balance between directional selection and biased pleiotropic mutations. Assuming that genes act additively both on the trait and on fitness, the total variance-standardized directional selection gradient was decomposed into apparent and true components. Experimental data on mutation bias from the bristle traits of Drosophila and life history traits of Daphnia suggest that apparent selection explains a small but significant fraction of directional selection pressure that is observed in nature; the data suggest that changes induced in a trait by biased pleiotropic mutation (i.e., by apparent directional selection) are easily compensated for by (true) directional selection.

  6. Measuring Agricultural Bias

    DEFF Research Database (Denmark)

    Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn

    The measurement issue is the key issue in the literature on trade policy-induced agri-cultural price incentive bias. This paper introduces a general equilibrium effective rate of protection (GE-ERP) measure, which extends and generalizes earlier partial equilibrium nominal protection measures...... shares and intersectoral linkages - are crucial for determining the sign and magnitude of trade policy bias. The GE-ERP measure is therefore uniquely suited to capture the full impact of trade policies on agricultural price incentives. A Monte Carlo procedure confirms that the results are robust....... For the 15 sample countries, the results indicate that the agricultural price incentive bias, which was generally perceived to exist during the 1980s, was largely eliminated during the 1990s. The results also demonstrate that general equilibrium effects and country-specific characteristics - including trade...

  7. Representation Bias, Return Forecast, and Portfolio Selection in the Stock Market of China

    Directory of Open Access Journals (Sweden)

    Daping Zhao

    2014-01-01

    Full Text Available Representation bias means a kind of cognitive tendency, and, for investors, it can affect their behavior in the stock market. Whether the representation bias can help the return forecast and portfolio selection is an interesting problem that is less studied. In this paper, based on the representation bias theory and current markets situation in China, a new hierarchy of stock measurement system is constructed and a corresponding set of criteria is also proposed. On each criterion, we try to measure the influence among stocks with adapted fuzzy AHP. Then the Hausdorff distance is applied to weight and compute the horizontal representation returns. For the forecast returns, according to representation behaviors, there is also a new computation method. Empirical results show that the representation bias information is useful to the return forecast as well as the portfolio selection.

  8. Selective processing of smoking-related cues in smokers: manipulation of deprivation level and comparison of three measures of processing bias.

    Science.gov (United States)

    Mogg, Karin; Bradley, Brendan P

    2002-12-01

    Recent theories of addiction suggest that an attentional bias for drug-related cues plays an important role in maintaining drug-taking behaviours. A key feature of the present study is that it used three different measures of processing bias for linguistic and pictorial smoking-related cues: masked and unmasked conditions of the modified Stroop task, and a pictorial version of the visual probe task. Participants were smokers (n = 27), who were tested twice, with deprivation level manipulated as a within-subjects variable. They were asked to abstain from smoking for 12 h before one session, and to smoke normally before the other. Results were consistent with an attentional bias for smoking-related pictures on the visual probe task, and for smoking-related words in the unmasked condition of the modified Stroop task. The latter bias was most strongly predicted by self-reported urge to smoke, rather than by the deprivation manipulation. There was no evidence of a preconscious bias for smoking cues. The three measures of cognitive bias (from masked and unmasked Stroop and visual probe tasks) were not significantly correlated with each other, which suggests they may tap different underlying mechanisms. We discuss the results with respect to conceptualizations of selective attention, addiction and motivational states in general.

  9. Ascertainment biases in SNP chips affect measures of population divergence

    DEFF Research Database (Denmark)

    Albrechtsen, Anders; Nielsen, Finn Cilius; Nielsen, Rasmus

    2010-01-01

    Chip-based high-throughput genotyping has facilitated genome-wide studies of genetic diversity. Many studies have utilized these large data sets to make inferences about the demographic history of human populations using measures of genetic differentiation such as F(ST) or principal component...... on direct sequencing. In addition, we also analyze publicly available genome-wide data. We demonstrate that the ascertainment biases will distort measures of human diversity and possibly change conclusions drawn from these measures in some times unexpected ways. We also show that details of the genotyping...... analyses. However, the single nucleotide polymorphism (SNP) chip data suffer from ascertainment biases caused by the SNP discovery process in which a small number of individuals from selected populations are used as discovery panels. In this study, we investigate the effect of the ascertainment bias...

  10. Target selection biases from recent experience transfer across effectors.

    Science.gov (United States)

    Moher, Jeff; Song, Joo-Hyun

    2016-02-01

    Target selection is often biased by an observer's recent experiences. However, not much is known about whether these selection biases influence behavior across different effectors. For example, does looking at a red object make it easier to subsequently reach towards another red object? In the current study, we asked observers to find the uniquely colored target object on each trial. Randomly intermixed pre-trial cues indicated the mode of action: either an eye movement or a visually guided reach movement to the target. In Experiment 1, we found that priming of popout, reflected in faster responses following repetition of the target color on consecutive trials, occurred regardless of whether the effector was repeated from the previous trial or not. In Experiment 2, we examined whether an inhibitory selection bias away from a feature could transfer across effectors. While priming of popout reflects both enhancement of the repeated target features and suppression of the repeated distractor features, the distractor previewing effect isolates a purely inhibitory component of target selection in which a previewed color is presented in a homogenous display and subsequently inhibited. Much like priming of popout, intertrial suppression biases in the distractor previewing effect transferred across effectors. Together, these results suggest that biases for target selection driven by recent trial history transfer across effectors. This indicates that representations in memory that bias attention towards or away from specific features are largely independent from their associated actions.

  11. The lack of selection bias in a snowball sampled case-control study on drug abuse.

    Science.gov (United States)

    Lopes, C S; Rodrigues, L C; Sichieri, R

    1996-12-01

    Friend controls in matched case-control studies can be a potential source of bias based on the assumption that friends are more likely to share exposure factors. This study evaluates the role of selection bias in a case-control study that used the snowball sampling method based on friendship for the selection of cases and controls. The cases selected fro the study were drug abusers located in the community. Exposure was defined by the presence of at least one psychiatric diagnosis. Psychiatric and drug abuse/dependence diagnoses were made according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R) criteria. Cases and controls were matched on sex, age and friendship. The measurement of selection bias was made through the comparison of the proportion of exposed controls selected by exposed cases (p1) with the proportion of exposed controls selected by unexposed cases (p2). If p1 = p2 then, selection bias should not occur. The observed distribution of the 185 matched pairs having at least one psychiatric disorder showed a p1 value of 0.52 and a p2 value of 0.51, indicating no selection bias in this study. Our findings support the idea that the use of friend controls can produce a valid basis for a case-control study.

  12. Impact of Selection Bias on Estimation of Subsequent Event Risk

    NARCIS (Netherlands)

    Hu, Yi Juan; Schmidt, Amand F.; Dudbridge, Frank; Holmes, Michael V; Brophy, James M.; Tragante, Vinicius; Li, Ziyi; Liao, Peizhou; Quyyumi, Arshed A.; McCubrey, Raymond O.; Horne, Benjamin D.; Hingorani, Aroon D; Asselbergs, Folkert W; Patel, Riyaz S.; Long, Qi; Åkerblom, Axel; Algra, Ale; Allayee, Hooman; Almgren, Peter; Anderson, Jeffrey L.; Andreassi, Maria G.; Anselmi, Chiara V.; Ardissino, Diego; Arsenault, Benoit J.; Ballantyne, Christie M.; Baranova, Ekaterina V.; Behloui, Hassan; Bergmeijer, Thomas O; Bezzina, Connie R; Bjornsson, Eythor; Body, Simon C.; Boeckx, Bram; Boersma, Eric H.; Boerwinkle, Eric; Bogaty, Peter; Braund, Peter S; Breitling, Lutz P.; Brenner, Hermann; Briguori, Carlo; Brugts, Jasper J.; Burkhardt, Ralph; Cameron, Vicky A.; Carlquist, John F.; Carpeggiani, Clara; Carruthers, Kathryn F.; Casu, Gavino; Condorelli, Gianluigi; Cresci, Sharon; Danchin, Nicolas; de Faire, Ulf; Deanfield, John; Delgado, Graciela; Deloukas, Panos; Direk, Kenan; Doughty, Robert N.; Drexel, Heinz; Duarte, Nubia E.; Dubé, Marie Pierre; Dufresne, Line; Engert, James C; Eriksson, Niclas; Fitzpatrick, Natalie; Foco, Luisa; Ford, Ian; Fox, Keith A; Gigante, Bruna; Gijsberts, Crystel M.; Girelli, Domenico; Gong, Yan; Gudbjartsson, Daniel F.; Hagström, Emil; Hartiala, Jaana; Hazen, Stanley L.; Held, Claes; Helgadottir, Anna; Hemingway, Harry; Heydarpour, Mahyar; Hoefer, Imo E.; Hovingh, G. Kees; Hubacek, Jaroslav A; James, Stefan; Johnson, Julie A; Jukema, J Wouter; Kaczor, Marcin P.; Kaminski, Karol A.; Kettner, Jiri; Kiliszek, Marek; Kleber, Marcus; Klungel, Olaf H.; Kofink, Daniel; Kohonen, Mika; Kotti, Salma; Kuukasjärvi, Pekka; Lagerqvist, Bo; Lambrechts, Diether; Lang, Chim C; Laurikka, Jari O.; Leander, Karin; Lee, Vei Vei; Lehtimäki, Terho; Leiherer, Andreas; Lenzini, Petra A.; Levin, Daniel; Lindholm, Daniel; Lokki, Marja-Liisa; Lotufo, Paulo A; Lyytikäinen, Leo-Pekka; Mahmoodi, B. Khan; Maitland-Van Der Zee, Anke H.; Martinelli, Nicola; März, Winfried; Marziliano, Nicola; McPherson, Ruth; Melander, Olle; Mons, Ute; Muehlschlegel, Jochen D.; Muhlestein, Joseph B.; Nelson, Cristopher P.; Cheh, Chris Newton; Olivieri, Oliviero; Opolski, Grzegorz; Palmer, Colin Na; Pare, Guillaume; Pasterkamp, Gerard; Pepine, Carl J; Pepinski, Witold; Pereira, Alexandre C.; Pilbrow, Anna P.; Pilote, Louise; Pitha, Jan; Ploski, Rafal; Richards, A. Mark; Saely, Christoph H.; Samani, Nilesh J; Samman-Tahhan, Ayman; Sanak, Marek; Sandesara, Pratik B.; Sattar, Naveed; Scholz, Markus; Siegbahn, Agneta; Simon, Tabassome; Sinisalo, Juha; Smith, J. Gustav; Spertus, John A.; Stefansson, Kari; Stewart, Alexandre F R; Stott, David J.; Szczeklik, Wojciech; Szpakowicz, Anna; Tanck, Michael W.T.; Tang, Wilson H.; Tardif, Jean-Claude; Ten Berg, Jur M.; Teren, Andrej; Thanassoulis, George; Thiery, Joachim; Thorgeirsson, Gudmundur; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Timmis, Adam; Trompet, Stella; Van de Werf, Frans; van der Graaf, Yolanda; Van Der Haarst, Pim; van der Laan, Sander W; Vilmundarson, Ragnar O.; Virani, Salim S.; Visseren, Frank L J; Vlachopoulou, Efthymia; Wallentin, Lars; Waltenberger, Johannes; Wauters, Els; Wilde, Arthur A M

    2017-01-01

    Background - Studies of recurrent or subsequent disease events may be susceptible to bias caused by selection of subjects who both experience and survive the primary indexing event. Currently, the magnitude of any selection bias, particularly for subsequent time-to-event analysis in genetic

  13. Heterogeneous Causal Effects and Sample Selection Bias

    DEFF Research Database (Denmark)

    Breen, Richard; Choi, Seongsoo; Holm, Anders

    2015-01-01

    The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how...... causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects....... This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias...

  14. Biased selection within the social health insurance market in Colombia.

    Science.gov (United States)

    Castano, Ramon; Zambrano, Andres

    2006-12-01

    Reducing the impact of insurance market failures with regulations such as community-rated premiums, standardized benefit packages and open enrolment, yield limited effect because they create room for selection bias. The Colombian social health insurance system started a market approach in 1993 expecting to improve performance of preexisting monopolistic insurance funds by exposing them to competition by new entrants. This paper tests the hypothesis that market failures would lead to biased selection favoring new entrants. Two household surveys are analyzed using Self-Reported Health Status and the presence of chronic conditions as prospective indicators of individual risk. Biased selection is found to take place, leading to adverse selection among incumbents, and favorable selection among new entrants. This pattern is absent in 1997 but is evident in 2003. Given that the two incumbents analyzed are public organizations, the fiscal implications of the findings in terms of government bailouts, are analyzed.

  15. Measuring agricultural policy bias

    DEFF Research Database (Denmark)

    Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn

    2010-01-01

    Measurement is a key issue in the literature on price incentive bias induced by trade policy. We introduce a general equilibrium measure of the relative effective rate of protection, which generalizes earlier protection measures. For our fifteen sample countries, results indicate that the agricul...

  16. Measurement of the $B^-$ lifetime using a simulation free approach for trigger bias correction

    Energy Technology Data Exchange (ETDEWEB)

    Aaltonen, T.; /Helsinki Inst. of Phys.; Adelman, J.; /Chicago U., EFI; Alvarez Gonzalez, B.; /Cantabria Inst. of Phys.; Amerio, S.; /INFN, Padua; Amidei, D.; /Michigan U.; Anastassov, A.; /Northwestern U.; Annovi, A.; /Frascati; Antos, J.; /Comenius U.; Apollinari, G.; /Fermilab; Appel, J.; /Fermilab; Apresyan, A.; /Purdue U. /Waseda U.

    2010-04-01

    The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. In this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B{sup -} using the mode B{sup -} {yields} D{sup 0}{pi}{sup -}. The B{sup -} lifetime is measured as {tau}{sub B{sup -}} = 1.663 {+-} 0.023 {+-} 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.

  17. Measurement of the B- lifetime using a simulation free approach for trigger bias correction

    International Nuclear Information System (INIS)

    2010-01-01

    The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. In this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B - using the mode B - → D 0 π - . The B - lifetime is measured as τ B# sup -# = 1.663 ± 0.023 ± 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.

  18. Selection bias and the Rubin-Ford effect

    International Nuclear Information System (INIS)

    James, P.A.; Joseph, R.D.; Collins, C.A.

    1991-01-01

    We have re-examined the 'Rubin-Ford effect', and more recent claims of galaxy streaming from the same galaxy sample, to investigate the impact of selection effects on these results. A 'Monte Carlo'-type analysis was applied to simulate the selection procedure used to obtain this sample, and a strong bias was identified, resulting in apparent velocity flows at 600-800 km s -1 . Thus the 'Rubin-Ford effect' and the associated galaxy streaming are spurious effects resulting from the method of sample selection. (author)

  19. Mis-estimation and bias of hyperpolarized apparent diffusion coefficient measurements due to slice profile effects.

    Science.gov (United States)

    Gordon, Jeremy W; Milshteyn, Eugene; Marco-Rius, Irene; Ohliger, Michael; Vigneron, Daniel B; Larson, Peder E Z

    2017-09-01

    The purpose of this work was to explore the impact of slice profile effects on apparent diffusion coefficient (ADC) mapping of hyperpolarized (HP) substrates. Slice profile effects were simulated using a Gaussian radiofrequency (RF) pulse with a variety of flip angle schedules and b-value ordering schemes. A long T 1 water phantom was used to validate the simulation results, and ADC mapping of HP [ 13 C, 15 N 2 ]urea was performed on the murine liver to assess these effects in vivo. Slice profile effects result in excess signal after repeated RF pulses, causing bias in HP measurements. The largest error occurs for metabolites with small ADCs, resulting in up to 10-fold overestimation for metabolites that are in more-restricted environments. A mixed b-value scheme substantially reduces this bias, whereas scaling the slice-select gradient can mitigate it completely. In vivo, the liver ADC of hyperpolarized [ 13 C, 15 N 2 ]urea is nearly 70% lower (0.99 ± 0.22 vs 1.69 ± 0.21 × 10 -3 mm 2 /s) when slice-select gradient scaling is used. Slice profile effects can lead to bias in HP ADC measurements. A mixed b-value ordering scheme can reduce this bias compared to sequential b-value ordering. Slice-select gradient scaling can also correct for this deviation, minimizing bias and providing more-precise ADC measurements of HP substrates. Magn Reson Med 78:1087-1092, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  20. Measurement of Minimum Bias Observables with ATLAS

    CERN Document Server

    Kvita, Jiri; The ATLAS collaboration

    2017-01-01

    The modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes. It has also a significant relevance for the simulation of the environment at the LHC with many concurrent pp interactions (“pileup”). The ATLAS collaboration has provided new measurements of the inclusive charged particle multiplicity and its dependence on transverse momentum and pseudorapidity in special data sets with low LHC beam currents, recorded at center of mass energies of 8 TeV and 13 TeV. The measurements cover a wide spectrum using charged particle selections with minimum transverse momentum of both 100 MeV and 500 MeV and in various phase space regions of low and high charged particle multiplicities.

  1. Case matching and the reduction of selection bias in quasi-experiments: The relative importance of pretest measures of outcome, of unreliable measurement, and of mode of data analysis.

    Science.gov (United States)

    Cook, Thomas D; Steiner, Peter M

    2010-03-01

    In this article, we note the many ontological, epistemological, and methodological similarities between how Campbell and Rubin conceptualize causation. We then explore 3 differences in their written emphases about individual case matching in observational studies. We contend that (a) Campbell places greater emphasis than Rubin on the special role of pretest measures of outcome among matching variables; (b) Campbell is more explicitly concerned with unreliability in the covariates; and (c) for analyzing the outcome, only Rubin emphasizes the advantages of using propensity score over regression methods. To explore how well these 3 factors reduce bias, we reanalyze and review within-study comparisons that contrast experimental and statistically adjusted nonexperimental causal estimates from studies with the same target population and treatment content. In this context, the choice of covariates counts most for reducing selection bias, and the pretest usually plays a special role relative to all the other covariates considered singly. Unreliability in the covariates also influences bias reduction but by less. Furthermore, propensity score and regression methods produce comparable degrees of bias reduction, though these within-study comparisons may not have met the theoretically specified conditions most likely to produce differences due to analytic method.

  2. Measurement and control of bias in patient reported outcomes using multidimensional item response theory.

    Science.gov (United States)

    Dowling, N Maritza; Bolt, Daniel M; Deng, Sien; Li, Chenxi

    2016-05-26

    Patient-reported outcome (PRO) measures play a key role in the advancement of patient-centered care research. The accuracy of inferences, relevance of predictions, and the true nature of the associations made with PRO data depend on the validity of these measures. Errors inherent to self-report measures can seriously bias the estimation of constructs assessed by the scale. A well-documented disadvantage of self-report measures is their sensitivity to response style (RS) effects such as the respondent's tendency to select the extremes of a rating scale. Although the biasing effect of extreme responding on constructs measured by self-reported tools has been widely acknowledged and studied across disciplines, little attention has been given to the development and systematic application of methodologies to assess and control for this effect in PRO measures. We review the methodological approaches that have been proposed to study extreme RS effects (ERS). We applied a multidimensional item response theory model to simultaneously estimate and correct for the impact of ERS on trait estimation in a PRO instrument. Model estimates were used to study the biasing effects of ERS on sum scores for individuals with the same amount of the targeted trait but different levels of ERS. We evaluated the effect of joint estimation of multiple scales and ERS on trait estimates and demonstrated the biasing effects of ERS on these trait estimates when used as explanatory variables. A four-dimensional model accounting for ERS bias provided a better fit to the response data. Increasing levels of ERS showed bias in total scores as a function of trait estimates. The effect of ERS was greater when the pattern of extreme responding was the same across multiple scales modeled jointly. The estimated item category intercepts provided evidence of content independent category selection. Uncorrected trait estimates used as explanatory variables in prediction models showed downward bias. A

  3. Minimum Bias Trigger in ATLAS

    International Nuclear Information System (INIS)

    Kwee, Regina

    2010-01-01

    Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)

  4. Selection Bias in Educational Transition Models: Theory and Empirical Evidence

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads

    variables. This paper, first, explains theoretically how selection on unobserved variables leads to waning coefficients and, second, illustrates empirically how selection leads to biased estimates of the effect of family background on educational transitions. Our empirical analysis using data from...

  5. Quantifying Selection Bias in National Institute of Health Stroke Scale Data Documented in an Acute Stroke Registry.

    Science.gov (United States)

    Thompson, Michael P; Luo, Zhehui; Gardiner, Joseph; Burke, James F; Nickles, Adrienne; Reeves, Mathew J

    2016-05-01

    As a measure of stroke severity, the National Institutes of Health Stroke Scale (NIHSS) is an important predictor of patient- and hospital-level outcomes, yet is often undocumented. The purpose of this study is to quantify and correct for potential selection bias in observed NIHSS data. Data were obtained from the Michigan Stroke Registry and included 10 262 patients with ischemic stroke aged ≥65 years discharged from 23 hospitals from 2009 to 2012, of which 74.6% of patients had documented NIHSS. We estimated models predicting NIHSS documentation and NIHSS score and used the Heckman selection model to estimate a correlation coefficient (ρ) between the 2 model error terms, which quantifies the degree of selection bias in the documentation of NIHSS. The Heckman model found modest, but significant, selection bias (ρ=0.19; 95% confidence interval: 0.09, 0.29; P2 points, which could significantly alter the risk profile of hospitals treating patients with ischemic stroke and subsequent hospital risk-adjusted outcomes. © 2016 American Heart Association, Inc.

  6. Junction Potentials Bias Measurements of Ion Exchange Membrane Permselectivity.

    Science.gov (United States)

    Kingsbury, Ryan S; Flotron, Sophie; Zhu, Shan; Call, Douglas F; Coronell, Orlando

    2018-04-17

    Ion exchange membranes (IEMs) are versatile materials relevant to a variety of water and waste treatment, energy production, and industrial separation processes. The defining characteristic of IEMs is their ability to selectively allow positive or negative ions to permeate, which is referred to as permselectivity. Measured values of permselectivity that equal unity (corresponding to a perfectly selective membrane) or exceed unity (theoretically impossible) have been reported for cation exchange membranes (CEMs). Such nonphysical results call into question our ability to correctly measure this crucial membrane property. Because weighing errors, temperature, and measurement uncertainty have been shown to not explain these anomalous permselectivity results, we hypothesized that a possible explanation are junction potentials that occur at the tips of reference electrodes. In this work, we tested this hypothesis by comparing permselectivity values obtained from bare Ag/AgCl wire electrodes (which have no junction) to values obtained from single-junction reference electrodes containing two different electrolytes. We show that permselectivity values obtained using reference electrodes with junctions were greater than unity for CEMs. In contrast, electrodes without junctions always produced permselectivities lower than unity. Electrodes with junctions also resulted in artificially low permselectivity values for AEMs compared to electrodes without junctions. Thus, we conclude that junctions in reference electrodes introduce two biases into results in the IEM literature: (i) permselectivity values larger than unity for CEMs and (ii) lower permselectivity values for AEMs compared to those for CEMs. These biases can be avoided by using electrodes without a junction.

  7. Cognitive bias measurement and social anxiety disorder: Correlating self-report data and attentional bias

    Directory of Open Access Journals (Sweden)

    Alexander Miloff

    2015-09-01

    Full Text Available Social anxiety disorder (SAD and attentional bias are theoretically connected in cognitive behavioral therapeutic models. In fact, there is an emerging field focusing on modifying attentional bias as a stand-alone treatment. However, it is unclear to what degree these attentional biases are present before commencing treatment. The purpose of this study was to measure pre-treatment attentional bias in 153 participants diagnosed with SAD using a home-based Internet version of the dot-probe paradigm. Results showed no significant correlation for attentional bias (towards or away from negative words or faces and the self-rated version of the Liebowitz Social Anxiety Scale (LSAS-SR. However, two positive correlations were found for the secondary measures Generalized Anxiety Disorder 7 (GAD-7 and Patient Health Questionnaire 9 (PHQ-9. These indicated that those with elevated levels of anxiety and depression had a higher bias towards negative faces in neutral–negative and positive–negative valence combinations, respectively. The unreliability of the dot-probe paradigm and home-based Internet delivery are discussed to explain the lack of correlations between LSAS-SR and attentional bias. Changes to the dot-probe task are suggested that could improve reliability.

  8. Selection bias in the reported performances of AD classification pipelines

    Directory of Open Access Journals (Sweden)

    Alex F. Mendelson

    2017-01-01

    Full Text Available The last decade has seen a great proliferation of supervised learning pipelines for individual diagnosis and prognosis in Alzheimer's disease. As more pipelines are developed and evaluated in the search for greater performance, only those results that are relatively impressive will be selected for publication. We present an empirical study to evaluate the potential for optimistic bias in classification performance results as a result of this selection. This is achieved using a novel, resampling-based experiment design that effectively simulates the optimisation of pipeline specifications by individuals or collectives of researchers using cross validation with limited data. Our findings indicate that bias can plausibly account for an appreciable fraction (often greater than half of the apparent performance improvement associated with the pipeline optimisation, particularly in small samples. We discuss the consistency of our findings with patterns observed in the literature and consider strategies for bias reduction and mitigation.

  9. Selection bias and subject refusal in a cluster-randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Rochelle Yang

    2017-07-01

    Full Text Available Abstract Background Selection bias and non-participation bias are major methodological concerns which impact external validity. Cluster-randomized controlled trials are especially prone to selection bias as it is impractical to blind clusters to their allocation into intervention or control. This study assessed the impact of selection bias in a large cluster-randomized controlled trial. Methods The Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE study examined the impact of a remote pharmacist-led intervention in twelve medical offices. To assess eligibility, a standardized form containing patient demographics and medical information was completed for each screened patient. Eligible patients were approached by the study coordinator for recruitment. Both the study coordinator and the patient were aware of the site’s allocation prior to consent. Patients who consented or declined to participate were compared across control and intervention arms for differing characteristics. Statistical significance was determined using a two-tailed, equal variance t-test and a chi-square test with adjusted Bonferroni p-values. Results were adjusted for random cluster variation. Results There were 2749 completed screening forms returned to research staff with 461 subjects who had either consented or declined participation. Patients with poorly controlled diabetes were found to be significantly more likely to decline participation in intervention sites compared to those in control sites. A higher mean diastolic blood pressure was seen in patients with uncontrolled hypertension who declined in the control sites compared to those who declined in the intervention sites. However, these findings were no longer significant after adjustment for random variation among the sites. After this adjustment, females were now found to be significantly more likely to consent than males (odds ratio = 1.41; 95% confidence interval = 1.03, 1

  10. Role Appropriateness of Educational Fields: Bias in Selection.

    Science.gov (United States)

    Smith, Elizabeth P.; And Others

    Bias towards women exists in the selection of applicants to professional and other positions. This research investigated the effects of two rater variables--sex and attitude toward women--and three applicant variables--sex, field (engineering-dietetics), and attributes--(feminine-masculine) upon ratings of competency and personal charm. Analyses…

  11. Perceptual Color Space Representations in the Oculomotor System Are Modulated by Surround Suppression and Biased Selection

    OpenAIRE

    Kehoe, Devin H.; Rahimi, Maryam; Fallah, Mazyar

    2018-01-01

    The oculomotor system utilizes color extensively for planning saccades. Therefore, we examined how the oculomotor system actually encodes color and several factors that modulate these representations: attention-based surround suppression and inherent biases in selecting and encoding color categories. We measured saccade trajectories while human participants performed a memory-guided saccade task with color targets and distractors and examined whether oculomotor target selection processing was...

  12. Age-ordered shirt numbering reduces the selection bias associated with the relative age effect.

    Science.gov (United States)

    Mann, David L; van Ginneken, Pleun J M A

    2017-04-01

    When placed into age groups for junior sporting competition, the relative differences in age between children leads to a bias in who is evaluated as being talented. While the impact of this relative age effect (RAE) is clear, until now there has been no evidence to show how to reduce it. The aim of this study was to determine whether the selection bias associated with the RAE could be reduced. Talent scouts from an elite football club watched junior games and ranked players on the basis of their potential. Scouts were allocated to one of three groups provided with contrasting information about the age of the players: (1) no age information, (2) players' birthdates or (3) knowledge that the numbers on the playing shirts corresponded to the relative age of the players. Results revealed a significant selection bias for the scouts in the no-age information group, and that bias remained when scouts knew the players' dates-of-birth. Strikingly though, the selection bias was eliminated when scouts watched the games knowing the shirt numbers corresponded to the relative ages of the players. The selection bias associated with the RAE can be reduced if information about age is presented appropriately.

  13. Strategi Mengatasi Common Measures Bias dalam Balanced Scorecard

    Directory of Open Access Journals (Sweden)

    Sekar Akrom Faradiza

    2016-06-01

    Balanced Scorecard (BSC is a comprehensive performance measurement. BSC is not only used financial indicators but also non financial indicators there are customer, internal process business and learning and growth perspective. By using BSC, evaluators have common and unique measures. When evaluate manager performance, evaluator tends to only use common measures and ignore unique measures. This is called common measures bias. This study aims to investigate whether dissaggregated and aggregated BSC and management communication can overcome common measures bias and intent to BSC approach. This study also will evaluate whether these approach will affect evaluator decision when allocated compensation. We conduct 2x2x2 experiment of undergraduate accounting students. Participant act as a senior manager and evaluate the performance of two divisions and then allocated the bonus. ANOVA repeated measurement are used to conduct hypothesis test. The results showed that dissaggregated BSC and management communication could not overcome common measures bias but effected  management decision when allocated compensation.

  14. Evidence of selective reporting bias in hematology journals: A systematic review.

    Science.gov (United States)

    Wayant, Cole; Scheckel, Caleb; Hicks, Chandler; Nissen, Timothy; Leduc, Linda; Som, Mousumi; Vassar, Matt

    2017-01-01

    Selective reporting bias occurs when chance or selective outcome reporting rather than the intervention contributes to group differences. The prevailing concern about selective reporting bias is the possibility of results being modified towards specific conclusions. In this study, we evaluate randomized controlled trials (RCTs) published in hematology journals, a group in which selective outcome reporting has not yet been explored. Our primary goal was to examine discrepancies between the reported primary and secondary outcomes in registered and published RCTs concerning hematological malignancies reported in hematology journals with a high impact factor. The secondary goals were to address whether outcome reporting discrepancies favored statistically significant outcomes, whether a pattern existed between the funding source and likelihood of outcome reporting bias, and whether temporal trends were present in outcome reporting bias. For trials with major outcome discrepancies, we contacted trialists to determine reasons for these discrepancies. Trials published between January 1, 2010 and December 31, 2015 in Blood; British Journal of Haematology; American Journal of Hematology; Leukemia; and Haematologica were included. Of 499 RCTs screened, 109 RCTs were included. Our analysis revealed 118 major discrepancies and 629 total discrepancies. Among the 118 discrepancies, 30 (25.4%) primary outcomes were demoted, 47 (39.8%) primary outcomes were omitted, and 30 (25.4%) primary outcomes were added. Three (2.5%) secondary outcomes were upgraded to a primary outcome. The timing of assessment for a primary outcome changed eight (6.8%) times. Thirty-one major discrepancies were published with a P-value and twenty-five (80.6%) favored statistical significance. A majority of authors whom we contacted cited a pre-planned subgroup analysis as a reason for outcome changes. Our results suggest that outcome changes occur frequently in hematology trials. Because RCTs ultimately

  15. Running Performance, VO2max, and Running Economy: The Widespread Issue of Endogenous Selection Bias.

    Science.gov (United States)

    Borgen, Nicolai T

    2018-05-01

    Studies in sport and exercise medicine routinely use samples of highly trained individuals in order to understand what characterizes elite endurance performance, such as running economy and maximal oxygen uptake VO 2max . However, it is not well understood in the literature that using such samples most certainly leads to biased findings and accordingly potentially erroneous conclusions because of endogenous selection bias. In this paper, I review the current literature on running economy and VO 2max , and discuss the literature in light of endogenous selection bias. I demonstrate that the results in a large part of the literature may be misleading, and provide some practical suggestions as to how future studies may alleviate endogenous selection bias.

  16. Entropy-based gene ranking without selection bias for the predictive classification of microarray data

    Directory of Open Access Journals (Sweden)

    Serafini Maria

    2003-11-01

    Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

  17. A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

    Science.gov (United States)

    Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

    2011-09-01

    Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

  18. Reducing selection bias in case-control studies from rare disease registries.

    Science.gov (United States)

    Cole, J Alexander; Taylor, John S; Hangartner, Thomas N; Weinreb, Neal J; Mistry, Pramod K; Khan, Aneal

    2011-09-12

    In clinical research of rare diseases, where small patient numbers and disease heterogeneity limit study design options, registries are a valuable resource for demographic and outcome information. However, in contrast to prospective, randomized clinical trials, the observational design of registries is prone to introduce selection bias and negatively impact the validity of data analyses. The objective of the study was to demonstrate the utility of case-control matching and the risk-set method in order to control bias in data from a rare disease registry. Data from the International Collaborative Gaucher Group (ICGG) Gaucher Registry were used as an example. A case-control matching analysis using the risk-set method was conducted to identify two groups of patients with type 1 Gaucher disease in the ICGG Gaucher Registry: patients with avascular osteonecrosis (AVN) and those without AVN. The frequency distributions of gender, decade of birth, treatment status, and splenectomy status were presented for cases and controls before and after matching. Odds ratios (and 95% confidence intervals) were calculated for each variable before and after matching. The application of case-control matching methodology results in cohorts of cases (i.e., patients with AVN) and controls (i.e., patients without AVN) who have comparable distributions for four common parameters used in subject selection: gender, year of birth (age), treatment status, and splenectomy status. Matching resulted in odds ratios of approximately 1.00, indicating no bias. We demonstrated bias in case-control selection in subjects from a prototype rare disease registry and used case-control matching to minimize this bias. Therefore, this approach appears useful to study cohorts of heterogeneous patients in rare disease registries.

  19. Minimum bias measurement at 13 TeV

    CERN Document Server

    Orlando, Nicola; The ATLAS collaboration

    2017-01-01

    The modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes and to simulate the environment at the LHC with many concurrent pp interactions (pile-up). We summarise the ATLAS minimum bias measurements with proton-proton collision at 13 TeV center-of-mass-energy at the Large Hadron Collider.

  20. Measurement of Minimum Bias Observables with the ATLAS detector

    CERN Document Server

    Kvita, Jiri; The ATLAS collaboration

    2017-01-01

    The modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes. It has also a significant relevance for the simulation of the environment at the LHC with many concurrent pp interactions (“pileup”). The ATLAS collaboration has provided new measurements of the inclusive charged particle multiplicity and its dependence on transverse momentum and pseudorapidity in special data sets with low LHC beam currents, recorded at center of mass energies of 8 TeV and 13 TeV. The measurements cover a wide spectrum using charged particle selections with minimum transverse momentum of both 100 MeV and 500 MeV and in various phase space regions of low and high charged particle multiplicities.

  1. A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection

    OpenAIRE

    Kwan, Johnny S. H.; Kung, Annie W. C.; Sham, Pak C.

    2011-01-01

    Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias. © The Author(s) 2011.

  2. Reducing selection bias in case-control studies from rare disease registries

    Directory of Open Access Journals (Sweden)

    Mistry Pramod K

    2011-09-01

    Full Text Available Abstract Background In clinical research of rare diseases, where small patient numbers and disease heterogeneity limit study design options, registries are a valuable resource for demographic and outcome information. However, in contrast to prospective, randomized clinical trials, the observational design of registries is prone to introduce selection bias and negatively impact the validity of data analyses. The objective of the study was to demonstrate the utility of case-control matching and the risk-set method in order to control bias in data from a rare disease registry. Data from the International Collaborative Gaucher Group (ICGG Gaucher Registry were used as an example. Methods A case-control matching analysis using the risk-set method was conducted to identify two groups of patients with type 1 Gaucher disease in the ICGG Gaucher Registry: patients with avascular osteonecrosis (AVN and those without AVN. The frequency distributions of gender, decade of birth, treatment status, and splenectomy status were presented for cases and controls before and after matching. Odds ratios (and 95% confidence intervals were calculated for each variable before and after matching. Results The application of case-control matching methodology results in cohorts of cases (i.e., patients with AVN and controls (i.e., patients without AVN who have comparable distributions for four common parameters used in subject selection: gender, year of birth (age, treatment status, and splenectomy status. Matching resulted in odds ratios of approximately 1.00, indicating no bias. Conclusions We demonstrated bias in case-control selection in subjects from a prototype rare disease registry and used case-control matching to minimize this bias. Therefore, this approach appears useful to study cohorts of heterogeneous patients in rare disease registries.

  3. Dealing with selection bias in educational transition models

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads Meier

    2011-01-01

    This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational tr...... account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models.......This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational...... transitions to be correlated across transitions. We use simulated and real data to illustrate how the BPSM improves on the traditional Mare model in terms of correcting for selection bias and providing credible estimates of the effect of family background on educational success. We conclude that models which...

  4. Selection bias in population-based cancer case-control studies due to incomplete sampling frame coverage.

    Science.gov (United States)

    Walsh, Matthew C; Trentham-Dietz, Amy; Gangnon, Ronald E; Nieto, F Javier; Newcomb, Polly A; Palta, Mari

    2012-06-01

    Increasing numbers of individuals are choosing to opt out of population-based sampling frames due to privacy concerns. This is especially a problem in the selection of controls for case-control studies, as the cases often arise from relatively complete population-based registries, whereas control selection requires a sampling frame. If opt out is also related to risk factors, bias can arise. We linked breast cancer cases who reported having a valid driver's license from the 2004-2008 Wisconsin women's health study (N = 2,988) with a master list of licensed drivers from the Wisconsin Department of Transportation (WDOT). This master list excludes Wisconsin drivers that requested their information not be sold by the state. Multivariate-adjusted selection probability ratios (SPR) were calculated to estimate potential bias when using this driver's license sampling frame to select controls. A total of 962 cases (32%) had opted out of the WDOT sampling frame. Cases age <40 (SPR = 0.90), income either unreported (SPR = 0.89) or greater than $50,000 (SPR = 0.94), lower parity (SPR = 0.96 per one-child decrease), and hormone use (SPR = 0.93) were significantly less likely to be covered by the WDOT sampling frame (α = 0.05 level). Our results indicate the potential for selection bias due to differential opt out between various demographic and behavioral subgroups of controls. As selection bias may differ by exposure and study base, the assessment of potential bias needs to be ongoing. SPRs can be used to predict the direction of bias when cases and controls stem from different sampling frames in population-based case-control studies.

  5. Mixed signals: The effect of conflicting reward- and goal-driven biases on selective attention

    OpenAIRE

    Preciado, Daniel; Munneke, Jaap; Theeuwes, Jan

    2017-01-01

    Attentional selection depends on the interaction between exogenous (stimulus-driven), endogenous (goal-driven), and selection history (experience-driven) factors. While endogenous and exogenous biases have been widely investigated, less is known about their interplay with value-driven attention. The present study investigated the interaction between reward-history and goal-driven biases on perceptual sensitivity (d?) and response time (RT) in a modified cueing paradigm presenting two coloured...

  6. Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance

    Directory of Open Access Journals (Sweden)

    Zhang Zhang

    2012-03-01

    Full Text Available Abstract Background Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB. Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis. Results Here we propose a novel measure--Codon Deviation Coefficient (CDC--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance. Conclusions As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions.

  7. Theory and experimental study of biased charge collector for measuring HPIB

    International Nuclear Information System (INIS)

    He Xiaoping; Wang Haiyang; Sun Jianfeng; Yang Hailiang; Qiu Aici; Tang Junping; Li Jingya; Li Hongyu

    2004-01-01

    Structure of the biased charge collector for measuring HPIB (High-power ion beam) is introduced in this paper. The inner charge propagation process of HPIB in the biased charge collector was simulated with KARAT PIC code. The simulation results indicated that charge was neutralized but current was not neutralized in the biased charge collector. The influence of biased voltage and aperture diameter were also simulated. A -800V biased voltage can meet the requirement for measuring 500 keV HPIB, and this is consistent with the experimental results

  8. Racial Bias and Predictive Validity in Testing for Selection.

    Science.gov (United States)

    1983-07-01

    the inequa - lity rR (P.C) *0 (2) must define test bias. This definition of test bias conforms to the requirements of the Civil Rights Act of 1964 as...of Educational Measurement, 1976, 13, 43-52. Einhorn, H. J., & Bass, A. R. Methodological considerations relevant to discrimination in employment ...34unbiased" selec- tion model: A question of utilities. Journal of Applied Psychology, 1975, 60, 345-351. Guion, R. M. Employment tests and discriminatory

  9. Missing Data Bias on a Selective Hedging Strategy

    Directory of Open Access Journals (Sweden)

    Kiss Gábor Dávid

    2017-03-01

    Full Text Available Foreign exchange rates affect corporate profitability both on the macro and cash-flow level. The current study analyses the bias of missing data on a selective hedging strategy, where currency options are applied in case of Value at Risk (1% signs. However, there can be special occasions when one or some data is missing due to lack of a trading activity. This paper focuses on the impact of different missing data handling methods on GARCH and Value at Risk model parameters, because of selective hedging and option pricing based on them. The main added value of the current paper is the comparison of the impact of different methods, such as listwise deletion, mean substitution, and maximum likelihood based Expectation Maximization, on risk management because this subject has insufficient literature. The current study tested daily closing data of floating currencies from Kenya (KES, Ghana (GHS, South Africa (ZAR, Tanzania (TZS, Uganda (UGX, Gambia (GMD, Madagascar (MGA and Mozambique (MZN in USD denomination against EUR/USD rate between March 8, 2000 and March 6, 2015 acquired from the Bloomberg database. Our results suggested the biases of missingness on Value at Risk and volatility models, presenting significant differences among the number of extreme fluctuations or model parameters. A selective hedging strategy can have different expenditures due to the choice of method. This paper suggests the usage of mean substitution or listwise deletion for daily financial time series due to their tendency to have a close to zero first momentum

  10. Gender Wage Gap Accounting: The Role of Selection Bias.

    Science.gov (United States)

    Bar, Michael; Kim, Seik; Leukhina, Oksana

    2015-10-01

    Mulligan and Rubinstein (2008) (MR) argued that changing selection of working females on unobservable characteristics, from negative in the 1970s to positive in the 1990s, accounted for nearly the entire closing of the gender wage gap. We argue that their female wage equation estimates are inconsistent. Correcting this error substantially weakens the role of the rising selection bias (39 % versus 78 %) and strengthens the contribution of declining discrimination (42 % versus 7 %). Our findings resonate better with related literature. We also explain why our finding of positive selection in the 1970s provides additional support for MR's main hypothesis that an exogenous rise in the market value of unobservable characteristics contributed to the closing of the gender gap.

  11. Alcohol-related biases in selective attention and action tendency make distinct contributions to dysregulated drinking behaviour.

    Science.gov (United States)

    Sharbanee, Jason M; Stritzke, Werner G K; Wiers, Reinout W; MacLeod, Colin

    2013-10-01

    To assess whether alcohol-related biases in selective-attention and action tendency uniquely or concurrently predict the ability to regulate alcohol consumption. Two groups of undergraduate social drinkers (total n = 55) who differed in their ability to regulate their alcohol consumption completed a novel Selective-Attention/Action-Tendency Task (SA/ATT), which assessed separately alcohol-related biases in selective attention and action tendency. University of Western Australia, Australia. Dysregulated drinking was operationalized as a self-reported high level of alcohol consumption on the Alcohol Consumption Questionnaire, and a high desire to reduce consumption on the Brief Readiness to Change Algorithm. Selective attention and action tendency were assessed using the SA/ATT, working memory was assessed using the operation-span task and participant characteristics were assessed using the Alcohol Use Disorders Identification Test (AUDIT) and Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES). Results indicated that (i) there was no significant association between alcohol-related biases in selective attention and action tendency, r = 0.16, P = 0.274, and (ii) biases towards alcohol, in both selective attention, β = 1.01, odds ratio = 2.74, P = 0.022, and action tendency, β = 1.24, odds ratio = 3.45, P = 0.015, predicted independent variance in dysregulated-drinker status. Biases in selective attention and action tendency appear to be distinct mechanisms that contribute independently to difficulty regulating alcohol consumption. Treatment components that could be combined to target both mechanisms could enhance treatment outcomes for alcohol-use disorders. © 2013 Society for the Study of Addiction.

  12. Codon Deviation Coefficient: A novel measure for estimating codon usage bias and its statistical significance

    KAUST Repository

    Zhang, Zhang

    2012-03-22

    Background: Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB). Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis.Results: Here we propose a novel measure--Codon Deviation Coefficient (CDC)--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance.Conclusions: As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions. 2012 Zhang et al; licensee BioMed Central Ltd.

  13. Sniffing out the Secret Poison: Selection Bias in Educational Research

    Science.gov (United States)

    Showalter, Daniel A.; Mullet, Luke B.

    2017-01-01

    Selection bias is a persistent, and often hidden, problem in educational research. It is the primary obstacle standing in between increasingly available large education datasets and the ability to make valid causal inferences to inform policymaking, research, and practice (Stuart, 2010). This article provides an accessible discussion on the…

  14. Exploring Selective Exposure and Confirmation Bias as Processes Underlying Employee Work Happiness: An Intervention Study.

    Science.gov (United States)

    Williams, Paige; Kern, Margaret L; Waters, Lea

    2016-01-01

    Employee psychological capital (PsyCap), perceptions of organizational virtue (OV), and work happiness have been shown to be associated within and over time. This study examines selective exposure and confirmation bias as potential processes underlying PsyCap, OV, and work happiness associations. As part of a quasi-experimental study design, school staff (N = 69) completed surveys at three time points. After the first assessment, some staff (n = 51) completed a positive psychology training intervention. Results of descriptive statistics, correlation, and regression analyses on the intervention group provide some support for selective exposure and confirmation bias as explanatory mechanisms. In focusing on the processes through which employee attitudes may influence work happiness this study advances theoretical understanding, specifically of selective exposure and confirmation bias in a field study context.

  15. Impact of marker ascertainment bias on genomic selection accuracy and estimates of genetic diversity.

    Directory of Open Access Journals (Sweden)

    Nicolas Heslot

    Full Text Available Genome-wide molecular markers are often being used to evaluate genetic diversity in germplasm collections and for making genomic selections in breeding programs. To accurately predict phenotypes and assay genetic diversity, molecular markers should assay a representative sample of the polymorphisms in the population under study. Ascertainment bias arises when marker data is not obtained from a random sample of the polymorphisms in the population of interest. Genotyping-by-sequencing (GBS is rapidly emerging as a low-cost genotyping platform, even for the large, complex, and polyploid wheat (Triticum aestivum L. genome. With GBS, marker discovery and genotyping occur simultaneously, resulting in minimal ascertainment bias. The previous platform of choice for whole-genome genotyping in many species such as wheat was DArT (Diversity Array Technology and has formed the basis of most of our knowledge about cereals genetic diversity. This study compared GBS and DArT marker platforms for measuring genetic diversity and genomic selection (GS accuracy in elite U.S. soft winter wheat. From a set of 365 breeding lines, 38,412 single nucleotide polymorphism GBS markers were discovered and genotyped. The GBS SNPs gave a higher GS accuracy than 1,544 DArT markers on the same lines, despite 43.9% missing data. Using a bootstrap approach, we observed significantly more clustering of markers and ascertainment bias with DArT relative to GBS. The minor allele frequency distribution of GBS markers had a deficit of rare variants compared to DArT markers. Despite the ascertainment bias of the DArT markers, GS accuracy for three traits out of four was not significantly different when an equal number of markers were used for each platform. This suggests that the gain in accuracy observed using GBS compared to DArT markers was mainly due to a large increase in the number of markers available for the analysis.

  16. Impact of Marker Ascertainment Bias on Genomic Selection Accuracy and Estimates of Genetic Diversity

    Science.gov (United States)

    Heslot, Nicolas; Rutkoski, Jessica; Poland, Jesse; Jannink, Jean-Luc; Sorrells, Mark E.

    2013-01-01

    Genome-wide molecular markers are often being used to evaluate genetic diversity in germplasm collections and for making genomic selections in breeding programs. To accurately predict phenotypes and assay genetic diversity, molecular markers should assay a representative sample of the polymorphisms in the population under study. Ascertainment bias arises when marker data is not obtained from a random sample of the polymorphisms in the population of interest. Genotyping-by-sequencing (GBS) is rapidly emerging as a low-cost genotyping platform, even for the large, complex, and polyploid wheat (Triticum aestivum L.) genome. With GBS, marker discovery and genotyping occur simultaneously, resulting in minimal ascertainment bias. The previous platform of choice for whole-genome genotyping in many species such as wheat was DArT (Diversity Array Technology) and has formed the basis of most of our knowledge about cereals genetic diversity. This study compared GBS and DArT marker platforms for measuring genetic diversity and genomic selection (GS) accuracy in elite U.S. soft winter wheat. From a set of 365 breeding lines, 38,412 single nucleotide polymorphism GBS markers were discovered and genotyped. The GBS SNPs gave a higher GS accuracy than 1,544 DArT markers on the same lines, despite 43.9% missing data. Using a bootstrap approach, we observed significantly more clustering of markers and ascertainment bias with DArT relative to GBS. The minor allele frequency distribution of GBS markers had a deficit of rare variants compared to DArT markers. Despite the ascertainment bias of the DArT markers, GS accuracy for three traits out of four was not significantly different when an equal number of markers were used for each platform. This suggests that the gain in accuracy observed using GBS compared to DArT markers was mainly due to a large increase in the number of markers available for the analysis. PMID:24040295

  17. Measuring Teaching Quality in Higher Education: Assessing Selection Bias in Course Evaluations

    Science.gov (United States)

    Goos, Maarten; Salomons, Anna

    2017-01-01

    Student evaluations of teaching (SETs) are widely used to measure teaching quality in higher education and compare it across different courses, teachers, departments and institutions. Indeed, SETs are of increasing importance for teacher promotion decisions, student course selection, as well as for auditing practices demonstrating institutional…

  18. Precision measurement of the local bias of dark matter halos

    Energy Technology Data Exchange (ETDEWEB)

    Lazeyras, Titouan; Wagner, Christian; Schmidt, Fabian [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, Garching, 85748 Germany (Germany); Baldauf, Tobias, E-mail: titouan@mpa-garching.mpg.de, E-mail: cwagner@mpa-garching.mpg.de, E-mail: t.baldauf@tbaweb.de, E-mail: fabians@mpa-garching.mpg.de [Institute for Advanced Study, Einstein Drive, Princeton, NJ, 08540 United States (United States)

    2016-02-01

    We present accurate measurements of the linear, quadratic, and cubic local bias of dark matter halos, using curved 'separate universe' N-body simulations which effectively incorporate an infinite-wavelength overdensity. This can be seen as an exact implementation of the peak-background split argument. We compare the results with the linear and quadratic bias measured from the halo-matter power spectrum and bispectrum, and find good agreement. On the other hand, the standard peak-background split applied to the Sheth and Tormen (1999) and Tinker et al. (2008) halo mass functions matches the measured linear bias parameter only at the level of 10%. The prediction from the excursion set-peaks approach performs much better, which can be attributed to the stochastic moving barrier employed in the excursion set-peaks prediction. We also provide convenient fitting formulas for the nonlinear bias parameters b{sub 2}(b{sub 1}) and b{sub 3}(b{sub 1}), which work well over a range of redshifts.

  19. Simulating publication bias

    DEFF Research Database (Denmark)

    Paldam, Martin

    is censoring: selection by the size of estimate; SR3 selects the optimal combination of fit and size; and SR4 selects the first satisficing result. The last four SRs are steered by priors and result in bias. The MST and the FAT-PET have been developed for detection and correction of such bias. The simulations......Economic research typically runs J regressions for each selected for publication – it is often selected as the ‘best’ of the regressions. The paper examines five possible meanings of the word ‘best’: SR0 is ideal selection with no bias; SR1 is polishing: selection by statistical fit; SR2...... are made by data variation, while the model is the same. It appears that SR0 generates narrow funnels much at odds with observed funnels, while the other four funnels look more realistic. SR1 to SR4 give the mean a substantial bias that confirms the prior causing the bias. The FAT-PET MRA works well...

  20. Measurement error correction in the least absolute shrinkage and selection operator model when validation data are available.

    Science.gov (United States)

    Vasquez, Monica M; Hu, Chengcheng; Roe, Denise J; Halonen, Marilyn; Guerra, Stefano

    2017-01-01

    Measurement of serum biomarkers by multiplex assays may be more variable as compared to single biomarker assays. Measurement error in these data may bias parameter estimates in regression analysis, which could mask true associations of serum biomarkers with an outcome. The Least Absolute Shrinkage and Selection Operator (LASSO) can be used for variable selection in these high-dimensional data. Furthermore, when the distribution of measurement error is assumed to be known or estimated with replication data, a simple measurement error correction method can be applied to the LASSO method. However, in practice the distribution of the measurement error is unknown and is expensive to estimate through replication both in monetary cost and need for greater amount of sample which is often limited in quantity. We adapt an existing bias correction approach by estimating the measurement error using validation data in which a subset of serum biomarkers are re-measured on a random subset of the study sample. We evaluate this method using simulated data and data from the Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD). We show that the bias in parameter estimation is reduced and variable selection is improved.

  1. Measurement bias of fluid velocity in molecular simulations

    International Nuclear Information System (INIS)

    Tysanner, Martin W.; Garcia, Alejandro L.

    2004-01-01

    In molecular simulations of fluid flow, the measurement of mean fluid velocity is considered to be a straightforward computation, yet there is some ambiguity in its definition. We show that in systems far from equilibrium, such as those with large temperature or velocity gradients, two commonly used definitions give slightly different results. Specifically, a bias can arise when computing the mean fluid velocity by measuring the mean particle velocity in a cell and averaging this mean over samples. We show that this bias comes from the correlation of momentum and density fluctuations in non-equilibrium fluids, obtain an analytical expression for predicting it, and discuss what system characteristics (e.g., number of particles per cell, temperature gradients) reduce or magnify the error. The bias has a physical origin so although we demonstrate it by direct simulation Monte Carlo (DSMC) computations, the same effect will be observed with other particle-based simulation methods, such as molecular dynamics and lattice gases

  2. The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

    Science.gov (United States)

    Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

    2018-01-01

    Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

  3. Disentangling the effects of selection and loss bias on gene dynamics

    NARCIS (Netherlands)

    Iranzo, J.; Cuesta, J.A.; Manrubia, S.; Katsnelson, M.I.; Koonin, E.V.

    2017-01-01

    We combine mathematical modeling of genome evolution with comparative analysis of prokaryotic genomes to estimate the relative contributions of selection and intrinsic loss bias to the evolution of different functional classes of genes and mobile genetic elements (MGE). An exact solution for the

  4. Correction of stream quality trends for the effects of laboratory measurement bias

    Science.gov (United States)

    Alexander, Richard B.; Smith, Richard A.; Schwarz, Gregory E.

    1993-01-01

    We present a statistical model relating measurements of water quality to associated errors in laboratory methods. Estimation of the model allows us to correct trends in water quality for long-term and short-term variations in laboratory measurement errors. An illustration of the bias correction method for a large national set of stream water quality and quality assurance data shows that reductions in the bias of estimates of water quality trend slopes are achieved at the expense of increases in the variance of these estimates. Slight improvements occur in the precision of estimates of trend in bias by using correlative information on bias and water quality to estimate random variations in measurement bias. The results of this investigation stress the need for reliable, long-term quality assurance data and efficient statistical methods to assess the effects of measurement errors on the detection of water quality trends.

  5. The Impact of Selection, Gene Conversion, and Biased Sampling on the Assessment of Microbial Demography.

    Science.gov (United States)

    Lapierre, Marguerite; Blin, Camille; Lambert, Amaury; Achaz, Guillaume; Rocha, Eduardo P C

    2016-07-01

    Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using skyline plots and site frequency spectra (SFS). Forward simulations based on biologically relevant parameters from Escherichia coli populations showed that theoretical arguments on the detrimental impact of recombination and especially natural selection on the reconstructed genealogies cannot be ignored in practice. In fact, both processes systematically lead to spurious interpretations of population expansion in skyline plots (and in SFS for selection). Weak purifying selection, and especially positive selection, had important effects on skyline plots, showing patterns akin to those of population expansions. State-of-the-art techniques to remove recombination further amplified these biases. We simulated three common sampling biases in microbiological research: uniform, clustered, and mixed sampling. Alone, or together with recombination and selection, they further mislead demographic inferences producing almost any possible skyline shape or SFS. Interestingly, sampling sub-populations also affected skyline plots and SFS, because the coalescent rates of populations and their sub-populations had different distributions. This study suggests that extreme caution is needed to infer demographic changes solely based on reconstructed genealogies. We suggest that the development of novel sampling strategies and the joint analyzes of diverse population genetic methods are strictly necessary to estimate demographic changes in populations where selection, recombination, and biased sampling are present. © The Author 2016. Published by Oxford University Press on behalf of the Society for

  6. Bias-Voltage Stabilizer for HVHF Amplifiers in VHF Pulse-Echo Measurement Systems.

    Science.gov (United States)

    Choi, Hojong; Park, Chulwoo; Kim, Jungsuk; Jung, Hayong

    2017-10-23

    The impact of high-voltage-high-frequency (HVHF) amplifiers on echo-signal quality is greater with very-high-frequency (VHF, ≥100 MHz) ultrasound transducers than with low-frequency (LF, ≤15 MHz) ultrasound transducers. Hence, the bias voltage of an HVHF amplifier must be stabilized to ensure stable echo-signal amplitudes. We propose a bias-voltage stabilizer circuit to maintain stable DC voltages over a wide input range, thus reducing the harmonic-distortion components of the echo signals in VHF pulse-echo measurement systems. To confirm the feasibility of the bias-voltage stabilizer, we measured and compared the deviations in the gain of the HVHF amplifier with and without a bias-voltage stabilizer. Between -13 and 26 dBm, the measured gain deviations of a HVHF amplifier with a bias-voltage stabilizer are less than that of an amplifier without a bias-voltage stabilizer. In order to confirm the feasibility of the bias-voltage stabilizer, we compared the pulse-echo responses of the amplifiers, which are typically used for the evaluation of transducers or electronic components used in pulse-echo measurement systems. From the responses, we observed that the amplitudes of the echo signals of a VHF transducer triggered by the HVHF amplifier with a bias-voltage stabilizer were higher than those of the transducer triggered by the HVHF amplifier alone. The second, third, and fourth harmonic-distortion components of the HVHF amplifier with the bias-voltage stabilizer were also lower than those of the HVHF amplifier alone. Hence, the proposed scheme is a promising method for stabilizing the bias voltage of an HVHF amplifier, and improving the echo-signal quality of VHF transducers.

  7. Attitude and gyro bias estimation by the rotation of an inertial measurement unit

    International Nuclear Information System (INIS)

    Wu, Zheming; Sun, Zhenguo; Zhang, Wenzeng; Chen, Qiang

    2015-01-01

    In navigation applications, the presence of an unknown bias in the measurement of rate gyros is a key performance-limiting factor. In order to estimate the gyro bias and improve the accuracy of attitude measurement, we proposed a new method which uses the rotation of an inertial measurement unit, which is independent from rigid body motion. By actively changing the orientation of the inertial measurement unit (IMU), the proposed method generates sufficient relations between the gyro bias and tilt angle (roll and pitch) error via ridge body dynamics, and the gyro bias, including the bias that causes the heading error, can be estimated and compensated. The rotation inertial measurement unit method makes the gravity vector measured from the IMU continuously change in a body-fixed frame. By theoretically analyzing the mathematic model, the convergence of the attitude and gyro bias to the true values is proven. The proposed method provides a good attitude estimation using only measurements from an IMU, when other sensors such as magnetometers and GPS are unreliable. The performance of the proposed method is illustrated under realistic robotic motions and the results demonstrate an improvement in the accuracy of the attitude estimation. (paper)

  8. National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models

    Science.gov (United States)

    Hogan, Daniel R; Salomon, Joshua A; Canning, David; Hammitt, James K; Zaslavsky, Alan M; Bärnighausen, Till

    2012-01-01

    Objectives Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors. Methods For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals. Results Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5. Conclusions Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence. PMID:23172342

  9. A measurement system for two-dimensional DC-biased properties of magnetic materials

    International Nuclear Information System (INIS)

    Enokizono, M.; Matsuo, H.

    2003-01-01

    So far, the DC-biased magnetic properties have been measured in one dimension (scalar). However, these scalar magnetic properties are not enough to clarify the DC-biased magnetic properties because the scalar magnetic properties cannot exactly take into account the phase difference between the magnetic flux density B vector and the magnetic filed strength H vector. Thus, the magnetic field strength H and magnetic flux density B in magnetic materials must be measured as vector quantities (two-dimensional), directly. We showed the measurement system using a single-sheet tester (SST) to clarify the two-dimensional DC-biased magnetic properties. This system excited AC in Y-direction and DC in X-direction. This paper shows the measurement system using an SST and presents the measurement results of two-dimensional DC-biased magnetic properties when changing the DC exciting voltage and the iron loss

  10. Bias in random forest variable importance measures: Illustrations, sources and a solution

    Directory of Open Access Journals (Sweden)

    Hothorn Torsten

    2007-01-01

    Full Text Available Abstract Background Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and related scientific fields, for instance to select a subset of genetic markers relevant for the prediction of a certain disease. We show that random forest variable importance measures are a sensible means for variable selection in many applications, but are not reliable in situations where potential predictor variables vary in their scale of measurement or their number of categories. This is particularly important in genomics and computational biology, where predictors often include variables of different types, for example when predictors include both sequence data and continuous variables such as folding energy, or when amino acid sequence data show different numbers of categories. Results Simulation studies are presented illustrating that, when random forest variable importance measures are used with data of varying types, the results are misleading because suboptimal predictor variables may be artificially preferred in variable selection. The two mechanisms underlying this deficiency are biased variable selection in the individual classification trees used to build the random forest on one hand, and effects induced by bootstrap sampling with replacement on the other hand. Conclusion We propose to employ an alternative implementation of random forests, that provides unbiased variable selection in the individual classification trees. When this method is applied using subsampling without replacement, the resulting variable importance measures can be used reliably for variable selection even in situations where the potential predictor variables vary in their scale of measurement or their number of categories. The usage of both random forest algorithms and their variable importance measures in the R system for statistical computing is illustrated and

  11. Selection bias and the perils of benchmarking.

    Science.gov (United States)

    Denrell, Jerker

    2005-04-01

    To find the secrets of business success, what could be more natural than studying successful businesses? In fact, nothing could be more dangerous, warns this Stanford professor. Generalizing from the examples of successful companies is like generalizing about New England weather from data taken only in the summer. That's essentially what businesspeople do when they learn from good examples and what consultants, authors, and researchers do when they study only existing companies or--worse yet--only high-performing companies. They reach conclusions from unrepresentative data samples, falling into the classic statistical trap of selection bias. Drawing on a wealth of case studies, for instance, one researcher concluded that great leaders share two key traits: They persist, often despite initial failures, and they are able to persuade others to join them. But those traits are also the hallmarks of spectacularly unsuccessful entrepreneurs, who must persist in the face of failure to incur large losses and must be able to persuade others to pour their money down the drain. To discover what makes a business successful, then, managers should look at both successes and failures. Otherwise, they will overvalue risky business practices, seeing only those companies that won big and not the ones that lost dismally. They will not be able to tell if their current good fortune stems from smart business practices or if they are actually coasting on past accomplishments or good luck. Fortunately, economists have developed relatively simple tools that can correct for selection bias even when data about failed companies are hard to come by. Success may be inspirational, but managers are more likely to find the secrets of high performance if they give the stories of their competitors'failures as full a hearing as they do the stories of dazzling successes.

  12. Visual selective attention biases contribute to the other-race effect among 9-month-old infants.

    Science.gov (United States)

    Markant, Julie; Oakes, Lisa M; Amso, Dima

    2016-04-01

    During the first year of life, infants maintain their ability to discriminate faces from their own race but become less able to differentiate other-race faces. Though this is likely due to daily experience with own-race faces, the mechanisms linking repeated exposure to optimal face processing remain unclear. One possibility is that frequent experience with own-race faces generates a selective attention bias to these faces. Selective attention elicits enhancement of attended information and suppression of distraction to improve visual processing of attended objects. Thus attention biases to own-race faces may boost processing and discrimination of these faces relative to other-race faces. We used a spatial cueing task to bias attention to own- or other-race faces among Caucasian 9-month-old infants. Infants discriminated faces in the focus of the attention bias, regardless of race, indicating that infants remained sensitive to differences among other-race faces. Instead, efficacy of face discrimination reflected the extent of attention engagement. © 2015 Wiley Periodicals, Inc.

  13. A method of bias correction for maximal reliability with dichotomous measures.

    Science.gov (United States)

    Penev, Spiridon; Raykov, Tenko

    2010-02-01

    This paper is concerned with the reliability of weighted combinations of a given set of dichotomous measures. Maximal reliability for such measures has been discussed in the past, but the pertinent estimator exhibits a considerable bias and mean squared error for moderate sample sizes. We examine this bias, propose a procedure for bias correction, and develop a more accurate asymptotic confidence interval for the resulting estimator. In most empirically relevant cases, the bias correction and mean squared error correction can be performed simultaneously. We propose an approximate (asymptotic) confidence interval for the maximal reliability coefficient, discuss the implementation of this estimator, and investigate the mean squared error of the associated asymptotic approximation. We illustrate the proposed methods using a numerical example.

  14. Correction of Selection Bias in Survey Data: Is the Statistical Cure Worse Than the Bias?

    Science.gov (United States)

    Hanley, James A

    2017-04-01

    In previous articles in the American Journal of Epidemiology (Am J Epidemiol. 2013;177(5):431-442) and American Journal of Public Health (Am J Public Health. 2013;103(10):1895-1901), Masters et al. reported age-specific hazard ratios for the contrasts in mortality rates between obesity categories. They corrected the observed hazard ratios for selection bias caused by what they postulated was the nonrepresentativeness of the participants in the National Health Interview Study that increased with age, obesity, and ill health. However, it is possible that their regression approach to remove the alleged bias has not produced, and in general cannot produce, sensible hazard ratio estimates. First, we must consider how many nonparticipants there might have been in each category of obesity and of age at entry and how much higher the mortality rates would have to be in nonparticipants than in participants in these same categories. What plausible set of numerical values would convert the ("biased") decreasing-with-age hazard ratios seen in the data into the ("unbiased") increasing-with-age ratios that they computed? Can these values be encapsulated in (and can sensible values be recovered from) one additional internal variable in a regression model? Second, one must examine the age pattern of the hazard ratios that have been adjusted for selection. Without the correction, the hazard ratios are attenuated with increasing age. With it, the hazard ratios at older ages are considerably higher, but those at younger ages are well below one. Third, one must test whether the regression approach suggested by Masters et al. would correct the nonrepresentativeness that increased with age and ill health that I introduced into real and hypothetical data sets. I found that the approach did not recover the hazard ratio patterns present in the unselected data sets: the corrections overshot the target at older ages and undershot it at lower ages.

  15. Quantifying the impact of selection bias caused by nonparticipation in a case-control study of mobile phone use

    DEFF Research Database (Denmark)

    Vrijheid, Martine; Richardson, Lesley; Armstrong, Bruce K

    2009-01-01

    To quantitatively assess the impact of selection bias caused by nonparticipation in a multinational case-control study of mobile phone use and brain tumor.......To quantitatively assess the impact of selection bias caused by nonparticipation in a multinational case-control study of mobile phone use and brain tumor....

  16. Selection bias in family reports on end of life with dementia in nursing homes

    NARCIS (Netherlands)

    van der Steen, J.T.; Deliens, L.; Ribbe, M.W.; Onwuteaka-Philipsen, B.D.

    2012-01-01

    Background: Selective participation in retrospective studies of families recruited after the patient's death may threaten generalizability of reports on end-of-life experiences. Objectives: To assess possible selection bias in retrospective study of dementia at the end of life using family reports.

  17. Impact of selective genotyping in the training population on accuracy and bias of genomic selection.

    Science.gov (United States)

    Zhao, Yusheng; Gowda, Manje; Longin, Friedrich H; Würschum, Tobias; Ranc, Nicolas; Reif, Jochen C

    2012-08-01

    Estimating marker effects based on routinely generated phenotypic data of breeding programs is a cost-effective strategy to implement genomic selection. Truncation selection in breeding populations, however, could have a strong impact on the accuracy to predict genomic breeding values. The main objective of our study was to investigate the influence of phenotypic selection on the accuracy and bias of genomic selection. We used experimental data of 788 testcross progenies from an elite maize breeding program. The testcross progenies were evaluated in unreplicated field trials in ten environments and fingerprinted with 857 SNP markers. Random regression best linear unbiased prediction method was used in combination with fivefold cross-validation based on genotypic sampling. We observed a substantial loss in the accuracy to predict genomic breeding values in unidirectional selected populations. In contrast, estimating marker effects based on bidirectional selected populations led to only a marginal decrease in the prediction accuracy of genomic breeding values. We concluded that bidirectional selection is a valuable approach to efficiently implement genomic selection in applied plant breeding programs.

  18. [Inverse probability weighting (IPW) for evaluating and "correcting" selection bias].

    Science.gov (United States)

    Narduzzi, Silvia; Golini, Martina Nicole; Porta, Daniela; Stafoggia, Massimo; Forastiere, Francesco

    2014-01-01

    the Inverse probability weighting (IPW) is a methodology developed to account for missingness and selection bias caused by non-randomselection of observations, or non-random lack of some information in a subgroup of the population. to provide an overview of IPW methodology and an application in a cohort study of the association between exposure to traffic air pollution (nitrogen dioxide, NO₂) and 7-year children IQ. this methodology allows to correct the analysis by weighting the observations with the probability of being selected. The IPW is based on the assumption that individual information that can predict the probability of inclusion (non-missingness) are available for the entire study population, so that, after taking account of them, we can make inferences about the entire target population starting from the nonmissing observations alone.The procedure for the calculation is the following: firstly, we consider the entire population at study and calculate the probability of non-missing information using a logistic regression model, where the response is the nonmissingness and the covariates are its possible predictors.The weight of each subject is given by the inverse of the predicted probability. Then the analysis is performed only on the non-missing observations using a weighted model. IPW is a technique that allows to embed the selection process in the analysis of the estimates, but its effectiveness in "correcting" the selection bias depends on the availability of enough information, for the entire population, to predict the non-missingness probability. In the example proposed, the IPW application showed that the effect of exposure to NO2 on the area of verbal intelligence quotient of children is stronger than the effect showed from the analysis performed without regard to the selection processes.

  19. Attention, interpretation, and memory biases in subclinical depression: a proof-of-principle test of the combined cognitive biases hypothesis.

    Science.gov (United States)

    Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

    2014-04-01

    Emotional biases in attention, interpretation, and memory are viewed as important cognitive processes underlying symptoms of depression. To date, there is a limited understanding of the interplay among these processing biases. This study tested the dependence of memory on depression-related biases in attention and interpretation. Subclinically depressed and nondepressed participants completed a computerized version of the scrambled sentences test (measuring interpretation bias) while their eye movements were recorded (measuring attention bias). This task was followed by an incidental free recall test of previously constructed interpretations (measuring memory bias). Path analysis revealed a good fit for the model in which selective orienting of attention was associated with interpretation bias, which in turn was associated with a congruent bias in memory. Also, a good fit was observed for a path model in which biases in the maintenance of attention and interpretation were associated with memory bias. Both path models attained a superior fit compared with path models without the theorized functional relations among processing biases. These findings enhance understanding of how mechanisms of attention and interpretation regulate what is remembered. As such, they offer support for the combined cognitive biases hypothesis or the notion that emotionally biased cognitive processes are not isolated mechanisms but instead influence each other. Implications for theoretical models and emotion regulation across the spectrum of depressive symptoms are discussed.

  20. Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

    Science.gov (United States)

    Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

    2016-10-01

    Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

  1. Calibration of colour gradient bias in shear measurement using HST/CANDELS data

    Science.gov (United States)

    Er, X.; Hoekstra, H.; Schrabback, T.; Cardone, V. F.; Scaramella, R.; Maoli, R.; Vicinanza, M.; Gillis, B.; Rhodes, J.

    2018-06-01

    Accurate shape measurements are essential to infer cosmological parameters from large area weak gravitational lensing studies. The compact diffraction-limited point spread function (PSF) in space-based observations is greatly beneficial, but its chromaticity for a broad-band observation can lead to new subtle effects that could hitherto be ignored: the PSF of a galaxy is no longer uniquely defined and spatial variations in the colours of galaxies result in biases in the inferred lensing signal. Taking Euclid as a reference, we show that this colour gradient bias (CG bias) can be quantified with high accuracy using available multicolour Hubble Space Telescope (HST) data. In particular we study how noise in the HST observations might impact such measurements and find this to be negligible. We determine the CG bias using HST observations in the F606W and F814W filters and observe a correlation with the colour, in line with expectations, whereas the dependence with redshift is weak. The biases for individual galaxies are generally well below 1 per cent, which may be reduced further using morphological information from the Euclid data. Our results demonstrate that CG bias should not be ignored, but it is possible to determine its amplitude with sufficient precision, so that it will not significantly bias the weak lensing measurements using Euclid data.

  2. A Model of Gravity Vector Measurement Noise for Estimating Accelerometer Bias in Gravity Disturbance Compensation.

    Science.gov (United States)

    Tie, Junbo; Cao, Juliang; Chang, Lubing; Cai, Shaokun; Wu, Meiping; Lian, Junxiang

    2018-03-16

    Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method.

  3. A Model of Gravity Vector Measurement Noise for Estimating Accelerometer Bias in Gravity Disturbance Compensation

    Science.gov (United States)

    Cao, Juliang; Cai, Shaokun; Wu, Meiping; Lian, Junxiang

    2018-01-01

    Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method. PMID:29547552

  4. Selection bias in studies of human reproduction-longevity trade-offs.

    Science.gov (United States)

    Helle, Samuli

    2017-12-13

    A shorter lifespan as a potential cost of high reproductive effort in humans has intrigued researchers for more than a century. However, the results have been inconclusive so far and despite strong theoretical expectations we do not currently have compelling evidence for the longevity costs of reproduction. Using Monte Carlo simulation, it is shown here that a common practice in human reproduction-longevity studies using historical data (the most relevant data sources for this question), the omission of women who died prior to menopausal age from the analysis, results in severe underestimation of the potential underlying trade-off between reproduction and lifespan. In other words, assuming that such a trade-off is expressed also during reproductive years, the strength of the trade-off between reproduction and lifespan is progressively weakened when women dying during reproductive ages are sequentially and non-randomly excluded from the analysis. In cases of small sample sizes (e.g. few hundreds of observations), this selection bias by reducing statistical power may even partly explain the null results commonly found in this field. Future studies in this field should thus apply statistical approaches that account for or avoid selection bias in order to recover reliable effect size estimates between reproduction and longevity. © 2017 The Author(s).

  5. Mixed signals: The effect of conflicting reward- and goal-driven biases on selective attention.

    Science.gov (United States)

    Preciado, Daniel; Munneke, Jaap; Theeuwes, Jan

    2017-07-01

    Attentional selection depends on the interaction between exogenous (stimulus-driven), endogenous (goal-driven), and selection history (experience-driven) factors. While endogenous and exogenous biases have been widely investigated, less is known about their interplay with value-driven attention. The present study investigated the interaction between reward-history and goal-driven biases on perceptual sensitivity (d') and response time (RT) in a modified cueing paradigm presenting two coloured cues, followed by sinusoidal gratings. Participants responded to the orientation of one of these gratings. In Experiment 1, one cue signalled reward availability but was otherwise task irrelevant. In Experiment 2, the same cue signalled reward, and indicated the target's most likely location at the opposite side of the display. This design introduced a conflict between reward-driven biases attracting attention and goal-driven biases directing it away. Attentional effects were examined comparing trials in which cue and target appeared at the same versus opposite locations. Two interstimulus interval (ISI) levels were used to probe the time course of attentional effects. Experiment 1 showed performance benefits at the location of the reward-signalling cue and costs at the opposite for both ISIs, indicating value-driven capture. Experiment 2 showed performance benefits only for the long ISI when the target was at the opposite to the reward-associated cue. At the short ISI, only performance costs were observed. These results reveal the time course of these biases, indicating that reward-driven effects influence attention early but can be overcome later by goal-driven control. This suggests that reward-driven biases are integrated as attentional priorities, just as exogenous and endogenous factors.

  6. Perceptual Color Space Representations in the Oculomotor System Are Modulated by Surround Suppression and Biased Selection

    Directory of Open Access Journals (Sweden)

    Devin H. Kehoe

    2018-01-01

    Full Text Available The oculomotor system utilizes color extensively for planning saccades. Therefore, we examined how the oculomotor system actually encodes color and several factors that modulate these representations: attention-based surround suppression and inherent biases in selecting and encoding color categories. We measured saccade trajectories while human participants performed a memory-guided saccade task with color targets and distractors and examined whether oculomotor target selection processing was functionally related to the CIE (x,y color space distances between color stimuli and whether there were hierarchical differences between color categories in the strength and speed of encoding potential saccade goals. We observed that saccade planning was modulated by the CIE (x,y distances between stimuli thus demonstrating that color is encoded in perceptual color space by the oculomotor system. Furthermore, these representations were modulated by (1 cueing attention to a particular color thereby eliciting surround suppression in oculomotor color space and (2 inherent selection and encoding biases based on color category independent of cueing and perceptual discriminability. Since surround suppression emerges from recurrent feedback attenuation of sensory projections, observing oculomotor surround suppression suggested that oculomotor encoding of behavioral relevance results from integrating sensory and cognitive signals that are pre-attenuated based on task demands and that the oculomotor system therefore does not functionally contribute to this process. Second, although perceptual discriminability did partially account for oculomotor processing differences between color categories, we also observed preferential processing of the red color category across various behavioral metrics. This is consistent with numerous previous studies and could not be simply explained by perceptual discriminability. Since we utilized a memory-guided saccade task, this

  7. Perceptual Color Space Representations in the Oculomotor System Are Modulated by Surround Suppression and Biased Selection.

    Science.gov (United States)

    Kehoe, Devin H; Rahimi, Maryam; Fallah, Mazyar

    2018-01-01

    The oculomotor system utilizes color extensively for planning saccades. Therefore, we examined how the oculomotor system actually encodes color and several factors that modulate these representations: attention-based surround suppression and inherent biases in selecting and encoding color categories. We measured saccade trajectories while human participants performed a memory-guided saccade task with color targets and distractors and examined whether oculomotor target selection processing was functionally related to the CIE ( x , y ) color space distances between color stimuli and whether there were hierarchical differences between color categories in the strength and speed of encoding potential saccade goals. We observed that saccade planning was modulated by the CIE ( x , y ) distances between stimuli thus demonstrating that color is encoded in perceptual color space by the oculomotor system. Furthermore, these representations were modulated by (1) cueing attention to a particular color thereby eliciting surround suppression in oculomotor color space and (2) inherent selection and encoding biases based on color category independent of cueing and perceptual discriminability. Since surround suppression emerges from recurrent feedback attenuation of sensory projections, observing oculomotor surround suppression suggested that oculomotor encoding of behavioral relevance results from integrating sensory and cognitive signals that are pre-attenuated based on task demands and that the oculomotor system therefore does not functionally contribute to this process. Second, although perceptual discriminability did partially account for oculomotor processing differences between color categories, we also observed preferential processing of the red color category across various behavioral metrics. This is consistent with numerous previous studies and could not be simply explained by perceptual discriminability. Since we utilized a memory-guided saccade task, this indicates that

  8. REAL-TIME ANALYSIS AND SELECTION BIASES IN THE SUPERNOVA LEGACY SURVEY

    International Nuclear Information System (INIS)

    Perrett, K.; Conley, A.; Carlberg, R.; Balam, D.; Hook, I. M.; Sullivan, M.; Pritchet, C.; Astier, P.; Balland, C.; Guy, J.; Hardin, D.; Pain, R.; Regnault, N.; Basa, S.; Fouchez, D.; Howell, D. A.

    2010-01-01

    The Supernova Legacy Survey (SNLS) has produced a high-quality, homogeneous sample of Type Ia supernovae (SNe Ia) out to redshifts greater than z = 1. In its first four years of full operation (to 2007 June), the SNLS discovered more than 3000 transient candidates, 373 of which have been spectroscopically confirmed as SNe Ia. Use of these SNe Ia in precision cosmology critically depends on an analysis of the observational biases incurred in the SNLS survey due to the incomplete sampling of the underlying SN Ia population. This paper describes our real-time supernova detection and analysis procedures, and uses detailed Monte Carlo simulations to examine the effects of Malmquist bias and spectroscopic sampling. Such sampling effects are found to become apparent at z ∼ 0.6, with a significant shift in the average magnitude of the spectroscopically confirmed SN Ia sample toward brighter values for z ∼> 0.75. We describe our approach to correct for these selection biases in our three-year SNLS cosmological analysis (SNLS3) and present a breakdown of the systematic uncertainties involved.

  9. The Bias in Bayes and How to Measure it

    Directory of Open Access Journals (Sweden)

    D.A. S. Fraser

    2012-07-01

    Full Text Available A Bayes prior with a likelihood can give approximate confidence and provide a remarkably flexible approach to statistical inference; but is also known to provide inaccurate perhaps incorrect results. We develop a measure of Bayes bias, first examining a simple Normal model and then progressing to quite general models with scalar and vector parameters. The Bias measure can be interpreted as the lateral displacement of the location standardized likelihood function and thus provides ready access to the effect of a prior on p-values, confidence bounds, and Bayes posterior bounds. The needed computation is comparable to that for the likelihood function and thus provides an initial option for checking merits of Bayesian computation for high dimensions.

  10. Correction for dynamic bias error in transmission measurements of void fraction

    International Nuclear Information System (INIS)

    Andersson, P.; Sundén, E. Andersson; Svärd, S. Jacobsson; Sjöstrand, H.

    2012-01-01

    Dynamic bias errors occur in transmission measurements, such as X-ray, gamma, or neutron radiography or tomography. This is observed when the properties of the object are not stationary in time and its average properties are assessed. The nonlinear measurement response to changes in transmission within the time scale of the measurement implies a bias, which can be difficult to correct for. A typical example is the tomographic or radiographic mapping of void content in dynamic two-phase flow systems. In this work, the dynamic bias error is described and a method to make a first-order correction is derived. A prerequisite for this method is variance estimates of the system dynamics, which can be obtained using high-speed, time-resolved data acquisition. However, in the absence of such acquisition, a priori knowledge might be used to substitute the time resolved data. Using synthetic data, a void fraction measurement case study has been simulated to demonstrate the performance of the suggested method. The transmission length of the radiation in the object under study and the type of fluctuation of the void fraction have been varied. Significant decreases in the dynamic bias error were achieved to the expense of marginal decreases in precision.

  11. MEASUREMENT OF THE HALO BIAS FROM STACKED SHEAR PROFILES OF GALAXY CLUSTERS

    Energy Technology Data Exchange (ETDEWEB)

    Covone, Giovanni [Dipartimento di Fisica, Università di Napoli " Federico II," Via Cinthia, I-80126 Napoli (Italy); Sereno, Mauro [Dipartimento di Fisica e Astronomia, Università di Bologna, Viale Berti Pichat 6/2, I-40127 Bologna (Italy); Kilbinger, Martin [CEA/Irfu/SAp Saclay, Laboratoire AIM, F-91191 Gif-sur-Yvette (France); Cardone, Vincenzo F. [I.N.A.F.-Osservatorio Astronomico di Roma, Via Frascati 33, I-00040 Monteporzio Catone (Roma) (Italy)

    2014-04-01

    We present observational evidence of the two-halo term in the stacked shear profile of a sample of ∼1200 optically selected galaxy clusters based on imaging data and the public shear catalog from the CFHTLenS. We find that the halo bias, a measure of the correlated distribution of matter around galaxy clusters, has amplitude and correlation with galaxy cluster mass in very good agreement with the predictions based on the LCDM standard cosmological model. The mass-concentration relation is flat but higher than theoretical predictions. We also confirm the close scaling relation between the optical richness of galaxy clusters and their mass.

  12. GALAXY BIAS AND ITS EFFECTS ON THE BARYON ACOUSTIC OSCILLATION MEASUREMENTS

    International Nuclear Information System (INIS)

    Mehta, Kushal T.; Eckel, Jonathan; Eisenstein, Daniel J.; Metchnik, Marc; Pinto, Philip; Xu Xiaoying; Seo, Hee-Jong

    2011-01-01

    The baryon acoustic oscillation (BAO) feature in the clustering of matter in the universe serves as a robust standard ruler and hence can be used to map the expansion history of the universe. We use high force resolution simulations to analyze the effects of galaxy bias on the measurements of the BAO signal. We apply a variety of Halo Occupation Distributions (HODs) and produce biased mass tracers to mimic different galaxy populations. We investigate whether galaxy bias changes the nonlinear shifts on the acoustic scale relative to the underlying dark matter distribution presented by Seo et al. For the less biased HOD models (b 3) show a shift at moderate significance (0.79% ± 0.31% for the most extreme case). We test the one-step reconstruction technique introduced by Eisenstein et al. in the case of realistic galaxy bias and shot noise. The reconstruction scheme increases the correlation between the initial and final (z = 1) density fields, achieving an equivalent level of correlation at nearly twice the wavenumber after reconstruction. Reconstruction reduces the shifts and errors on the shifts. We find that after reconstruction the shifts from the galaxy cases and the dark matter case are consistent with each other and with no shift. The 1σ systematic errors on the distance measurements inferred from our BAO measurements with various HODs after reconstruction are about 0.07%-0.15%.

  13. A new method to measure galaxy bias by combining the density and weak lensing fields

    Energy Technology Data Exchange (ETDEWEB)

    Pujol, Arnau; Chang, Chihway; Gaztañaga, Enrique; Amara, Adam; Refregier, Alexandre; Bacon, David J.; Carretero, Jorge; Castander, Francisco J.; Crocce, Martin; Fosalba, Pablo; Manera, Marc; Vikram, Vinu

    2016-07-29

    We present a new method to measure redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on the work of Amara et al., who use the galaxy density field to construct a bias-weighted convergence field κg. The main difference between Amara et al.'s work and our new implementation is that here we present another way to measure galaxy bias, using tomography instead of bias parametrizations. The correlation between κg and the true lensing field κ allows us to measure galaxy bias using different zero-lag correlations, such as <κgκ>/<κκ> or <κgκg>/<κgκ>. Our method measures the linear bias factor on linear scales, under the assumption of no stochasticity between galaxies and matter. We use the Marenostrum Institut de Ciències de l'Espai (MICE) simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This article is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method and the regime in which it is consistent with the linear galaxy bias defined by projected two-point correlation functions (2PCF). We find that our method is consistent with a linear bias at the per cent level for scales larger than 30 arcmin, while non-linearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on σ8 as do the 2PCF measurements. We will apply this method to the Dark Energy Survey Science Verification data in a follow-up article.

  14. Reducing biases on H0 measurements using strong lensing and galaxy dynamics: results from the EAGLE simulation

    Science.gov (United States)

    Tagore, Amitpal S.; Barnes, David J.; Jackson, Neal; Kay, Scott T.; Schaller, Matthieu; Schaye, Joop; Theuns, Tom

    2018-03-01

    Cosmological parameter constraints from observations of time-delay lenses are becoming increasingly precise. However, there may be significant bias and scatter in these measurements due to, among other things, the so-called mass-sheet degeneracy. To estimate these uncertainties, we analyse strong lenses from the largest EAGLE hydrodynamical simulation. We apply a mass-sheet transformation to the radial density profiles of lenses, and by selecting lenses near isothermality, we find that the bias on H0 can be reduced to 5 per cent with an intrinsic scatter of 10 per cent, confirming previous results performed on a different simulation data set. We further investigate whether combining lensing observables with kinematic constraints helps to minimize this bias. We do not detect any significant dependence of the bias on lens model parameters or observational properties of the galaxy, but depending on the source-lens configuration, a bias may still exist. Cross lenses provide an accurate estimate of the Hubble constant, while fold (double) lenses tend to be biased low (high). With kinematic constraints, double lenses show bias and intrinsic scatter of 6 per cent and 10 per cent, respectively, while quad lenses show bias and intrinsic scatter of 0.5 per cent and 10 per cent, respectively. For lenses with a reduced χ2 > 1, a power-law dependence of the χ2 on the lens environment (number of nearby galaxies) is seen. Lastly, we model, in greater detail, the cases of two double lenses that are significantly biased. We are able to remove the bias, suggesting that the remaining biases could also be reduced by carefully taking into account additional sources of systematic uncertainty.

  15. Codon usage bias analysis for the coding sequences of Camellia ...

    African Journals Online (AJOL)

    sunny t

    2016-02-24

    Feb 24, 2016 ... suggested that codon usage bias is driven by selection, particularly for .... For example, as mentioned above, highly expressed genes tend to use fewer ... directional codon bias measure effective number of codons (ENc) was ...

  16. Stimulus-Driven Attention, Threat Bias, and Sad Bias in Youth with a History of an Anxiety Disorder or Depression.

    Science.gov (United States)

    Sylvester, Chad M; Hudziak, James J; Gaffrey, Michael S; Barch, Deanna M; Luby, Joan L

    2016-02-01

    Attention biases towards threatening and sad stimuli are associated with pediatric anxiety and depression, respectively. The basic cognitive mechanisms associated with attention biases in youth, however, remain unclear. Here, we tested the hypothesis that threat bias (selective attention for threatening versus neutral stimuli) but not sad bias relies on stimulus-driven attention. We collected measures of stimulus-driven attention, threat bias, sad bias, and current clinical symptoms in youth with a history of an anxiety disorder and/or depression (ANX/DEP; n = 40) as well as healthy controls (HC; n = 33). Stimulus-driven attention was measured with a non-emotional spatial orienting task, while threat bias and sad bias were measured at a short time interval (150 ms) with a spatial orienting task using emotional faces and at a longer time interval (500 ms) using a dot-probe task. In ANX/DEP but not HC, early attention bias towards threat was negatively correlated with later attention bias to threat, suggesting that early threat vigilance was associated with later threat avoidance. Across all subjects, stimulus-driven orienting was not correlated with early threat bias but was negatively correlated with later threat bias, indicating that rapid stimulus-driven orienting is linked to later threat avoidance. No parallel relationships were detected for sad bias. Current symptoms of depression but not anxiety were related to decreased stimulus-driven attention. Together, these results are consistent with the hypothesis that threat bias but not sad bias relies on stimulus-driven attention. These results inform the design of attention bias modification programs that aim to reverse threat biases and reduce symptoms associated with pediatric anxiety and depression.

  17. Stimulus-driven attention, threat bias, and sad bias in youth with a history of an anxiety disorder or depression

    Science.gov (United States)

    Sylvester, Chad M.; Hudziak, James J.; Gaffrey, Michael S.; Barch, Deanna M.; Luby, Joan L.

    2015-01-01

    Attention biases towards threatening and sad stimuli are associated with pediatric anxiety and depression, respectively. The basic cognitive mechanisms associated with attention biases in youth, however, remain unclear. Here, we tested the hypothesis that threat bias (selective attention for threatening versus neutral stimuli) but not sad bias relies on stimulus-driven attention. We collected measures of stimulus-driven attention, threat bias, sad bias, and current clinical symptoms in youth with a history of an anxiety disorder and/or depression (ANX/DEP; n=40) as well as healthy controls (HC; n=33). Stimulus-driven attention was measured with a non-emotional spatial orienting task, while threat bias and sad bias were measured at a short time interval (150 ms) with a spatial orienting task using emotional faces and at a longer time interval (500 ms) using a dot-probe task. In ANX/DEP but not HC, early attention bias towards threat was negatively correlated with later attention bias to threat, suggesting that early threat vigilance was associated with later threat avoidance. Across all subjects, stimulus-driven orienting was not correlated with early threat bias but was negatively correlated with later threat bias, indicating that rapid stimulus-driven orienting is linked to later threat avoidance. No parallel relationships were detected for sad bias. Current symptoms of depression but not anxiety were related to decreased stimulus-driven attention. Together, these results are consistent with the hypothesis that threat bias but not sad bias relies on stimulus-driven attention. These results inform the design of attention bias modification programs that aim to reverse threat biases and reduce symptoms associated with pediatric anxiety and depression. PMID:25702927

  18. Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements.

    Science.gov (United States)

    Malyarenko, Dariya I; Ross, Brian D; Chenevert, Thomas L

    2014-03-01

    Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Copyright © 2013 Wiley Periodicals, Inc.

  19. Bias in patient satisfaction surveys: a threat to measuring healthcare quality.

    Science.gov (United States)

    Dunsch, Felipe; Evans, David K; Macis, Mario; Wang, Qiao

    2018-01-01

    Patient satisfaction surveys are an increasingly common element of efforts to evaluate the quality of healthcare. Many patient satisfaction surveys in low/middle-income countries frame statements positively and invite patients to agree or disagree, so that positive responses may reflect either true satisfaction or bias induced by the positive framing. In an experiment with more than 2200 patients in Nigeria, we distinguish between actual satisfaction and survey biases. Patients randomly assigned to receive negatively framed statements expressed significantly lower levels of satisfaction (87%) than patients receiving the standard positively framed statements (95%-pquality of health services. Providers and policymakers wishing to gauge the quality of care will need to avoid framing that induces bias and to complement patient satisfaction measures with more objective measures of quality.

  20. Galaxy Bias and its Effects on the Baryon Acoustic Oscillations Measurements

    International Nuclear Information System (INIS)

    Mehta, Kushal T.; Seo, Hee-Jong; Eckel, Jonathan; Eisenstein, Daniel J.; Metchnik, Marc; Pinto, Philip; Xu, Xiaoying

    2011-01-01

    The baryon acoustic oscillation (BAO) feature in the clustering of matter in the universe serves as a robust standard ruler and hence can be used to map the expansion history of the universe. We use high force resolution simulations to analyze the effects of galaxy bias on the measurements of the BAO signal. We apply a variety of Halo Occupation Distributions (HODs) and produce biased mass tracers to mimic different galaxy populations. We investigate whether galaxy bias changes the non-linear shifts on the acoustic scale relative to the underlying dark matter distribution presented by Seo et al. (2009). For the less biased HOD models (b 3) show a shift at moderate significance (0.79% ± 0.31% for the most extreme case). We test the one-step reconstruction technique introduced by Eisenstein et al. (2007) in the case of realistic galaxy bias and shot noise. The reconstruction scheme increases the correlation between the initial and final (z = 1) density fields achieving an equivalent level of correlation at nearly twice the wavenumber after reconstruction. Reconstruction reduces the shifts and errors on the shifts. We find that after reconstruction the shifts from the galaxy cases and the dark matter case are consistent with each other and with no shift. The 1σ systematic errors on the distance measurements inferred from our BAO measurements with various HODs after reconstruction are about 0.07%-0.15%.

  1. Mini biased collimated faraday cups for measurement of intense pulsed ion beams

    International Nuclear Information System (INIS)

    He Xiaoping; Shi Lei; Zhang Jiasheng; Qiu Aici

    2000-01-01

    An analysis of principle of a biased Faraday cup for measuring ion beams density and the main reasons related to the measuring accuracy were presented. An array of mini biased collimated Faraday cups was manufactured for the measurement of ion beam density of a compact 200 keV high power ion beam source. In the experiments the maximum density of ion beam was in the center of the beam, and it was about 170 A/cm 2

  2. Maximum likelihood estimation and EM algorithm of Copas-like selection model for publication bias correction.

    Science.gov (United States)

    Ning, Jing; Chen, Yong; Piao, Jin

    2017-07-01

    Publication bias occurs when the published research results are systematically unrepresentative of the population of studies that have been conducted, and is a potential threat to meaningful meta-analysis. The Copas selection model provides a flexible framework for correcting estimates and offers considerable insight into the publication bias. However, maximizing the observed likelihood under the Copas selection model is challenging because the observed data contain very little information on the latent variable. In this article, we study a Copas-like selection model and propose an expectation-maximization (EM) algorithm for estimation based on the full likelihood. Empirical simulation studies show that the EM algorithm and its associated inferential procedure performs well and avoids the non-convergence problem when maximizing the observed likelihood. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. Measurement Error in Income and Schooling and the Bias of Linear Estimators

    DEFF Research Database (Denmark)

    Bingley, Paul; Martinello, Alessandro

    2017-01-01

    and Retirement in Europe data with Danish administrative registers. Contrary to most validation studies, we find that measurement error in income is classical once we account for imperfect validation data. We find nonclassical measurement error in schooling, causing a 38% amplification bias in IV estimators......We propose a general framework for determining the extent of measurement error bias in ordinary least squares and instrumental variable (IV) estimators of linear models while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing...

  4. Probabilistic causality, selection bias, and the logic of the democratic peace

    OpenAIRE

    Slantchev, Branislav L; Alexandrova, A; Gartzke, E

    2005-01-01

    Rosato (2003) claims to have discredited democratic peace theories. However, the methodological approach adopted by the study cannot reliably generate the conclusions espoused by the author. Rosato seems to misunderstand the probabilistic nature of most arguments about democratic peace and ignores issues that an appropriate research design should account for. Further, the study's use of case studies and data sets without attention to selection-bias produces examples that actually support theo...

  5. Biased agonism of the calcium-sensing receptor

    DEFF Research Database (Denmark)

    Thomsen, Alex Rojas Bie; Hvidtfeldt, Maja; Bräuner-Osborne, Hans

    2012-01-01

    After the discovery of molecules modulating G protein-coupled receptors (GPCRs) that are able to selectively affect one signaling pathway over others for a specific GPCR, thereby "biasing" the signaling, it has become obvious that the original model of GPCRs existing in either an "on" or "off...... through recruitment of ß-arrestins. Next, by measuring activity of all three signaling pathways we found that barium, spermine, neomycin, and tobramycin act as biased agonist in terms of efficacy and/or potency. Finally, polyamines and aminoglycosides in general were biased in their potencies toward ERK1...

  6. Measuring Teaching Quality in Higher Education : Assessing the Problem of Selection Bias in Course Evaluations

    OpenAIRE

    Salomons, Anna; Goos, Maarten

    2014-01-01

    Student evaluations of teaching are widely used to measure teaching quality and compare it across different courses, teachers, departments and institutions: as such, they are of increasing importance for teacher promotion decisions as well as student course selection. However, the response on course evaluations is rarely perfect, rendering such uses unwarranted if students who participate in the evaluation are not randomly selected: this paper is the first to investigate this issue. We quanti...

  7. Optogenetic stimulation in a computational model of the basal ganglia biases action selection and reward prediction error.

    Science.gov (United States)

    Berthet, Pierre; Lansner, Anders

    2014-01-01

    Optogenetic stimulation of specific types of medium spiny neurons (MSNs) in the striatum has been shown to bias the selection of mice in a two choices task. This shift is dependent on the localisation and on the intensity of the stimulation but also on the recent reward history. We have implemented a way to simulate this increased activity produced by the optical flash in our computational model of the basal ganglia (BG). This abstract model features the direct and indirect pathways commonly described in biology, and a reward prediction pathway (RP). The framework is similar to Actor-Critic methods and to the ventral/dorsal distinction in the striatum. We thus investigated the impact on the selection caused by an added stimulation in each of the three pathways. We were able to reproduce in our model the bias in action selection observed in mice. Our results also showed that biasing the reward prediction is sufficient to create a modification in the action selection. However, we had to increase the percentage of trials with stimulation relative to that in experiments in order to impact the selection. We found that increasing only the reward prediction had a different effect if the stimulation in RP was action dependent (only for a specific action) or not. We further looked at the evolution of the change in the weights depending on the stage of learning within a block. A bias in RP impacts the plasticity differently depending on that stage but also on the outcome. It remains to experimentally test how the dopaminergic neurons are affected by specific stimulations of neurons in the striatum and to relate data to predictions of our model.

  8. Mechanisms of attentional selection bias for threatening emotions of anger and disgust in individuals with high-trait anxiety.

    Science.gov (United States)

    Xia, Luyao; Cui, Lixia; Zhang, Qin; Dong, Xiaofei; Shi, Guangyuan

    2018-03-07

    There are still some controversies that attentional bias to negative emotions in individuals with high-trait anxiety (HTA), as compare with those with low-trait anxiety (LTA), occurs in the engagement or disengagement facet of attentional selectivity and whether this attentional bias is affected by negative emotional types. In this study, we explored the different attentional selectivity mechanisms for threatening emotions of anger and disgust between individuals with HTA and LTA using the variant attentional-probe paradigm. The results showed that under the engagement condition, the HTA group's attentional bias index of the anger mood was negative and was significantly less than the disgusting mood (positive) and that the P1 was smaller with angry faces as compared with neutral faces, which was separate from the results of the disgusted faces, having a significant difference with neutral faces on P1 component. In the LTA group, under the disengagement condition, the attentional bias index of the disgusting mood was significantly bigger than the attentional bias index of the anger mood. Moreover, the P1 of the disgusted faces was significantly bigger than the P1 of the angry faces. The topographical maps were also made to reveal the different neural underpinnings. The results suggested that there were different mechanisms of selective attentional bias for threatening emotions of anger and disgust in individuals with HTA. HTA individuals were characterized by facilitated attentional engagement with angry faces and impaired attentional engagement with disgusted faces. LTA individuals had different neural underpinnings and had impaired attentional disengagement with disgusted faces.

  9. Electrocortical measures of information processing biases in social anxiety disorder: A review.

    Science.gov (United States)

    Harrewijn, Anita; Schmidt, Louis A; Westenberg, P Michiel; Tang, Alva; van der Molen, Melle J W

    2017-10-01

    Social anxiety disorder (SAD) is characterized by information processing biases, however, their underlying neural mechanisms remain poorly understood. The goal of this review was to give a comprehensive overview of the most frequently studied EEG spectral and event-related potential (ERP) measures in social anxiety during rest, anticipation, stimulus processing, and recovery. A Web of Science search yielded 35 studies reporting on electrocortical measures in individuals with social anxiety or related constructs. Social anxiety was related to increased delta-beta cross-frequency correlation during anticipation and recovery, and information processing biases during early processing of faces (P1) and errors (error-related negativity). These electrocortical measures are discussed in relation to the persistent cycle of information processing biases maintaining SAD. Future research should further investigate the mechanisms of this persistent cycle and study the utility of electrocortical measures in early detection, prevention, treatment and endophenotype research. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Selection bias in species distribution models: An econometric approach on forest trees based on structural modeling

    Science.gov (United States)

    Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.

    2014-12-01

    Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents

  11. Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional prediction

    Directory of Open Access Journals (Sweden)

    Boulesteix Anne-Laure

    2009-12-01

    Full Text Available Abstract Background In biometric practice, researchers often apply a large number of different methods in a "trial-and-error" strategy to get as much as possible out of their data and, due to publication pressure or pressure from the consulting customer, present only the most favorable results. This strategy may induce a substantial optimistic bias in prediction error estimation, which is quantitatively assessed in the present manuscript. The focus of our work is on class prediction based on high-dimensional data (e.g. microarray data, since such analyses are particularly exposed to this kind of bias. Methods In our study we consider a total of 124 variants of classifiers (possibly including variable selection or tuning steps within a cross-validation evaluation scheme. The classifiers are applied to original and modified real microarray data sets, some of which are obtained by randomly permuting the class labels to mimic non-informative predictors while preserving their correlation structure. Results We assess the minimal misclassification rate over the different variants of classifiers in order to quantify the bias arising when the optimal classifier is selected a posteriori in a data-driven manner. The bias resulting from the parameter tuning (including gene selection parameters as a special case and the bias resulting from the choice of the classification method are examined both separately and jointly. Conclusions The median minimal error rate over the investigated classifiers was as low as 31% and 41% based on permuted uninformative predictors from studies on colon cancer and prostate cancer, respectively. We conclude that the strategy to present only the optimal result is not acceptable because it yields a substantial bias in error rate estimation, and suggest alternative approaches for properly reporting classification accuracy.

  12. Measurement error in income and schooling, and the bias of linear estimators

    DEFF Research Database (Denmark)

    Bingley, Paul; Martinello, Alessandro

    The characteristics of measurement error determine the bias of linear estimators. We propose a method for validating economic survey data allowing for measurement error in the validation source, and we apply this method by validating Survey of Health, Ageing and Retirement in Europe (SHARE) data...... with Danish administrative registers. We find that measurement error in surveys is classical for annual gross income but non-classical for years of schooling, causing a 21% amplification bias in IV estimators of returns to schooling. Using a 1958 Danish schooling reform, we contextualize our result...

  13. Anxiety-related biases in visual orienting and spatial motor response selection independently assessed by a probe-classification task

    NARCIS (Netherlands)

    Schrooten, M.G.S.; Smulders, F.T.Y.; Mogg, K.; Bradley, B.P.

    2012-01-01

    This dot-probe study assessed anxiety-related biases in visual attentional orienting and spatial motor response selection (motor attention) in high- and low-trait-anxious adults, and whether anxiety-related biases depend on response speed. Emotional-neutral word pairs appeared for 14 or 500 ms, with

  14. Model for an irreversible bias current in the superconducting qubit measurement process

    International Nuclear Information System (INIS)

    Hutchinson, G. D.; Williams, D. A.; Holmes, C. A.; Stace, T. M.; Spiller, T. P.; Barrett, S. D.; Milburn, G. J.; Hasko, D. G.

    2006-01-01

    The superconducting charge-phase ''quantronium'' qubit is considered in order to develop a model for the measurement process used in the experiment of Vion et al. [Science 296, 886 (2002)]. For this model we propose a method for including the bias current in the readout process in a fundamentally irreversible way, which to first order is approximated by the Josephson junction tilted-washboard potential phenomenology. The decohering bias current is introduced in the form of a Lindblad operator and the Wigner function for the current-biased readout Josephson junction is derived and analyzed. During the readout current pulse used in the quantronium experiment we find that the coherence of the qubit initially prepared in a symmetric superposition state is lost at a time of 0.2 ns after the bias current pulse has been applied, a time scale that is much shorter than the experimental readout time. Additionally we look at the effect of Johnson-Nyquist noise with zero mean from the current source during the qubit manipulation and show that the decoherence due to the irreversible bias current description is an order of magnitude smaller than that found through adding noise to the reversible tilted-washboard potential model. Our irreversible bias current model is also applicable to persistent-current-based qubits where the state is measured according to its flux via a small-inductance direct-current superconducting quantum interference device

  15. Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias.

    Directory of Open Access Journals (Sweden)

    Thomas Pfeiffer

    2011-03-01

    Full Text Available Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63% relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%. Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%. Such dynamic patterns in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust

  16. Uninformative polymorphisms bias genome scans for signatures of selection

    Directory of Open Access Journals (Sweden)

    Roesti Marius

    2012-06-01

    Full Text Available Abstract Background With the establishment of high-throughput sequencing technologies and new methods for rapid and extensive single nucleotide (SNP discovery, marker-based genome scans in search of signatures of divergent selection between populations occupying ecologically distinct environments are becoming increasingly popular. Methods and Results On the basis of genome-wide SNP marker data generated by RAD sequencing of lake and stream stickleback populations, we show that the outcome of such studies can be systematically biased if markers with a low minor allele frequency are included in the analysis. The reason is that these ‘uninformative’ polymorphisms lack the adequate potential to capture signatures of drift and hitchhiking, the focal processes in ecological genome scans. Bias associated with uninformative polymorphisms is not eliminated by just avoiding technical artifacts in the data (PCR and sequencing errors, as a high proportion of SNPs with a low minor allele frequency is a general biological feature of natural populations. Conclusions We suggest that uninformative markers should be excluded from genome scans based on empirical criteria derived from careful inspection of the data, and that these criteria should be reported explicitly. Together, this should increase the quality and comparability of genome scans, and hence promote our understanding of the processes driving genomic differentiation.

  17. Bias caused by water adsorption in hourly PM measurements

    Science.gov (United States)

    Kiss, Gyula; Imre, Kornélia; Molnár, Ágnes; Gelencsér, András

    2017-07-01

    Beta-attenuation monitors are used worldwide to monitor PM mass concentration with high temporal resolution. Hourly PM10 and PM2. 5 dry mass concentrations are publicly available with the tacit assumption that water is effectively removed prior to the measurement. However, as both the filter material of the monitor and the aerosol particles are capable of retaining a significant amount of water even at low relative humidities, the basic assumption may not be valid, resulting in significant bias in reported PM10 and PM2. 5 concentrations. Here we show that in PM10 measurement, particle-free air can produce apparent hourly average PM concentrations in the range of -13-+21 µg m-3 under conditions of fluctuating relative humidity. Positive and negative apparent readings are observed with increasing and decreasing relative humidities, respectively. Similar phenomena have been observed when the instrument filter was previously loaded with atmospheric aerosol. As a result the potential measurement biases in hourly readings arising from the interaction with water may be in the range of -53… + 69 %.

  18. Overview about bias in Customer Satisfaction Surveys and focus on self-selection error

    OpenAIRE

    Giovanna Nicolini; Luciana Dalla Valle

    2009-01-01

    The present paper provides an overview of the main types of surveys carried out for customer satisfaction analyses. In order to carry out these surveys it is possible to plan a census or select a sample. The higher the accuracy of the survey, the more reliable the results of the analysis. For this very reason, researchers pay special attention to surveys with bias due to non sampling errors, in particular to self-selection errors. These phenomena are very frequent especially in web surveys. S...

  19. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    Energy Technology Data Exchange (ETDEWEB)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)

    2012-01-10

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  20. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    International Nuclear Information System (INIS)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  1. Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

    Science.gov (United States)

    Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John

    2012-01-01

    Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

  2. Selection bias in dynamically measured supermassive black hole samples: scaling relations and correlations between residuals in semi-analytic galaxy formation models

    Science.gov (United States)

    Barausse, Enrico; Shankar, Francesco; Bernardi, Mariangela; Dubois, Yohan; Sheth, Ravi K.

    2017-07-01

    Recent work has confirmed that the scaling relations between the masses of supermassive black holes and host-galaxy properties such as stellar masses and velocity dispersions may be biased high. Much of this may be caused by the requirement that the black hole sphere of influence must be resolved for the black hole mass to be reliably estimated. We revisit this issue with a comprehensive galaxy evolution semi-analytic model. Once tuned to reproduce the (mean) correlation of black hole mass with velocity dispersion, the model cannot account for the correlation with stellar mass. This is independent of the model's parameters, thus suggesting an internal inconsistency in the data. The predicted distributions, especially at the low-mass end, are also much broader than observed. However, if selection effects are included, the model's predictions tend to align with the observations. We also demonstrate that the correlations between the residuals of the scaling relations are more effective than the relations themselves at constraining models for the feedback of active galactic nuclei (AGNs). In fact, we find that our model, while in apparent broad agreement with the scaling relations when accounting for selection biases, yields very weak correlations between their residuals at fixed stellar mass, in stark contrast with observations. This problem persists when changing the AGN feedback strength, and is also present in the hydrodynamic cosmological simulation Horizon-AGN, which includes state-of-the-art treatments of AGN feedback. This suggests that current AGN feedback models are too weak or simply not capturing the effect of the black hole on the stellar velocity dispersion.

  3. Measuring Teaching Quality in Higher Education : Assessing the Problem of Selection Bias in Course Evaluations

    NARCIS (Netherlands)

    Salomons, Anna; Goos, Maarten

    2014-01-01

    Student evaluations of teaching are widely used to measure teaching quality and compare it across different courses, teachers, departments and institutions: as such, they are of increasing importance for teacher promotion decisions as well as student course selection. However, the response on course

  4. Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions.

    Science.gov (United States)

    Verdam, Mathilde G E; Oort, Frans J

    2014-01-01

    Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data.A method for the investigation of measurement bias with Kronecker product restricted models.Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions.The use of curves to facilitate substantive interpretation of apparent measurement bias.Assessment of change in common factor means, after accounting for apparent measurement bias.Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks.

  5. Selectivity and stoichiometry boosting of beta-cyclodextrin in cationic/anionic surfactant systems: when host-guest equilibrium meets biased aggregation equilibrium.

    Science.gov (United States)

    Jiang, Lingxiang; Yu, Caifang; Deng, Manli; Jin, Changwen; Wang, Yilin; Yan, Yun; Huang, Jianbin

    2010-02-18

    Cationic surfactant/anionic surfactant/beta-CD ternary aqueous systems provide a platform for the coexistence of the host-guest (beta-CD/surfactant) equilibrium and the biased aggregation (monomeric/aggregated surfactants) equilibrium. We report here that the interplay between the two equilibria dominates the systems as follows. (1) The biased aggregation equilibrium imposes an apparent selectivity on the host-guest equilibrium, namely, beta-CD has to always selectively bind the major surfactant (molar fraction > 0.5) even if binding constants of beta-CD to the pair of surfactants are quite similar. (2) In return, the host-guest equilibrium amplifies the bias of the aggregation equilibrium, that is, the selective binding partly removes the major surfactant from the aggregates and leaves the aggregate composition approaching the electroneutral mixing stoichiometry. (3) This composition variation enhances electrostatic attractions between oppositely charged surfactant head groups, thus resulting in less-curved aggregates. In particular, the present apparent host-guest selectivity is of remarkably high values, and the selectivity stems from the bias of the aggregation equilibrium rather than the difference in binding constants. Moreover, beta-CD is defined as a "stoichiometry booster" for the whole class of cationic/anionic surfactant systems, which provides an additional degree of freedom to directly adjust aggregate compositions of the systems. The stoichiometry boosting of the compositions can in turn affect or even determine microstructures and macroproperties of the systems.

  6. The Difference-in-Difference Method: Assessing the Selection Bias in the Effects of Neighborhood Environment on Health

    Science.gov (United States)

    Grafova, Irina; Freedman, Vicki; Lurie, Nicole; Kumar, Rizie; Rogowski, Jeannette

    2013-01-01

    This paper uses the difference-in-difference estimation approach to explore the self-selection bias in estimating the effect of neighborhood economic environment on self-assessed health among older adults. The results indicate that there is evidence of downward bias in the conventional estimates of the effect of neighborhood economic disadvantage on self-reported health, representing a lower bound of the true effect. PMID:23623818

  7. Statistical study on the self-selection bias in FDG-PET cancer screening by a questionnaire survey

    International Nuclear Information System (INIS)

    Kita, Tamotsu; Yano, Fuzuki; Watanabe, Sadahiro; Soga, Shigeyoshi; Hama, Yukihiro; Shinmoto, Hiroshi; Kosuda, Shigeru

    2008-01-01

    A questionnaire survey was performed to investigate the possible presence of self-selection bias in 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) cancer screening (PET cancer screening). Responders to the questionnaires survey consisted of 80 healthy persons, who answered whether they undergo PET cancer screening, health consciousness, age, sex, and smoking history. The univariate and multivariate analyses on the four parameters were performed between the responders who were to undergo PET cancer screening and the responders who were not. Statistically significant difference was found in health consciousness between the above-mentioned two groups by both univariate and multivariate analysis with the odds ratio of 2.088. The study indicated that self-selection bias should exist in PET cancer screening. (author)

  8. Microcredit and domestic violence in Bangladesh: an exploration of selection bias influences.

    Science.gov (United States)

    Bajracharya, Ashish; Amin, Sajeda

    2013-10-01

    This article explores the relationship between women's participation in microcredit groups and domestic violence in Bangladesh. Several recent studies have raised concern about microcredit programs by reporting higher levels of violence among women who are members. These results, however, may be attributable to selection bias because members might differ from nonmembers in ways that make them more susceptible to violence to begin with. Using a sample of currently married women from the 2007 Bangladesh Demographic Health Survey (BDHS) (N = 4,195), we use propensity score matching (PSM) as a way of exploring selection bias in this relationship. Results suggest that the previously seen strong positive association between membership and violence does not hold when an appropriate comparison group, generated using PSM, is used in the analyses. Additional analyses also suggest that levels of violence do not differ significantly between members and nonmembers and instead could depend on context-specific factors related to poverty. Members for whom a match is not found report considerably higher levels of violence relative to nonmembers in the unmatched group. The background characteristics of members and nonmembers who do not match suggest that they are more likely to be younger and from relatively well-to-do households.

  9. Capturing Dynamics of Biased Attention: Are New Attention Variability Measures the Way Forward?

    Directory of Open Access Journals (Sweden)

    Anne-Wil Kruijt

    Full Text Available New indices, calculated on data from the widely used Dot Probe Task, were recently proposed to capture variability in biased attention allocation. We observed that it remains unclear which data pattern is meant to be indicative of dynamic bias and thus to be captured by these indices. Moreover, we hypothesized that the new indices are sensitive to SD differences at the response time (RT level in the absence of bias.Randomly generated datasets were analyzed to assess properties of the Attention Bias Variability (ABV and Trial Level Bias Score (TL-BS indices. Sensitivity to creating differences in 1 RT standard deviation, 2 mean RT, and 3 bias magnitude were assessed. In addition, two possible definitions of dynamic attention bias were explored by creating differences in 4 frequency of bias switching, and 5 bias magnitude in the presence of constant switching.ABV and TL-BS indices were found highly sensitive to increasing SD at the response time level, insensitive to increasing bias, linearly sensitive to increasing bias magnitude in the presence of bias switches, and non-linearly sensitive to increasing the frequency of bias switches. The ABV index was also found responsive to increasing mean response times in the absence of bias.Recently proposed DPT derived variability indices cannot uncouple measurement error from bias variability. Significant group differences may be observed even if there is no bias present in any individual dataset. This renders the new indices in their current form unfit for empirical purposes. Our discussion focuses on fostering debate and ideas for new research to validate the potentially very important notion of biased attention being dynamic.

  10. Evaluating anemometer drift: A statistical approach to correct biases in wind speed measurement

    Science.gov (United States)

    Azorin-Molina, Cesar; Asin, Jesus; McVicar, Tim R.; Minola, Lorenzo; Lopez-Moreno, Juan I.; Vicente-Serrano, Sergio M.; Chen, Deliang

    2018-05-01

    Recent studies on observed wind variability have revealed a decline (termed "stilling") of near-surface wind speed during the last 30-50 years over many mid-latitude terrestrial regions, particularly in the Northern Hemisphere. The well-known impact of cup anemometer drift (i.e., wear on the bearings) on the observed weakening of wind speed has been mentioned as a potential contributor to the declining trend. However, to date, no research has quantified its contribution to stilling based on measurements, which is most likely due to lack of quantification of the ageing effect. In this study, a 3-year field experiment (2014-2016) with 10-minute paired wind speed measurements from one new and one malfunctioned (i.e., old bearings) SEAC SV5 cup anemometer which has been used by the Spanish Meteorological Agency in automatic weather stations since mid-1980s, was developed for assessing for the first time the role of anemometer drift on wind speed measurement. The results showed a statistical significant impact of anemometer drift on wind speed measurements, with the old anemometer measuring lower wind speeds than the new one. Biases show a marked temporal pattern and clear dependency on wind speed, with both weak and strong winds causing significant biases. This pioneering quantification of biases has allowed us to define two regression models that correct up to 37% of the artificial bias in wind speed due to measurement with an old anemometer.

  11. A Test for Cluster Bias: Detecting Violations of Measurement Invariance across Clusters in Multilevel Data

    Science.gov (United States)

    Jak, Suzanne; Oort, Frans J.; Dolan, Conor V.

    2013-01-01

    We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings…

  12. Triangles in ROC space: History and theory of "nonparametric" measures of sensitivity and response bias.

    Science.gov (United States)

    Macmillan, N A; Creelman, C D

    1996-06-01

    Can accuracy and response bias in two-stimulus, two-response recognition or detection experiments be measured nonparametrically? Pollack and Norman (1964) answered this question affirmatively for sensitivity, Hodos (1970) for bias: Both proposed measures based on triangular areas in receiver-operating characteristic space. Their papers, and especially a paper by Grier (1971) that provided computing formulas for the measures, continue to be heavily cited in a wide range of content areas. In our sample of articles, most authors described triangle-based measures as making fewer assumptions than measures associated with detection theory. However, we show that statistics based on products or ratios of right triangle areas, including a recently proposed bias index and a not-yetproposed but apparently plausible sensitivity index, are consistent with a decision process based on logistic distributions. Even the Pollack and Norman measure, which is based on non-right triangles, is approximately logistic for low values of sensitivity. Simple geometric models for sensitivity and bias are not nonparametric, even if their implications are not acknowledged in the defining publications.

  13. Bias caused by water adsorption in hourly PM measurements

    Directory of Open Access Journals (Sweden)

    G. Kiss

    2017-07-01

    Full Text Available Beta-attenuation monitors are used worldwide to monitor PM mass concentration with high temporal resolution. Hourly PM10 and PM2. 5 dry mass concentrations are publicly available with the tacit assumption that water is effectively removed prior to the measurement. However, as both the filter material of the monitor and the aerosol particles are capable of retaining a significant amount of water even at low relative humidities, the basic assumption may not be valid, resulting in significant bias in reported PM10 and PM2. 5 concentrations. Here we show that in PM10 measurement, particle-free air can produce apparent hourly average PM concentrations in the range of −13–+21 µg m−3 under conditions of fluctuating relative humidity. Positive and negative apparent readings are observed with increasing and decreasing relative humidities, respectively. Similar phenomena have been observed when the instrument filter was previously loaded with atmospheric aerosol. As a result the potential measurement biases in hourly readings arising from the interaction with water may be in the range of −53… + 69 %.

  14. Investigation of bias in a study of nuclear shipyard workers

    International Nuclear Information System (INIS)

    Greenberg, E.R.; Rosner, B.; Hennekens, C.; Rinsky, R.; Colton, T.

    1985-01-01

    The authors examined discrepant findings between a 1978 proportional mortality study and a 1981 cohort study of workers at the Portsmouth, New Hampshire Naval Shipyard to determine whether the healthy worker effect, selection bias, or measurement bias could explain why only the proportional mortality study found excess cancer deaths among nuclear workers. Lower mortality from noncancer causes in nuclear workers (the healthy worker effect) partly accounted for the observed elevated cancer proportional mortality. More important, however, was measurement bias which occurred in the proportional mortality study when nuclear workers who had not died of cancer were misclassified as not being nuclear workers based on information from their next of kin, thereby, creating a spurious association. Although the proportional mortality study was based on a small sample of all deaths occuring in the cohort, selection bias did not contribute materially to the discrepant results for total cancer deaths. With regard to leukemia, misclassification of occupation in the proportional mortality study and disagreement about cause of death accounted for some of the reported excess deaths. 16 references, 4 tables

  15. Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions

    Science.gov (United States)

    Verdam, Mathilde G. E.; Oort, Frans J.

    2014-01-01

    Highlights Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data. A method for the investigation of measurement bias with Kronecker product restricted models. Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions. The use of curves to facilitate substantive interpretation of apparent measurement bias. Assessment of change in common factor means, after accounting for apparent measurement bias. Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks. PMID:25295016

  16. Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias

    International Nuclear Information System (INIS)

    Yoo, Seung-Hoon; Lim, Hea-Jin; Kwak, Seung-Jun

    2009-01-01

    Over the last twenty years, the consumption of natural gas in Korea has increased dramatically. This increase has mainly resulted from the rise of consumption in the residential sector. The main objective of the study is to estimate households' demand function for natural gas by applying a sample selection model using data from a survey of households in Seoul. The results show that there exists a selection bias in the sample and that failure to correct for sample selection bias distorts the mean estimate, of the demand for natural gas, downward by 48.1%. In addition, according to the estimation results, the size of the house, the dummy variable for dwelling in an apartment, the dummy variable for having a bed in an inner room, and the household's income all have positive relationships with the demand for natural gas. On the other hand, the size of the family and the price of gas negatively contribute to the demand for natural gas. (author)

  17. Birth order and sibship size: evaluation of the role of selection bias in a case-control study of non-Hodgkin's lymphoma.

    Science.gov (United States)

    Mensah, F K; Willett, E V; Simpson, J; Smith, A G; Roman, E

    2007-09-15

    Substantial heterogeneity has been observed among case-control studies investigating associations between non-Hodgkin's lymphoma and familial characteristics, such as birth order and sibship size. The potential role of selection bias in explaining such heterogeneity is considered within this study. Selection bias according to familial characteristics and socioeconomic status is investigated within a United Kingdom-based case-control study of non-Hodgkin's lymphoma diagnosed during 1998-2001. Reported distributions of birth order and maternal age are each compared with expected reference distributions derived using national birth statistics from the United Kingdom. A method is detailed in which yearly data are used to derive expected distributions, taking account of variability in birth statistics over time. Census data are used to reweight both the case and control study populations such that they are comparable with the general population with regard to socioeconomic status. The authors found little support for an association between non-Hodgkin's lymphoma and birth order or family size and little evidence for an influence of selection bias. However, the findings suggest that between-study heterogeneity could be explained by selection biases that influence the demographic characteristics of participants.

  18. How to investigate and adjust for selection bias in cohort studies

    DEFF Research Database (Denmark)

    Nohr, Ellen A; Liew, Zeyan

    2018-01-01

    National Birth Cohort (DNBC) as examples on how to quantify selection bias and also understand the underlying selection mechanisms. Although women who chose to participate in the cohort were typically of higher social status, healthier and with less disease than all those eligible for study, differential...... of the presented methods are applicable even with limited data on non-participants and those lost to follow-up, and can also be applied to other study designs such as case-control studies and surveys. This article is protected by copyright. All rights reserved.......Longitudinal cohort studies can provide important evidence about preventable causes of disease, but the success relies heavily on the commitment of their participants, both at recruitment and during follow-up. Initial participation rates have decreased in recent decades as have willingness...

  19. Methodologies for Measuring Judicial Performance: The Problem of Bias

    Directory of Open Access Journals (Sweden)

    Jennifer Elek

    2014-12-01

    Full Text Available Concerns about gender and racial bias in the survey-based evaluations of judicial performance common in the United States have persisted for decades. Consistent with a large body of basic research in the psychological sciences, recent studies confirm that the results from these JPE surveys are systematically biased against women and minority judges. In this paper, we explain the insidious manner in which performance evaluations may be biased, describe some techniques that may help to reduce expressions of bias in judicial performance evaluation surveys, and discuss the potential problem such biases may pose in other common methods of performance evaluation used in the United States and elsewhere. We conclude by highlighting the potential adverse consequences of judicial performance evaluation programs that rely on biased measurements. Durante décadas ha habido una preocupación por la discriminación por género y racial en las evaluaciones del rendimiento judicial basadas en encuestas, comunes en Estados Unidos. De acuerdo con un gran corpus de investigación básica en las ciencias psicológicas, estudios recientes confirman que los resultados de estas encuestas de evaluación del rendimiento judicial están sistemáticamente sesgados contra las mujeres y los jueces de minorías. En este artículo se explica la manera insidiosa en que las evaluaciones de rendimiento pueden estar sesgadas, se describen algunas técnicas que pueden ayudar a reducir las expresiones de sesgo en los estudios de evaluación del rendimiento judicial, y se debate el problema potencial que estos sesgos pueden plantear en otros métodos comunes de evaluación del rendimiento utilizados en Estados Unidos y otros países. Se concluye destacando las posibles consecuencias adversas de los programas de evaluación del rendimiento judicial que se basan en mediciones sesgadas. DOWNLOAD THIS PAPER FROM SSRN: http://ssrn.com/abstract=2533937

  20. Associations among Selective Attention, Memory Bias, Cognitive Errors and Symptoms of Anxiety in Youth

    Science.gov (United States)

    Watts, Sarah E.; Weems, Carl F.

    2006-01-01

    The purpose of this study was to examine the linkages among selective attention, memory bias, cognitive errors, and anxiety problems by testing a model of the interrelations among these cognitive variables and childhood anxiety disorder symptoms. A community sample of 81 youth (38 females and 43 males) aged 9-17 years and their parents completed…

  1. Accounting for selection bias in species distribution models: An econometric approach on forested trees based on structural modeling

    Science.gov (United States)

    Ay, Jean-Sauveur; Guillemot, Joannès; Martin-StPaul, Nicolas K.; Doyen, Luc; Leadley, Paul

    2015-04-01

    Species distribution models (SDMs) are widely used to study and predict the outcome of global change on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of application on forested trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8 km). We also compared the output of the SSDM with outputs of a classical SDM in term of bioclimatic response curves and potential distribution under current climate. According to the species and the spatial resolution of the calibration dataset, shapes of bioclimatic response curves the modelled species distribution maps differed markedly between the SSDM and classical SDMs. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents a crucial step to account for economic constraints on tree

  2. Occupational noise exposure and age correction: the problem of selection bias.

    Science.gov (United States)

    Dobie, Robert A

    2009-12-01

    Selection bias often invalidates conclusions about populations based on clinical convenience samples. A recent paper in this journal makes two surprising assertions about noise-induced permanent threshold shift (NIPTS): first, that there is more NIPTS at 2 kHz than at higher frequencies; second, that NIPTS declines with advancing age. Neither assertion can be supported with the data presented, which were obtained from a clinical sample; both are consistent with the hypothesis that people who choose to attend an audiology clinic have worse hearing, especially at 2 kHz, than people of the same age and gender who choose not to attend.

  3. Regional differences in the validity of self-reported use of health care in Belgium: selection versus reporting bias

    Directory of Open Access Journals (Sweden)

    J. Van der Heyden

    2016-08-01

    Full Text Available Abstract Background The Health Care Module of the European Health Interview Survey (EHIS is aimed to obtain comparable information on the use of inpatient and ambulatory care in all EU member states. In this study we assessed the validity of self-reported information on the use of health care, collected through this instrument, in the Belgian Health Interview Survey (BHIS, and explored the impact of selection and reporting bias on the validity of regional differences in health care use observed in the BHIS. Methods To assess reporting bias, self-reported BHIS 2008 data were linked with register-based data from the Belgian compulsory health insurance (BCHI. The latter were compared with similar estimates from a random sample of the BCHI to investigate the selection bias. Outcome indicators included the prevalence of a contact with a GP, specialist, dentist and a physiotherapist, as well as inpatient and day patient hospitalisation. The validity of the estimates and the regional differences were explored through measures of agreement and logistic regression analyses. Results Validity of self-reported health care use varies by type of health service and is more affected by reporting than by selection bias. Compared to health insurance estimates, self-reported results underestimate the percentage of people with a specialist contact in the past year (50.5 % versus 65.0 % and a day patient hospitalisation (7.8 % versus 13.9 %. Inversely, survey results overestimated the percentage of people having visited a dentist in the past year: 58.3 % versus 48.6 %. The best concordance was obtained for an inpatient hospitalisation (kappa 0.75. Survey data overestimate the higher prevalence of a contact with a specialist [OR 1.51 (95 % CI 1.33–1.72 for self-report and 1.08 (95 % CI 1.05–1.15 for register] and underestimate the lower prevalence of a contact with a GP [ORs 0.59 (95 % CI 0.51–0.70 and 0.41 (95 % CI 0.39–0.42 respectively] in

  4. Measuring Nonresponse Bias in a Cross-Country Enterprise Survey

    Directory of Open Access Journals (Sweden)

    Katarzyna Bańkowska

    2015-04-01

    Full Text Available Nonresponse is a common issue affecting the vast majority of surveys. Efforts to convince those unwilling to participate in a survey might not necessary result in a better picture of the target population and can lead to higher, not lower, nonresponse bias.We investigate the impact of non-response in the European Commission & European Central Bank Survey on the Access to Finance of Enterprises (SAFE, which collects evidence on the financing conditions faced by European SMEs compared with those of large firms. This survey, conducted by telephone bi-annually since 2009 by the ECB and the European Commission, provides a valuable means to search for this kind of bias, given the high heterogeneity of response propensities across countries.The study relies on so-called “Representativity Indicators” developed within the Representativity Indicators of Survey Quality (RISQ project, which measure the distance to a fully representative response. On this basis, we examine the quality of the SAFE Survey at different stages of the fieldwork as well as across different survey waves and countries. The RISQ methodology relies on rich sampling frame information, which is however partly limited in the case of the SAFE. We also assess the representativeness of the SAFE particular subsample created by linking the survey responses with the companies’ financial information from a business register; this sub-sampling is another potential source of bias which we also attempt to quantify. Finally, we suggest possible ways how to improve monitoring of the possible nonresponse bias in the future rounds of the survey.

  5. Bias of shear wave elasticity measurements in thin layer samples and a simple correction strategy.

    Science.gov (United States)

    Mo, Jianqiang; Xu, Hao; Qiang, Bo; Giambini, Hugo; Kinnick, Randall; An, Kai-Nan; Chen, Shigao; Luo, Zongping

    2016-01-01

    Shear wave elastography (SWE) is an emerging technique for measuring biological tissue stiffness. However, the application of SWE in thin layer tissues is limited by bias due to the influence of geometry on measured shear wave speed. In this study, we investigated the bias of Young's modulus measured by SWE in thin layer gelatin-agar phantoms, and compared the result with finite element method and Lamb wave model simulation. The result indicated that the Young's modulus measured by SWE decreased continuously when the sample thickness decreased, and this effect was more significant for smaller thickness. We proposed a new empirical formula which can conveniently correct the bias without the need of using complicated mathematical modeling. In summary, we confirmed the nonlinear relation between thickness and Young's modulus measured by SWE in thin layer samples, and offered a simple and practical correction strategy which is convenient for clinicians to use.

  6. Preanalytical Biases in the Measurement of Human Blood Sphingolipids

    Directory of Open Access Journals (Sweden)

    Robert Brunkhorst

    2018-05-01

    Full Text Available Dysregulation of blood sphingolipids is an emerging topic in clinical science. The objective of this study was to determine preanalytical biases that typically occur in clinical and translational studies and that influence measured blood sphingolipid levels. Therefore, we collected blood samples from four healthy male volunteers to investigate the effect of storage conditions (time, temperature, long-term storage, freeze–thaw cycles, blood drawing (venous or arterial sampling, prolonged venous compression, and sample preparation (centrifugation, freezing on sphingolipid levels measured by LC-MS/MS. Our data show that sphingosine 1-phosphate (S1P and sphinganine 1-phosphate (SA1P were upregulated in whole blood samples in a time- and temperature-dependent manner. Increased centrifugation at higher speeds led to lower amounts of S1P and SA1P. All other preanalytical biases did not significantly alter the amounts of S1P and SA1P. Further, in almost all settings, we did not detect differences in (dihydroceramide levels. In summary, besides time-, temperature-, and centrifugation-dependent changes in S1P and SA1P levels, sphingolipids in blood remained stable under practically relevant preanalytical conditions.

  7. Approach-Induced Biases in Human Information Sampling.

    Directory of Open Access Journals (Sweden)

    Laurence T Hunt

    2016-11-01

    Full Text Available Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled ("positive evidence approach", the selection of which information to sample ("sampling the favorite", and the interaction between information sampling and subsequent choices ("rejecting unsampled options". The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.

  8. Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

    Science.gov (United States)

    Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

    2018-04-15

    For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

  9. The self-attribution bias and paranormal beliefs.

    Science.gov (United States)

    van Elk, Michiel

    2017-03-01

    The present study investigated the relation between paranormal beliefs, illusory control and the self-attribution bias, i.e., the motivated tendency to attribute positive outcomes to oneself while negative outcomes are externalized. Visitors of a psychic fair played a card guessing game and indicated their perceived control over randomly selected cards as a function of the congruency and valence of the card. A stronger self-attribution bias was observed for paranormal believers compared to skeptics and this bias was specifically related to traditional religious beliefs and belief in superstition. No relation between paranormal beliefs and illusory control was found. Self-report measures indicated that paranormal beliefs were associated to being raised in a spiritual family and to anomalous experiences during childhood. Thereby this study suggests that paranormal beliefs are related to specific cognitive biases that in turn are shaped by socio-cultural factors. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Mechanism for and method of biasing magnetic sensor

    Science.gov (United States)

    Kautz, David R.

    2007-12-04

    A magnetic sensor package having a biasing mechanism involving a coil-generated, resistor-controlled magnetic field for providing a desired biasing effect. In a preferred illustrated embodiment, the package broadly comprises a substrate; a magnetic sensor element; a biasing mechanism, including a coil and a first resistance element; an amplification mechanism; a filter capacitor element; and an encapsulant. The sensor is positioned within the coil. A current applied to the coil produces a biasing magnetic field. The biasing magnetic field is controlled by selecting a resistance value for the first resistance element which achieves the desired biasing effect. The first resistance element preferably includes a plurality of selectable resistors, the selection of one or more of which sets the resistance value.

  11. OBJECTS IN KEPLER'S MIRROR MAY BE LARGER THAN THEY APPEAR: BIAS AND SELECTION EFFECTS IN TRANSITING PLANET SURVEYS

    International Nuclear Information System (INIS)

    Gaidos, Eric; Mann, Andrew W.

    2013-01-01

    Statistical analyses of large surveys for transiting planets such as the Kepler mission must account for systematic errors and biases. Transit detection depends not only on the planet's radius and orbital period, but also on host star properties. Thus, a sample of stars with transiting planets may not accurately represent the target population. Moreover, targets are selected using criteria such as a limiting apparent magnitude. These selection effects, combined with uncertainties in stellar radius, lead to biases in the properties of transiting planets and their host stars. We quantify possible biases in the Kepler survey. First, Eddington bias produced by a steep planet radius distribution and uncertainties in stellar radius results in a 15%-20% overestimate of planet occurrence. Second, the magnitude limit of the Kepler target catalog induces Malmquist bias toward large, more luminous stars and underestimation of the radii of about one-third of candidate planets, especially those larger than Neptune. Third, because metal-poor stars are smaller, stars with detected planets will be very slightly (<0.02 dex) more metal-poor than the target average. Fourth, uncertainties in stellar radii produce correlated errors in planet radius and stellar irradiation. A previous finding, that highly irradiated giants are more likely to have 'inflated' radii, remains significant, even accounting for this effect. In contrast, transit depth is negatively correlated with stellar metallicity even in the absence of any intrinsic correlation, and a previous claim of a negative correlation between giant planet transit depth and stellar metallicity is probably an artifact.

  12. Lessons learnt on biases and uncertainties in personal exposure measurement surveys of radiofrequency electromagnetic fields with exposimeters.

    Science.gov (United States)

    Bolte, John F B

    2016-09-01

    Personal exposure measurements of radio frequency electromagnetic fields are important for epidemiological studies and developing prediction models. Minimizing biases and uncertainties and handling spatial and temporal variability are important aspects of these measurements. This paper reviews the lessons learnt from testing the different types of exposimeters and from personal exposure measurement surveys performed between 2005 and 2015. Applying them will improve the comparability and ranking of exposure levels for different microenvironments, activities or (groups of) people, such that epidemiological studies are better capable of finding potential weak correlations with health effects. Over 20 papers have been published on how to prevent biases and minimize uncertainties due to: mechanical errors; design of hardware and software filters; anisotropy; and influence of the body. A number of biases can be corrected for by determining multiplicative correction factors. In addition a good protocol on how to wear the exposimeter, a sufficiently small sampling interval and sufficiently long measurement duration will minimize biases. Corrections to biases are possible for: non-detects through detection limit, erroneous manufacturer calibration and temporal drift. Corrections not deemed necessary, because no significant biases have been observed, are: linearity in response and resolution. Corrections difficult to perform after measurements are for: modulation/duty cycle sensitivity; out of band response aka cross talk; temperature and humidity sensitivity. Corrections not possible to perform after measurements are for: multiple signals detection in one band; flatness of response within a frequency band; anisotropy to waves of different elevation angle. An analysis of 20 microenvironmental surveys showed that early studies using exposimeters with logarithmic detectors, overestimated exposure to signals with bursts, such as in uplink signals from mobile phones and Wi

  13. Investigations of a voltage-biased microwave cavity for quantum measurements of nanomechanical resonators

    Science.gov (United States)

    Rouxinol, Francisco; Hao, Hugo; Lahaye, Matt

    2015-03-01

    Quantum electromechanical systems incorporating superconducting qubits have received extensive interest in recent years due to their promising prospects for studying fundamental topics of quantum mechanics such as quantum measurement, entanglement and decoherence in new macroscopic limits, also for their potential as elements in technological applications in quantum information network and weak force detector, to name a few. In this presentation we will discuss ours efforts toward to devise an electromechanical circuit to strongly couple a nanomechanical resonator to a superconductor qubit, where a high voltage dc-bias is required, to study quantum behavior of a mechanical resonator. Preliminary results of our latest generation of devices integrating a superconductor qubit into a high-Q voltage biased microwave cavities are presented. Developments in the circuit design to couple a mechanical resonator to a qubit in the high-Q voltage bias CPW cavity is discussed as well prospects of achieving single-phonon measurement resolution. National Science Foundation under Grant No. DMR-1056423 and Grant No. DMR-1312421.

  14. A Systematic Review of Attention Biases in Opioid, Cannabis, Stimulant Use Disorders.

    Science.gov (United States)

    Zhang, Melvyn; Ying, Jiangbo; Wing, Tracey; Song, Guo; Fung, Daniel S S; Smith, Helen

    2018-06-01

    Background : Opiates, cannabis, and amphetamines are highly abused, and use of these substances are prevalent disorders. Psychological interventions are crucial given that they help individuals maintain abstinence following a lapse or relapse into substance use. Advances in experimental psychology have suggested that automatic attention biases might be responsible for relapse. Prior reviews have provided evidence for the presence of these biases in addictive disorders and the effectiveness of bias modification. However, the prior studies are limited, as they failed to include trials involving participants with these prevalent addictive disorders or have failed to adopt a systematic approach in evidence synthesis. Objectives : The primary aim of this current systematic review is to synthesise the current evidence for attention biases amongst opioid use, cannabis use, and stimulant use disorders. The secondary aim is to determine the efficacy of attention bias modification interventions and other addictions related outcomes. Methods : A search was conducted from November 2017 to January 2018 on PubMed, MEDLINE, Embase, PsycINFO, Science Direct, Cochrane Central, and Scopus. The selection process of the articles was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A qualitative synthesis was undertaken. Risk of bias was assessed using the Cochrane Risk of Bias tool. Results : Six randomised trials were identified. The evidence synthesized from these trials have provided strong evidence that attentional biases are present in opioid and stimulant use disorders. Evidence synthesis for other secondary outcome measures could not be performed given the heterogeneity in the measures reported and the limited number of trials. The risk of bias assessment for the included trials revealed a high risk of selection and attrition bias. Conclusions : This review demonstrates the potential need for interventions targeting attention

  15. Expectancy bias in a selective conditioning procedure: trait anxiety increases the threat value of a blocked stimulus.

    Science.gov (United States)

    Boddez, Yannick; Vervliet, Bram; Baeyens, Frank; Lauwers, Stephanie; Hermans, Dirk; Beckers, Tom

    2012-06-01

    In a blocking procedure, a single conditioned stimulus (CS) is paired with an unconditioned stimulus (US), such as electric shock, in the first stage. During the subsequent stage, the CS is presented together with a second CS and this compound is followed by the same US. Fear conditioning studies in non-human animals have demonstrated that fear responding to the added second CS typically remains low, despite its being paired with the US. Accordingly, the blocking procedure is well suited as a laboratory model for studying (deficits in) selective threat appraisal. The present study tested the relation between trait anxiety and blocking in human aversive conditioning. Healthy participants filled in a trait anxiety questionnaire and underwent blocking treatment in the human aversive conditioning paradigm. Threat appraisal was measured through shock expectancy ratings and skin conductance. As hypothesized, trait anxiety was positively associated with shock expectancy ratings to the blocked stimulus. In skin conductance responding, no significant effects of stimulus type could be detected during blocking training or testing. The current study does not allow strong claims to be made regarding the theoretical process underlying the expectancy bias we observed. The observed shock expectancy bias might be one of the mechanisms leading to non-specific fear in individuals at risk for developing anxiety disorders. A deficit in blocking, or a deficit in selective threat appraisal at the more general level, indeed results in fear becoming non-specific and disconnected from the most likely causes or predictors of danger. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Facial expression movement enhances the measurement of temporal dynamics of attentional bias in the dot-probe task.

    Science.gov (United States)

    Caudek, Corrado; Ceccarini, Francesco; Sica, Claudio

    2017-08-01

    The facial dot-probe task is one of the most common experimental paradigms used to assess attentional bias toward emotional information. In recent years, however, the psychometric properties of this paradigm have been questioned. In the present study, attentional bias to emotional face stimuli was measured with dynamic and static images of realistic human faces in 97 college students (63 women) who underwent either a positive or a negative mood-induction prior to the experiment. We controlled the bottom-up salience of the stimuli in order to dissociate the top-down orienting of attention from the effects of the bottom-up physical properties of the stimuli. A Bayesian analysis of our results indicates that 1) the traditional global attentional bias index shows a low reliability, 2) reliability increases dramatically when biased attention is analyzed by extracting a series of bias estimations from trial-to-trial (Zvielli, Bernstein, & Koster, 2015), 3) dynamic expression of emotions strengthens biased attention to emotional information, and 4) mood-congruency facilitates the measurement of biased attention to emotional stimuli. These results highlight the importance of using ecologically valid stimuli in attentional bias research, together with the importance of estimating biased attention at the trial level. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Peak Measurement for Vancomycin AUC Estimation in Obese Adults Improves Precision and Lowers Bias.

    Science.gov (United States)

    Pai, Manjunath P; Hong, Joseph; Krop, Lynne

    2017-04-01

    Vancomycin area under the curve (AUC) estimates may be skewed in obese adults due to weight-dependent pharmacokinetic parameters. We demonstrate that peak and trough measurements reduce bias and improve the precision of vancomycin AUC estimates in obese adults ( n = 75) and validate this in an independent cohort ( n = 31). The precision and mean percent bias of Bayesian vancomycin AUC estimates are comparable between covariate-dependent ( R 2 = 0.774, 3.55%) and covariate-independent ( R 2 = 0.804, 3.28%) models when peaks and troughs are measured but not when measurements are restricted to troughs only ( R 2 = 0.557, 15.5%). Copyright © 2017 American Society for Microbiology.

  18. Selection bias, vote counting, and money-priming effects: A comment on Rohrer, Pashler, and Harris (2015) and Vohs (2015).

    Science.gov (United States)

    Vadillo, Miguel A; Hardwicke, Tom E; Shanks, David R

    2016-05-01

    When a series of studies fails to replicate a well-documented effect, researchers might be tempted to use a "vote counting" approach to decide whether the effect is reliable-that is, simply comparing the number of successful and unsuccessful replications. Vohs's (2015) response to the absence of money priming effects reported by Rohrer, Pashler, and Harris (2015) provides an example of this approach. Unfortunately, vote counting is a poor strategy to assess the reliability of psychological findings because it neglects the impact of selection bias and questionable research practices. In the present comment, we show that a range of meta-analytic tools indicate irregularities in the money priming literature discussed by Rohrer et al. and Vohs, which all point to the conclusion that these effects are distorted by selection bias, reporting biases, or p-hacking. This could help to explain why money-priming effects have proven unreliable in a number of direct replication attempts in which biases have been minimized through preregistration or transparent reporting. Our major conclusion is that the simple proportion of significant findings is a poor guide to the reliability of research and that preregistered replications are an essential means to assess the reliability of money-priming effects. (c) 2016 APA, all rights reserved).

  19. Simulation free measurement of the B+ → $\\bar{D}$0π+ lifetime using decays selected using displaced tracks

    Energy Technology Data Exchange (ETDEWEB)

    Malde, Sneha [St. Anne' s College, Oxford (United Kingdom)

    2008-01-01

    The lifetime of the B± meson is measured using the decay channel B+ → $\\bar{D}$0π+. The measurement is made using approximately 1.0 fb-1 of Tevatron proton-anti-proton collision data at √s = 1.96 TeV collected by the CDF detector. The data were collected using impact parameter based triggers that were designed to select events with a secondary vertex. The trigger selection criteria result in data rich in a variety of B hadron decays, but intrinsically bias the lifetime distribution of the collected signal events. The traditional way to compensate for the bias is to use information from simulation. Presented here is a new method for correction of the lifetime bias using an analytical technique that uses information from the data only. This eliminates measurement uncertainty due to data and simulation agreement, ultimately resulting in a smaller systematic measurement uncertainty. The B± lifetime measurement is the first measurement using this new technique and demonstrates its potential for use in future measurements. The B± lifetime is measured to be τ(B±) = 1.662 ± 0.023(stat) ± 0.015(syst)ps.

  20. Sex Attracts: Investigating Individual Differences in Attentional Bias to Sexual Stimuli

    Science.gov (United States)

    Kagerer, Sabine; Wehrum, Sina; Klucken, Tim; Walter, Bertram; Vaitl, Dieter; Stark, Rudolf

    2014-01-01

    We investigated the impact of sexual stimuli and the influence of sexual motivation on the performance in a dot-probe task and a line-orientation task in a large sample of males and females. All pictures (neutral, erotic) were rated on the dimensions of valence, arousal, disgust, and sexual arousal. Additionally, questionnaires measuring sexual interest/desire/motivation were employed. The ratings of the sexual stimuli point to a successful picture selection because sexual arousal did not differ between the sexes. The stimuli were equally arousing for men and women. Higher scores in the employed questionnaires measuring sexual interest/desire/motivation led to higher sexual arousal ratings of the sex pictures. Attentional bias towards sex pictures was observed in both experimental tasks. The attentional biases measured by the dot-probe and the line-orientation task were moderately intercorrelated suggesting attentional bias as a possible marker for a sex-attention trait. Finally, only the sexual sensation seeking score correlated with the attentional biases of the two tasks. Future research is needed to increase the predictive power of these indirect measures of sexual interest. PMID:25238545

  1. Performance of bias-correction methods for exposure measurement error using repeated measurements with and without missing data.

    Science.gov (United States)

    Batistatou, Evridiki; McNamee, Roseanne

    2012-12-10

    It is known that measurement error leads to bias in assessing exposure effects, which can however, be corrected if independent replicates are available. For expensive replicates, two-stage (2S) studies that produce data 'missing by design', may be preferred over a single-stage (1S) study, because in the second stage, measurement of replicates is restricted to a sample of first-stage subjects. Motivated by an occupational study on the acute effect of carbon black exposure on respiratory morbidity, we compare the performance of several bias-correction methods for both designs in a simulation study: an instrumental variable method (EVROS IV) based on grouping strategies, which had been recommended especially when measurement error is large, the regression calibration and the simulation extrapolation methods. For the 2S design, either the problem of 'missing' data was ignored or the 'missing' data were imputed using multiple imputations. Both in 1S and 2S designs, in the case of small or moderate measurement error, regression calibration was shown to be the preferred approach in terms of root mean square error. For 2S designs, regression calibration as implemented by Stata software is not recommended in contrast to our implementation of this method; the 'problematic' implementation of regression calibration although substantially improved with use of multiple imputations. The EVROS IV method, under a good/fairly good grouping, outperforms the regression calibration approach in both design scenarios when exposure mismeasurement is severe. Both in 1S and 2S designs with moderate or large measurement error, simulation extrapolation severely failed to correct for bias. Copyright © 2012 John Wiley & Sons, Ltd.

  2. Functional conservation of nucleosome formation selectively biases presumably neutral molecular variation in yeast genomes.

    Science.gov (United States)

    Babbitt, Gregory A; Cotter, C R

    2011-01-01

    One prominent pattern of mutational frequency, long appreciated in comparative genomics, is the bias of purine/pyrimidine conserving substitutions (transitions) over purine/pyrimidine altering substitutions (transversions). Traditionally, this transitional bias has been thought to be driven by the underlying rates of DNA mutation and/or repair. However, recent sequencing studies of mutation accumulation lines in model organisms demonstrate that substitutions generally do not accumulate at rates that would indicate a transitional bias. These observations have called into question a very basic assumption of molecular evolution; that naturally occurring patterns of molecular variation in noncoding regions accurately reflect the underlying processes of randomly accumulating neutral mutation in nuclear genomes. Here, in Saccharomyces yeasts, we report a very strong inverse association (r = -0.951, P < 0.004) between the genome-wide frequency of substitutions and their average energetic effect on nucleosome formation, as predicted by a structurally based energy model of DNA deformation around the nucleosome core. We find that transitions occurring at sites positioned nearest the nucleosome surface, which are believed to function most importantly in nucleosome formation, alter the deformation energy of DNA to the nucleosome core by only a fraction of the energy changes typical of most transversions. When we examined the same substitutions set against random background sequences as well as an existing study reporting substitutions arising in mutation accumulation lines of Saccharomyces cerevisiae, we failed to find a similar relationship. These results support the idea that natural selection acting to functionally conserve chromatin organization may contribute significantly to genome-wide transitional bias, even in noncoding regions. Because nucleosome core structure is highly conserved across eukaryotes, our observations may also help to further explain locally elevated

  3. Bias in calculated keff from subcritical measurements by the 252Cf-source-driven noise analysis method

    International Nuclear Information System (INIS)

    Mihalczo, J.T.; Valentine, T.E.

    1995-01-01

    The development of MCNP-DSP, which allows direct calculation of the measured time and frequency analysis parameters from subcritical measurements using the 252 Cf-source-driven noise analysis method, permits the validation of calculational methods for criticality safety with in-plant subcritical measurements. In addition, a method of obtaining the bias in the calculations, which is essential to the criticality safety specialist, is illustrated using the results of measurements with 17.771-cm-diam, enriched (93.15), unreflected, and unmoderated uranium metal cylinders. For these uranium metal cylinders the bias obtained using MCNP-DSP and ENDF/B-V cross-section data increased with subcriticality. For a critical experiment [height (h) = 12.629 cm], it was -0.0061 ± 0.0003. For a 10.16-cm-high cylinder (k ∼ 0.93), it was 0.0060 ± 0.0016, and for a subcritical cylinder (h = 8.13 cm, k ∼ 0.85), the bias was -0.0137 ± 0.0037, more than a factor of 2 larger in magnitude. This method allows the nuclear criticality safety specialist to establish the bias in calculational methods for criticality safety from in-plant subcritical measurements by the 252 Cf-source-driven noise analysis method

  4. Why and how FDI stocks are a biased measure of MNE affiliate activity

    NARCIS (Netherlands)

    Beugelsdijk, S.; Hennart, J.-F.; Slangen, A.; Smeets, R.

    2010-01-01

    Many international business (IB) studies have used foreign direct investment (FDI) stocks to measure the aggregate value-adding activity of multinational enterprises (MNE) affiliates in host countries. We argue that FDI stocks are a biased measure of that activity, because the degree to which they

  5. Why and how FDI stocks are a biased measure of MNE affiliate activity

    NARCIS (Netherlands)

    Beugelsdijk, Sjoerd; Hennart, Jean-Francois; Slangen, Arjen; Smeets, Roger

    2010-01-01

    Many international business (IB) studies have used foreign direct investment (FDI) stocks to measure the aggregate value adding activity of multinational enterprises (MNE) affiliates in host countries We argue that FDI stocks are a biased measure of that activity, because the degree to which they

  6. Intrinsic measurement bias on computed tomography scout view is unpredictable: computed tomography pelvimetry using a phantom

    International Nuclear Information System (INIS)

    Anderson, N.G.; Fenwick, J.L.; Wells, J.E.

    2006-01-01

    Our aim was to determine the degree of bias in CT scanogram measurements. We obtained standard lateral and anteroposterior (AP) pelvimetry scanograms of a phantom pelvis after placing ball bearings or aluminium rods to mark bony landmarks. Computed tomography pelvimetry was carried out at the manufacturer-recommended table height on two commercial CT scanners and at 10-mm increments up to 50 mm above and below this height. The AP inlet, AP outlet, interspinous distance and transverse diameters were each measured three times for each scanogram. The true measurements were obtained directly from the disassembled phantom. Bias was defined as the difference between the CT measurement and the true measurement. Observer error was negligible. The transverse diameter was overestimated at high table positions and underestimated at low table positions on both scanners (+6 to -10 mm). After correcting for geometric distortion, up to 6 mm bias was still present. The point at which no bias occurred was different for each scanner and did not correspond to the manufacturers' recommended table height. The outlet was overestimated on both scanners by up to 5 mm. The true inlet measurement was overestimated by 1.2 mm. The interspinous distance was minimally underestimated on both scanners. The measurements on CT scanogram were underestimated or overestimated in an inconsistent and unpredictable fashion, varying from one type of measurement to another and from CT scanner to CT scanner. This has implications for the accuracy and clinical utility of measurements obtained from a CT scanogram. Copyright (2006) Blackwell Science Pty Ltd

  7. Constraining omega and bias from the Stromlo-APM survey

    International Nuclear Information System (INIS)

    Loveday, J.

    1995-05-01

    Galaxy redshift surveys provide a distorted picture of the universe due to the non-Hubble component of galaxy motions. By measuring such distortions in the linear regime one can constrain the quantity β = Ω 0.6 where Ω is the cosmological density parameter and b is the (linear) bias factor for optically-selected galaxies. In this paper we estimate β from the Stromlo-APM redshift survey by comparing the amplitude of the direction-averaged redshift space correlation function to the real space correlation function. We find a 95% confidence upper limit of β = 0.75, with a 'best estimate' of β ∼ 0.48. A bias parameter b ∼ 2 is thus required if Ω ≡ 1. However, higher-order correlations measured from the APM galaxy survey indicate a low value for the bias parameter b ∼ 1, requiring that Q approx-lt 0.6

  8. Is it feasible to estimate radiosonde biases from interlaced measurements?

    Science.gov (United States)

    Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.

    2018-05-01

    Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the

  9. Selection Bias in Students' Evaluation of Teaching: Causes of Student Absenteeism and Its Consequences for Course Ratings and Rankings

    Science.gov (United States)

    Wolbring, Tobias; Treischl, Edgar

    2016-01-01

    Systematic sampling error due to self-selection is a common topic in methodological research and a key challenge for every empirical study. Since selection bias is often not sufficiently considered as a potential flaw in research on and evaluations in higher education, the aim of this paper is to raise awareness for the topic using the case of…

  10. Redox Bias in Loss on Ignition Moisture Measurement for Relatively Pure Plutonium-Bearing Oxide Materials

    International Nuclear Information System (INIS)

    Eller, P. G.; Stakebake, J. L.; Cooper, T. D.

    2002-01-01

    This paper evaluates potential analytical bias in application of the Loss on Ignition (LOI) technique for moisture measurement to relatively pure (plutonium assay of 80 wt.% or higher) oxides containing uranium that have been stabilized according to stabilization and storage standard DOE-STD-3013-2000 (STD- 3013). An immediate application is to Rocky Flats (RF) materials derived from high-grade metal hydriding separations subsequently treated by multiple calcination cycles. Specifically evaluated are weight changes due to oxidation/reduction of multivalent impurity oxides that could mask true moisture equivalent content measurement. Process knowledge and characterization of materials representing complex-wide materials to be stabilized and packaged according to STD-3013, and particularly for the immediate RF target stream, indicate that oxides of uranium, iron and gallium are the only potential multivalent constituents expected to be present above 0.5 wt.%. The evaluation show s that of these constituents, with few exceptions, only uranium oxides can be present at a sufficient level to produce weight gain biases significant with respect to the LOI stability test. In general, these formerly high-value, high-actinide content materials are reliably identifiable by process knowledge and measurement. Significant bias also requires that UO2 components remain largely unoxidized after calcination and are largely converted to U3O8 during LOI testing at only slightly higher temperatures. Based on well-established literature, it is judged unlikely that this set of conditions will be realized in practice. We conclude that it is very likely that LOI weight gain bias will be small for the immediate target RF oxide materials containing greater than 80 wt.% plutonium plus a much smaller uranium content. Recommended tests are in progress to confirm these expectations and to provide a more authoritative basis for bounding LOI oxidation/reduction biases. LOI bias evaluation is more

  11. Selection bias in genetic-epidemiological studies of cleft lip and palate

    Energy Technology Data Exchange (ETDEWEB)

    Christensen, K.; Holm, N.V.; Kock, K. (Odense Univ. (Denmark)); Olsen, J. (Aarhus Univ. (Denmark)); Fogh-Anderson, P.

    1992-09-01

    The possible impact of selection bias in genetic and epidemiological studies of cleft lip and palate was studied, using three nationwide ascertainment sources and an autopsy study in a 10% sample of the Danish population. A total of 670 cases were identified. Two national record systems, when used together, were found suitable for ascertaining facial cleft in live births. More than 95% ascertainment was obtained by means of surgical files for cleft lip (with or without cleft palate) without associated malformations/syndromes. However, surgical files could be a poor source for studying isolated cleft palate (CP) (only a 60% and biased ascertainment), and they cannot be used to study the prevalence of associated malformations or syndromes in facial cleft cases. The male:female ratio was 0.88 in surgically treated cases of CP and was 1.5 in nonoperated CP cases, making the overall sex ratio for CP 1.1 (95% confidence limits 0.86-1.4) The sex ratio for CP without associated malformation was 1.1 (95% confidence limits 0.84-1.6). One of the major test criteria in CP multifactorial threshold models (higher CP liability among male CP relatives) must be reconsidered, if other investigations confirm that a CP sex-ratio reversal to male predominance occurs when high ascertainment is achieved. 24 refs., 1 fig., 4 tabs.

  12. Regression dilution bias: tools for correction methods and sample size calculation.

    Science.gov (United States)

    Berglund, Lars

    2012-08-01

    Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. In this article we give a non-technical description of designs of reliability studies with emphasis on selection of individuals for a repeated measurement, assumptions of measurement error models, and correction methods for the slope in a simple linear regression model where the dependent variable is a continuous variable. Also, we describe situations where correction for regression dilution bias is not appropriate. The methods are illustrated with the association between insulin sensitivity measured with the euglycaemic insulin clamp technique and fasting insulin, where measurement of the latter variable carries noticeable random error. We provide software tools for estimation of a corrected slope in a simple linear regression model assuming data for a continuous dependent variable and a continuous risk factor from a main study and an additional measurement of the risk factor in a reliability study. Also, we supply programs for estimation of the number of individuals needed in the reliability study and for choice of its design. Our conclusion is that correction for regression dilution bias is seldom applied in epidemiological studies. This may cause important effects of risk factors with large measurement errors to be neglected.

  13. Measurement bias dependence of enhanced bipolar gain degradation at low dose rates

    International Nuclear Information System (INIS)

    Witczak, S.C.; Lacoe, R.C.; Mayer, D.C.; Fleetwood, D.M.

    1998-03-01

    Oxide trapped charge, field effects from emitter metallization, and high level injection phenomena moderate enhanced gain degradation of lateral pnp transistors at low dose rates. Hardness assurance tests at elevated irradiation temperatures require larger design margins for low power measurement biases

  14. A selective emotional decision-making bias elicited by facial expressions.

    Directory of Open Access Journals (Sweden)

    Nicholas Furl

    Full Text Available Emotional and social information can sway otherwise rational decisions. For example, when participants decide between two faces that are probabilistically rewarded, they make biased choices that favor smiling relative to angry faces. This bias may arise because facial expressions evoke positive and negative emotional responses, which in turn may motivate social approach and avoidance. We tested a wide range of pictures that evoke emotions or convey social information, including animals, words, foods, a variety of scenes, and faces differing in trustworthiness or attractiveness, but we found only facial expressions biased decisions. Our results extend brain imaging and pharmacological findings, which suggest that a brain mechanism supporting social interaction may be involved. Facial expressions appear to exert special influence over this social interaction mechanism, one capable of biasing otherwise rational choices. These results illustrate that only specific types of emotional experiences can best sway our choices.

  15. A Selective Emotional Decision-Making Bias Elicited by Facial Expressions

    Science.gov (United States)

    Furl, Nicholas; Gallagher, Shannon; Averbeck, Bruno B.

    2012-01-01

    Emotional and social information can sway otherwise rational decisions. For example, when participants decide between two faces that are probabilistically rewarded, they make biased choices that favor smiling relative to angry faces. This bias may arise because facial expressions evoke positive and negative emotional responses, which in turn may motivate social approach and avoidance. We tested a wide range of pictures that evoke emotions or convey social information, including animals, words, foods, a variety of scenes, and faces differing in trustworthiness or attractiveness, but we found only facial expressions biased decisions. Our results extend brain imaging and pharmacological findings, which suggest that a brain mechanism supporting social interaction may be involved. Facial expressions appear to exert special influence over this social interaction mechanism, one capable of biasing otherwise rational choices. These results illustrate that only specific types of emotional experiences can best sway our choices. PMID:22438936

  16. A selective emotional decision-making bias elicited by facial expressions.

    Science.gov (United States)

    Furl, Nicholas; Gallagher, Shannon; Averbeck, Bruno B

    2012-01-01

    Emotional and social information can sway otherwise rational decisions. For example, when participants decide between two faces that are probabilistically rewarded, they make biased choices that favor smiling relative to angry faces. This bias may arise because facial expressions evoke positive and negative emotional responses, which in turn may motivate social approach and avoidance. We tested a wide range of pictures that evoke emotions or convey social information, including animals, words, foods, a variety of scenes, and faces differing in trustworthiness or attractiveness, but we found only facial expressions biased decisions. Our results extend brain imaging and pharmacological findings, which suggest that a brain mechanism supporting social interaction may be involved. Facial expressions appear to exert special influence over this social interaction mechanism, one capable of biasing otherwise rational choices. These results illustrate that only specific types of emotional experiences can best sway our choices.

  17. The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

    Science.gov (United States)

    Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

    2009-09-21

    Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

  18. Sex attracts: investigating individual differences in attentional bias to sexual stimuli.

    Directory of Open Access Journals (Sweden)

    Sabine Kagerer

    Full Text Available We investigated the impact of sexual stimuli and the influence of sexual motivation on the performance in a dot-probe task and a line-orientation task in a large sample of males and females. All pictures (neutral, erotic were rated on the dimensions of valence, arousal, disgust, and sexual arousal. Additionally, questionnaires measuring sexual interest/desire/motivation were employed. The ratings of the sexual stimuli point to a successful picture selection because sexual arousal did not differ between the sexes. The stimuli were equally arousing for men and women. Higher scores in the employed questionnaires measuring sexual interest/desire/motivation led to higher sexual arousal ratings of the sex pictures. Attentional bias towards sex pictures was observed in both experimental tasks. The attentional biases measured by the dot-probe and the line-orientation task were moderately intercorrelated suggesting attentional bias as a possible marker for a sex-attention trait. Finally, only the sexual sensation seeking score correlated with the attentional biases of the two tasks. Future research is needed to increase the predictive power of these indirect measures of sexual interest.

  19. Common method biases in behavioral research: a critical review of the literature and recommended remedies.

    Science.gov (United States)

    Podsakoff, Philip M; MacKenzie, Scott B; Lee, Jeong-Yeon; Podsakoff, Nathan P

    2003-10-01

    Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.

  20. Multi-faceted Rasch measurement and bias patterns in EFL writing performance assessment.

    Science.gov (United States)

    He, Tung-Hsien; Gou, Wen Johnny; Chien, Ya-Chen; Chen, I-Shan Jenny; Chang, Shan-Mao

    2013-04-01

    This study applied multi-faceted Rasch measurement to examine rater bias in the assessment of essays written by college students learning English as a foreign language. Four raters who had received different academic training from four distinctive disciplines applied a six-category rating scale to analytically rate essays on an argumentative topic and on a descriptive topic. FACETS, a Rasch computer program, was utilized to pinpoint bias patterns by analyzing the rater-topic, rater-category, and topic-category interactions. Results showed: argumentative essays were rated more severely than were descriptive essays; the linguistics-major rater was the most lenient rater, while the literature-major rater was the severest one; and the category of language use received the severest ratings, whereas content was given the most lenient ratings. The severity hierarchies for raters, essay topics, and rating categories suggested that raters' academic training and their perceptions of the importance of categories were associated with their bias patterns. Implications for rater training are discussed.

  1. Nucleus accumbens shell moderates preference bias during voluntary choice behavior.

    Science.gov (United States)

    Jang, Hyeran; Jung, Kanghoon; Jeong, Jaehoon; Park, Sang Ki; Kralik, Jerald D; Jeong, Jaeseung

    2017-09-01

    The nucleus accumbens (NAc) shell lies anatomically at a critical intersection within the brain's reward system circuitry, however, its role in voluntary choice behavior remains unclear. Rats with electrolytic lesions in the NAc shell were tested in a novel foraging paradigm. Over a continuous two-week period they freely chose among four nutritionally identical but differently flavored food pellets by pressing corresponding levers. We examined the lesion's effects on three behavioral dynamics components: motivation (when to eat), preference bias (what to choose) and persistence (how long to repeat the same choice). The lesion led to a marked increase in the preference bias: i.e., increased selection of the most-preferred choice option, and decreased selection of the others. We found no effects on any other behavioral measures, suggesting no effect on motivation or choice persistence. The results implicate the NAc shell in moderating the instrumental valuation process by inhibiting excessive bias toward preferred choice options. © The Author (2017). Published by Oxford University Press.

  2. Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network.

    Science.gov (United States)

    Byrd, Darrin; Christopfel, Rebecca; Arabasz, Grae; Catana, Ciprian; Karp, Joel; Lodge, Martin A; Laymon, Charles; Moros, Eduardo G; Budzevich, Mikalai; Nehmeh, Sadek; Scheuermann, Joshua; Sunderland, John; Zhang, Jun; Kinahan, Paul

    2018-01-01

    Positron emission tomography (PET) is a quantitative imaging modality, but the computation of standardized uptake values (SUVs) requires several instruments to be correctly calibrated. Variability in the calibration process may lead to unreliable quantitation. Sealed source kits containing traceable amounts of [Formula: see text] were used to measure signal stability for 19 PET scanners at nine hospitals in the National Cancer Institute's Quantitative Imaging Network. Repeated measurements of the sources were performed on PET scanners and in dose calibrators. The measured scanner and dose calibrator signal biases were used to compute the bias in SUVs at multiple time points for each site over a 14-month period. Estimation of absolute SUV accuracy was confounded by bias from the solid phantoms' physical properties. On average, the intrascanner coefficient of variation for SUV measurements was 3.5%. Over the entire length of the study, single-scanner SUV values varied over a range of 11%. Dose calibrator bias was not correlated with scanner bias. Calibration factors from the image metadata were nearly as variable as scanner signal, and were correlated with signal for many scanners. SUVs often showed low intrascanner variability between successive measurements but were also prone to shifts in apparent bias, possibly in part due to scanner recalibrations that are part of regular scanner quality control. Biases of key factors in the computation of SUVs were not correlated and their temporal variations did not cancel out of the computation. Long-lived sources and image metadata may provide a check on the recalibration process.

  3. Effects of habitat features on size-biased predation on salmon by bears.

    Science.gov (United States)

    Andersson, Luke C; Reynolds, John D

    2017-05-01

    Predators can drive trait divergence among populations of prey by imposing differential selection on prey traits. Habitat characteristics can mediate predator selectivity by providing refuge for prey. We quantified the effects of stream characteristics on biases in the sizes of spawning salmon caught by bears (Ursus arctos and U. americanus) on the central coast of British Columbia, Canada by measuring size-biased predation on spawning chum (Oncorhynchus keta) and pink (O. gorbuscha) salmon in 12 streams with varying habitat characteristics. We tested the hypotheses that bears would catch larger than average salmon (size-biased predation) and that this bias toward larger fish would be higher in streams that provide less protection to spawning salmon from predation (e.g., less pools, wood, undercut banks). We then we tested for how such size biases in turn translate into differences among populations in the sizes of the fish. Bears caught larger-than-average salmon as the spawning season progressed and as predicted, this was most pronounced in streams with fewer refugia for the fish (i.e., wood and undercut banks). Salmon were marginally smaller in streams with more pronounced size-biased predation but this predictor was less reliable than physical characteristics of streams, with larger fish in wider, deeper streams. These results support the hypothesis that selective forces imposed by predators can be mediated by habitat characteristics, with potential consequences for physical traits of prey.

  4. Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

    Science.gov (United States)

    Hearty, Thomas J.; Savtchenko, Andrey K.; Tian, Baijun; Fetzer, Eric; Yung, Yuk L.; Theobald, Michael; Vollmer, Bruce; Fishbein, Evan; Won, Young-In

    2014-01-01

    We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

  5. Religious attendance after elevated depressive symptoms: is selection bias at work?

    Directory of Open Access Journals (Sweden)

    Lloyd Balbuena

    2014-03-01

    Full Text Available In an attempt to determine if selection bias could be a reason that religious attendance and depression are related, the predictive value of elevated depressive symptoms for a decrease in future attendance at religious services was examined in a longitudinal panel of 1,673 Dutch adults. Religious attendance was assessed yearly over five years using the single question, “how often do you attend religious gatherings nowadays?” Depressive symptoms were assessed four times within the first year using the Depression subscale of the Brief Symptom Inventory. Logistic regression models of change in attendance were created, stratifying by baseline attendance status. Attenders who developed elevated symptoms were less likely to subsequently decrease their attendance (relative risk ratio: 0.55, 95% CI [0.38–0.79] relative to baseline as compared to those without elevated symptoms. This inverse association remained significant after controlling for health and demographic covariates, and when using multiply imputed data to account for attrition. Non-attenders were unlikely to start attending after elevated depressive symptoms. This study provides counter evidence against previous findings that church attenders are a self-selected healthier group.

  6. Educational Research with Real-World Data: Reducing Selection Bias with Propensity Scores

    Directory of Open Access Journals (Sweden)

    Jill L. Adelson

    2013-12-01

    Full Text Available Often it is infeasible or unethical to use random assignment in educational settings to study important constructs and questions. Hence, educational research often uses observational data, such as large-scale secondary data sets and state and school district data, and quasi-experimental designs. One method of reducing selection bias in estimations of treatment effects is propensity score analysis. This method reduces a large number of pretreatment covariates to a single scalar function and allows researchers to compare subjects with similar probability to receive the treatment. This article provides an introduction to propensity score analysis and stratification, an example illustrating its use, and suggestions for using propensity score analysis in educational research.

  7. A single extracellular amino acid in Free Fatty Acid Receptor 2 defines antagonist species selectivity and G protein selection bias

    DEFF Research Database (Denmark)

    Sergeev, Eugenia; Hansen, Anders Højgaard; Bolognini, Daniele

    2017-01-01

    selectivity and mutational swap studies confirmed this hypothesis. Extending these studies to agonist function indicated that although the lysine - arginine variation between human and mouse orthologs had limited effect on G protein-mediated signal transduction, removal of positive charge from this residue...... produced a signalling-biased variant of Free Fatty Acid Receptor 2 in which Gi-mediated signalling by both short chain fatty acids and synthetic agonists was maintained whilst there was marked loss of agonist potency for signalling via Gq/11 and G12/13 G proteins. A single residue at the extracellular face...

  8. Measurement of Negativity Bias in Personal Narratives Using Corpus-Based Emotion Dictionaries

    Science.gov (United States)

    Cohen, Shuki J.

    2011-01-01

    This study presents a novel methodology for the measurement of negativity bias using positive and negative dictionaries of emotion words applied to autobiographical narratives. At odds with the cognitive theory of mood dysregulation, previous text-analytical studies have failed to find significant correlation between emotion dictionaries and…

  9. Inviting parents to take part in paediatric palliative care research: a mixed-methods examination of selection bias.

    Science.gov (United States)

    Crocker, Joanna C; Beecham, Emma; Kelly, Paula; Dinsdale, Andrew P; Hemsley, June; Jones, Louise; Bluebond-Langner, Myra

    2015-03-01

    Recruitment to paediatric palliative care research is challenging, with high rates of non-invitation of eligible families by clinicians. The impact on sample characteristics is unknown. To investigate, using mixed methods, non-invitation of eligible families and ensuing selection bias in an interview study about parents' experiences of advance care planning (ACP). We examined differences between eligible families invited and not invited to participate by clinicians using (1) field notes of discussions with clinicians during the invitation phase and (2) anonymised information from the service's clinical database. Families were eligible for the ACP study if their child was receiving care from a UK-based tertiary palliative care service (Group A; N = 519) or had died 6-10 months previously having received care from the service (Group B; N = 73). Rates of non-invitation to the ACP study were high. A total of 28 (5.4%) Group A families and 21 (28.8%) Group B families (p research findings. Non-invitation and selection bias should be considered, assessed and reported in palliative care studies. © The Author(s) 2014.

  10. Tunable reverse-biased graphene/silicon heterojunction Schottky diode sensor.

    Science.gov (United States)

    Singh, Amol; Uddin, Ahsan; Sudarshan, Tangali; Koley, Goutam

    2014-04-24

    A new chemical sensor based on reverse-biased graphene/Si heterojunction diode has been developed that exhibits extremely high bias-dependent molecular detection sensitivity and low operating power. The device takes advantage of graphene's atomically thin nature, which enables molecular adsorption on its surface to directly alter graphene/Si interface barrier height, thus affecting the junction current exponentially when operated in reverse bias and resulting in ultrahigh sensitivity. By operating the device in reverse bias, the work function of graphene, and hence the barrier height at the graphene/Si heterointerface, can be controlled by the bias magnitude, leading to a wide tunability of the molecular detection sensitivity. Such sensitivity control is also possible by carefully selecting the graphene/Si heterojunction Schottky barrier height. Compared to a conventional graphene amperometric sensor fabricated on the same chip, the proposed sensor demonstrated 13 times higher sensitivity for NO₂ and 3 times higher for NH₃ in ambient conditions, while consuming ∼500 times less power for same magnitude of applied voltage bias. The sensing mechanism based on heterojunction Schottky barrier height change has been confirmed using capacitance-voltage measurements. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Estimation bias from using nonlinear Fourier plane correlators for sub-pixel image shift measurement and implications for the binary joint transform correlator

    Science.gov (United States)

    Grycewicz, Thomas J.; Florio, Christopher J.; Franz, Geoffrey A.; Robinson, Ross E.

    2007-09-01

    When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images, interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than 0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.

  12. Latest Minimum Bias and Underlying Event measurements with the ATLAS Detector

    CERN Document Server

    Cairo, Valentina Maria; The ATLAS collaboration

    2018-01-01

    The modeling of Minimum Bias and Underlying Event is a crucial component in the description of soft Quantum Chromodynamics processes. They are both described by multi-parton interaction models, the result of proton collisions containing more than one partonic interaction due to collective and beam remnant effects. Recent ATLAS studies aimed at measuring Charged-Particle distributions and the properties of the Underlying Event are presented.

  13. Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

    Science.gov (United States)

    Theis, Fabian J.

    2017-01-01

    Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

  14. Structural optimization and structure-functional selectivity relationship studies of G protein-biased EP2 receptor agonists.

    Science.gov (United States)

    Ogawa, Seiji; Watanabe, Toshihide; Moriyuki, Kazumi; Goto, Yoshikazu; Yamane, Shinsaku; Watanabe, Akio; Tsuboi, Kazuma; Kinoshita, Atsushi; Okada, Takuya; Takeda, Hiroyuki; Tani, Kousuke; Maruyama, Toru

    2016-05-15

    The modification of the novel G protein-biased EP2 agonist 1 has been investigated to improve its G protein activity and develop a better understanding of its structure-functional selectivity relationship (SFSR). The optimization of the substituents on the phenyl ring of 1, followed by the inversion of the hydroxyl group on the cyclopentane moiety led to compound 9, which showed a 100-fold increase in its G protein activity compared with 1 without any increase in β-arrestin recruitment. Furthermore, SFSR studies revealed that the combination of meta and para substituents on the phenyl moiety was crucial to the functional selectivity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Good practices for quantitative bias analysis.

    Science.gov (United States)

    Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander

    2014-12-01

    Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage

  16. Non-Gaussian halo assembly bias

    International Nuclear Information System (INIS)

    Reid, Beth A.; Verde, Licia; Dolag, Klaus; Matarrese, Sabino; Moscardini, Lauro

    2010-01-01

    The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f NL , offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ∼ 23% and ∼ 48% for galaxies at z = 1 selected by stellar mass and star formation rate, respectively

  17. Reduction of determinate errors in mass bias-corrected isotope ratios measured using a multi-collector plasma mass spectrometer

    International Nuclear Information System (INIS)

    Doherty, W.

    2015-01-01

    A nebulizer-centric instrument response function model of the plasma mass spectrometer was combined with a signal drift model, and the result was used to identify the causes of the non-spectroscopic determinate errors remaining in mass bias-corrected Pb isotope ratios (Tl as internal standard) measured using a multi-collector plasma mass spectrometer. Model calculations, confirmed by measurement, show that the detectable time-dependent errors are a result of the combined effect of signal drift and differences in the coordinates of the Pb and Tl response function maxima (horizontal offset effect). If there are no horizontal offsets, then the mass bias-corrected isotope ratios are approximately constant in time. In the absence of signal drift, the response surface curvature and horizontal offset effects are responsible for proportional errors in the mass bias-corrected isotope ratios. The proportional errors will be different for different analyte isotope ratios and different at every instrument operating point. Consequently, mass bias coefficients calculated using different isotope ratios are not necessarily equal. The error analysis based on the combined model provides strong justification for recommending a three step correction procedure (mass bias correction, drift correction and a proportional error correction, in that order) for isotope ratio measurements using a multi-collector plasma mass spectrometer

  18. Broadband non-selective excitation of plutonium isotopes for isotope ratio measurements in resonance ionization mass spectrometry: a theoretical study.

    Science.gov (United States)

    Sankari, M

    2012-10-15

    Making isotope ratio measurements with minimum isotope bias has always been a challenging task to mass spectrometrists, especially for the specific case of plutonium, owing to the strategic importance of the element. In order to use resonance ionization mass spectrometry (RIMS) as a tool for isotope ratio measurements, optimization of the various laser parameters and other atomic and system parameters is critical to minimize isotopic biases. Broadband simultaneous non-selective excitation of the isotopes of plutonium in the triple resonance excitation scheme with λ(1) = 420.77 nm, λ(2) = 847.28 nm, and λ(3) = 767.53 nm based on density matrix formalism has been theoretically computed for the determination of isotope ratios. The effects of the various laser parameters and other factors such as the atomization temperature and the dimensions of the atomic beam on the estimation of isotope ratios were studied. The effects of Doppler broadening, and time-dependent excitation parameters such as Rabi frequencies, ionization rate and the effect of non-Lorenztian lineshape have all been incorporated. The average laser powers and bandwidths for the three-excitation steps were evaluated for non-selective excitation. The laser intensity required to saturate the three-excitation steps were studied. The two-dimensional lineshape contour and its features were investigated, while the reversal of peak asymmetry of two-step and two-photon excitation peaks under these conditions is discussed. Optimized powers for the non-selective ionization of the three transitions were calculated as 545 mW, 150 mW and 545 mW and the laser bandwidth for all the three steps was ~20 GHz. The isotopic bias between the resonant and off-resonant isotope under the optimized conditions was no more than 9%, which is better than an earlier reported value. These optimized laser power and bandwidth conditions are better than in the earlier experimental work since these comprehensive calculations yield

  19. Semiparametric efficient and robust estimation of an unknown symmetric population under arbitrary sample selection bias

    KAUST Repository

    Ma, Yanyuan

    2013-09-01

    We propose semiparametric methods to estimate the center and shape of a symmetric population when a representative sample of the population is unavailable due to selection bias. We allow an arbitrary sample selection mechanism determined by the data collection procedure, and we do not impose any parametric form on the population distribution. Under this general framework, we construct a family of consistent estimators of the center that is robust to population model misspecification, and we identify the efficient member that reaches the minimum possible estimation variance. The asymptotic properties and finite sample performance of the estimation and inference procedures are illustrated through theoretical analysis and simulations. A data example is also provided to illustrate the usefulness of the methods in practice. © 2013 American Statistical Association.

  20. Social desirability bias in dietary self-report may compromise the validity of dietary intake measures.

    Science.gov (United States)

    Hebert, J R; Clemow, L; Pbert, L; Ockene, I S; Ockene, J K

    1995-04-01

    Self-report of dietary intake could be biased by social desirability or social approval thus affecting risk estimates in epidemiological studies. These constructs produce response set biases, which are evident when testing in domains characterized by easily recognizable correct or desirable responses. Given the social and psychological value ascribed to diet, assessment methodologies used most commonly in epidemiological studies are particularly vulnerable to these biases. Social desirability and social approval biases were tested by comparing nutrient scores derived from multiple 24-hour diet recalls (24HR) on seven randomly assigned days with those from two 7-day diet recalls (7DDR) (similar in some respects to commonly used food frequency questionnaires), one administered at the beginning of the test period (pre) and one at the end (post). Statistical analysis included correlation and multiple linear regression. Cross-sectionally, no relationships between social approval score and the nutritional variables existed. Social desirability score was negatively correlated with most nutritional variables. In linear regression analysis, social desirability score produced a large downward bias in nutrient estimation in the 7DDR relative to the 24HR. For total energy, this bias equalled about 50 kcal/point on the social desirability scale or about 450 kcal over its interquartile range. The bias was approximately twice as large for women as for men and only about half as large in the post measures. Individuals having the highest 24HR-derived fat and total energy intake scores had the largest downward bias due to social desirability. We observed a large downward bias in reporting food intake related to social desirability score. These results are consistent with the theoretical constructs on which the hypothesis is based. The effect of social desirability bias is discussed in terms of its influence on epidemiological estimates of effect. Suggestions are made for future work

  1. Weight Bias: A Systematic Review of Characteristics and Psychometric Properties of Self-Report Questionnaires.

    Science.gov (United States)

    Lacroix, Emilie; Alberga, Angela; Russell-Mathew, Shelly; McLaren, Lindsay; von Ranson, Kristin

    2017-01-01

    People living with overweight and obesity often experience weight-based stigmatization. Investigations of the prevalence and correlates of weight bias and evaluation of weight bias reduction interventions depend upon psychometrically-sound measurement. Our paper is the first to comprehensively evaluate the psychometric properties, use of people-first language within items, and suitability for use with various populations of available self-report measures of weight bias. We searched five electronic databases to identify English-language self-report questionnaires of weight bias. We rated each questionnaire's psychometric properties based on initial validation reports and subsequent use, and examined item language. Our systematic review identified 40 original self-report questionnaires. Most questionnaires were brief, demonstrated adequate internal consistency, and tapped key cognitive and affective dimensions of weight bias such as stereotypes and blaming. Current psychometric evidence is incomplete for many questionnaires, particularly with regard to the properties of test-retest reliability, sensitivity to change as well as discriminant and structural validity. Most questionnaires were developed prior to debate surrounding terminology preferences, and do not employ people-first language in the items administered to participants. We provide information and recommendations for clinicians and researchers in selecting psychometrically sound measures of weight bias for various purposes and populations, and discuss future directions to improve measurement of this construct. © 2017 The Author(s) Published by S. Karger GmbH, Freiburg.

  2. A KiDS weak lensing analysis of assembly bias in GAMA galaxy groups

    Science.gov (United States)

    Dvornik, Andrej; Cacciato, Marcello; Kuijken, Konrad; Viola, Massimo; Hoekstra, Henk; Nakajima, Reiko; van Uitert, Edo; Brouwer, Margot; Choi, Ami; Erben, Thomas; Fenech Conti, Ian; Farrow, Daniel J.; Herbonnet, Ricardo; Heymans, Catherine; Hildebrandt, Hendrik; Hopkins, Andrew M.; McFarland, John; Norberg, Peder; Schneider, Peter; Sifón, Cristóbal; Valentijn, Edwin; Wang, Lingyu

    2017-07-01

    We investigate possible signatures of halo assembly bias for spectroscopically selected galaxy groups from the Galaxy And Mass Assembly (GAMA) survey using weak lensing measurements from the spatially overlapping regions of the deeper, high-imaging-quality photometric Kilo-Degree Survey. We use GAMA groups with an apparent richness larger than 4 to identify samples with comparable mean host halo masses but with a different radial distribution of satellite galaxies, which is a proxy for the formation time of the haloes. We measure the weak lensing signal for groups with a steeper than average and with a shallower than average satellite distribution and find no sign of halo assembly bias, with the bias ratio of 0.85^{+0.37}_{-0.25}, which is consistent with the Λ cold dark matter prediction. Our galaxy groups have typical masses of 1013 M⊙ h-1, naturally complementing previous studies of halo assembly bias on galaxy cluster scales.

  3. [Potential selection bias in telephone surveys: landline and mobile phones].

    Science.gov (United States)

    Garcia-Continente, Xavier; Pérez-Giménez, Anna; López, María José; Nebot, Manel

    2014-01-01

    The increasing use of mobile phones in the last decade has decreased landline telephone coverage in Spanish households. This study aimed to analyze sociodemographic characteristics and health indicators by type of telephone service (mobile phone vs. landline or landline and mobile phone). Two telephone surveys were conducted in Spanish samples (February 2010 and February 2011). Multivariate logistic regression analyses were performed to analyze differences in the main sociodemographic characteristics and health indicators according to the type of telephone service available in Spanish households. We obtained 2027 valid responses (1627 landline telephones and 400 mobile phones). Persons contacted through a mobile phone were more likely to be a foreigner, to belong to the manual social class, to have a lower educational level, and to be a smoker than those contacted through a landline telephone. The profile of the population that has only a mobile phone differs from that with a landline telephone. Therefore, telephone surveys that exclude mobile phones could show a selection bias. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

  4. Behind the scenes: how visual memory load biases selective attention during processing of visual streams.

    Science.gov (United States)

    Klaver, Peter; Talsma, Durk

    2013-11-01

    We recorded ERPs to investigate whether the visual memory load can bias visual selective attention. Participants memorized one or four letters and then responded to memory-matching letters presented in a relevant color while ignoring distractor letters or letters in an irrelevant color. Stimuli in the relevant color elicited larger frontal selection positivities (FSP) and occipital selection negativities (OSN) compared to irrelevant color stimuli. Only distractors elicited a larger FSP in the high than in the low memory load task. Memory load prolonged the OSN for all letters. Response mapping complexity was also modulated but did not affect the FSP and OSN. Together, the FSP data suggest that high memory load increased distractability. The OSN data suggest that memory load sustained attention to letters in a relevant color until working memory processing was completed, independently of whether the letters were in working memory or not. Copyright © 2013 Society for Psychophysiological Research.

  5. CEO emotional bias and investment decision, Bayesian network method

    Directory of Open Access Journals (Sweden)

    Jarboui Anis

    2012-08-01

    Full Text Available This research examines the determinants of firms’ investment introducing a behavioral perspective that has received little attention in corporate finance literature. The following central hypothesis emerges from a set of recently developed theories: Investment decisions are influenced not only by their fundamentals but also depend on some other factors. One factor is the biasness of any CEO to their investment, biasness depends on the cognition and emotions, because some leaders use them as heuristic for the investment decision instead of fundamentals. This paper shows how CEO emotional bias (optimism, loss aversion and overconfidence affects the investment decisions. The proposed model of this paper uses Bayesian Network Method to examine this relationship. Emotional bias has been measured by means of a questionnaire comprising several items. As for the selected sample, it has been composed of some 100 Tunisian executives. Our results have revealed that the behavioral analysis of investment decision implies leader affected by behavioral biases (optimism, loss aversion, and overconfidence adjusts its investment choices based on their ability to assess alternatives (optimism and overconfidence and risk perception (loss aversion to create of shareholder value and ensure its place at the head of the management team.

  6. Estimate of Radiosonde Dry Bias From Far-Infrared Measurements on the Antarctic Plateau

    Science.gov (United States)

    Rizzi, R.; Maestri, T.; Arosio, C.

    2018-03-01

    The experimental data set of downwelling radiance spectra measured at the ground in clear conditions during 2013 by a Far-Infrared Fourier Transform Spectrometer at Dome-C, Antarctica, presented in Rizzi et al. (2016, https://doi.org/10.1002/2016JD025341) is used to estimate the effect of solar heating of the radiosonde humidity sensor, called dry bias. The effect is quite evident comparing residuals for the austral summer and winter clear cases and can be modeled by an increase of the water vapor concentration at all levels by about 15%. Such an estimate has become possible only after a new version of the simulation code and spectroscopic data has become available, which has substantially improved the modeling of water vapor absorption in the far infrared. The negative yearly spectral bias reported in Rizzi et al. (2016, https://doi.org/10.1002/2016JD025341) is in fact greatly reduced when compared to the same measurement data set.

  7. Bias correction for selecting the minimal-error classifier from many machine learning models.

    Science.gov (United States)

    Ding, Ying; Tang, Shaowu; Liao, Serena G; Jia, Jia; Oesterreich, Steffi; Lin, Yan; Tseng, George C

    2014-11-15

    Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts. In this article, we illustrated the probabilistic framework of the problem and explored the statistical and asymptotic properties. We proposed a new bias correction method based on learning curve fitting by inverse power law (IPL) and compared it with three existing methods: nested cross-validation, weighted mean correction and Tibshirani-Tibshirani procedure. All methods were compared in simulation datasets, five moderate size real datasets and two large breast cancer datasets. The result showed that IPL outperforms the other methods in bias correction with smaller variance, and it has an additional advantage to extrapolate error estimates for larger sample sizes, a practical feature to recommend whether more samples should be recruited to improve the classifier and accuracy. An R package 'MLbias' and all source files are publicly available. tsenglab.biostat.pitt.edu/software.htm. ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. Influence of monitoring data selection for optimization of a steady state multimedia model on the magnitude and nature of the model prediction bias.

    Science.gov (United States)

    Kim, Hee Seok; Lee, Dong Soo

    2017-11-01

    SimpleBox is an important multimedia model used to estimate the predicted environmental concentration for screening-level exposure assessment. The main objectives were (i) to quantitatively assess how the magnitude and nature of prediction bias of SimpleBox vary with the selection of observed concentration data set for optimization and (ii) to present the prediction performance of the optimized SimpleBox. The optimization was conducted using a total of 9604 observed multimedia data for 42 chemicals of four groups (i.e., polychlorinated dibenzo-p-dioxins/furans (PCDDs/Fs), polybrominated diphenyl ethers (PBDEs), phthalates, and polycyclic aromatic hydrocarbons (PAHs)). The model performance was assessed based on the magnitude and skewness of prediction bias. Monitoring data selection in terms of number of data and kind of chemicals plays a significant role in optimization of the model. The coverage of the physicochemical properties was found to be very important to reduce the prediction bias. This suggests that selection of observed data should be made such that the physicochemical property (such as vapor pressure, octanol-water partition coefficient, octanol-air partition coefficient, and Henry's law constant) range of the selected chemical groups be as wide as possible. With optimization, about 55%, 90%, and 98% of the total number of the observed concentration ratios were predicted within factors of three, 10, and 30, respectively, with negligible skewness. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Potential sources of analytical bias and error in selected trace element data-quality analyses

    Science.gov (United States)

    Paul, Angela P.; Garbarino, John R.; Olsen, Lisa D.; Rosen, Michael R.; Mebane, Christopher A.; Struzeski, Tedmund M.

    2016-09-28

    Potential sources of analytical bias and error associated with laboratory analyses for selected trace elements where concentrations were greater in filtered samples than in paired unfiltered samples were evaluated by U.S. Geological Survey (USGS) Water Quality Specialists in collaboration with the USGS National Water Quality Laboratory (NWQL) and the Branch of Quality Systems (BQS).Causes for trace-element concentrations in filtered samples to exceed those in associated unfiltered samples have been attributed to variability in analytical measurements, analytical bias, sample contamination either in the field or laboratory, and (or) sample-matrix chemistry. These issues have not only been attributed to data generated by the USGS NWQL but have been observed in data generated by other laboratories. This study continues the evaluation of potential analytical bias and error resulting from matrix chemistry and instrument variability by evaluating the performance of seven selected trace elements in paired filtered and unfiltered surface-water and groundwater samples collected from 23 sampling sites of varying chemistries from six States, matrix spike recoveries, and standard reference materials.Filtered and unfiltered samples have been routinely analyzed on separate inductively coupled plasma-mass spectrometry instruments. Unfiltered samples are treated with hydrochloric acid (HCl) during an in-bottle digestion procedure; filtered samples are not routinely treated with HCl as part of the laboratory analytical procedure. To evaluate the influence of HCl on different sample matrices, an aliquot of the filtered samples was treated with HCl. The addition of HCl did little to differentiate the analytical results between filtered samples treated with HCl from those samples left untreated; however, there was a small, but noticeable, decrease in the number of instances where a particular trace-element concentration was greater in a filtered sample than in the associated

  10. Low noise constant current source for bias dependent noise measurements

    International Nuclear Information System (INIS)

    Talukdar, D.; Bose, Suvendu; Bardhan, K. K.; Chakraborty, R. K.

    2011-01-01

    A low noise constant current source used for measuring the 1/f noise in disordered systems in ohmic as well as nonohmic regime is described. The source can supply low noise constant current starting from as low as 1 μA to a few tens of milliampere with a high voltage compliance limit of around 20 V. The constant current source has several stages, which can work in a standalone manner or together to supply the desired value of load current. The noise contributed by the current source is very low in the entire current range. The fabrication of a low noise voltage preamplifier modified for bias dependent noise measurements and based on the existing design available in the MAT04 data sheet is also described.

  11. BIAS IN THE MEASUREMENT OF QUALITY OF LIFE: RESPONSE SHIFT

    Directory of Open Access Journals (Sweden)

    Yesim SENOL

    2006-10-01

    Full Text Available Quality of Life (QoL is a descriptive term that refers to people’s emotional, social and physical wellbeing, and their ability to function in the ordinary task of living. The importance of QoL makes it critical to improve and refine measure to understand patients’ experience of health, illness and treatment. However individuals change with time and the basis on which they make a QoL judgment may also change, a phenomenon increasingly referred to as response shift. The definition of response shift is recalibration of internal standards of measurement and reconceptualization of the meaning of item. The purpose of study is to discuss the effects of response shift bias. [TAF Prev Med Bull 2006; 5(5.000: 382-389

  12. Bias Correction and Random Error Characterization for the Assimilation of HRDI Line-of-Sight Wind Measurements

    Science.gov (United States)

    Tangborn, Andrew; Menard, Richard; Ortland, David; Einaudi, Franco (Technical Monitor)

    2001-01-01

    A new approach to the analysis of systematic and random observation errors is presented in which the error statistics are obtained using forecast data rather than observations from a different instrument type. The analysis is carried out at an intermediate retrieval level, instead of the more typical state variable space. This method is carried out on measurements made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). HRDI, a limb sounder, is the only satellite instrument measuring winds in the stratosphere, and the only instrument of any kind making global wind measurements in the upper atmosphere. HRDI measures doppler shifts in the two different O2 absorption bands (alpha and B) and the retrieved products are tangent point Line-of-Sight wind component (level 2 retrieval) and UV winds (level 3 retrieval). This analysis is carried out on a level 1.9 retrieval, in which the contributions from different points along the line-of-sight have not been removed. Biases are calculated from O-F (observed minus forecast) LOS wind components and are separated into a measurement parameter space consisting of 16 different values. The bias dependence on these parameters (plus an altitude dependence) is used to create a bias correction scheme carried out on the level 1.9 retrieval. The random error component is analyzed by separating the gamma and B band observations and locating observation pairs where both bands are very nearly looking at the same location at the same time. It is shown that the two observation streams are uncorrelated and that this allows the forecast error variance to be estimated. The bias correction is found to cut the effective observation error variance in half.

  13. Estimates of bias and uncertainty in recorded external dose

    International Nuclear Information System (INIS)

    Fix, J.J.; Gilbert, E.S.; Baumgartner, W.V.

    1994-10-01

    A study is underway to develop an approach to quantify bias and uncertainty in recorded dose estimates for workers at the Hanford Site based on personnel dosimeter results. This paper focuses on selected experimental studies conducted to better define response characteristics of Hanford dosimeters. The study is more extensive than the experimental studies presented in this paper and includes detailed consideration and evaluation of other sources of bias and uncertainty. Hanford worker dose estimates are used in epidemiologic studies of nuclear workers. A major objective of these studies is to provide a direct assessment of the carcinogenic risk of exposure to ionizing radiation at low doses and dose rates. Considerations of bias and uncertainty in the recorded dose estimates are important in the conduct of this work. The method developed for use with Hanford workers can be considered an elaboration of the approach used to quantify bias and uncertainty in estimated doses for personnel exposed to radiation as a result of atmospheric testing of nuclear weapons between 1945 and 1962. This approach was first developed by a National Research Council (NRC) committee examining uncertainty in recorded film badge doses during atmospheric tests (NRC 1989). It involved quantifying both bias and uncertainty from three sources (i.e., laboratory, radiological, and environmental) and then combining them to obtain an overall assessment. Sources of uncertainty have been evaluated for each of three specific Hanford dosimetry systems (i.e., the Hanford two-element film dosimeter, 1944-1956; the Hanford multi-element film dosimeter, 1957-1971; and the Hanford multi-element TLD, 1972-1993) used to estimate personnel dose throughout the history of Hanford operations. Laboratory, radiological, and environmental sources of bias and uncertainty have been estimated based on historical documentation and, for angular response, on selected laboratory measurements

  14. On the model-dependence of the relation between minimum-bias and inelastic proton-proton cross sections

    International Nuclear Information System (INIS)

    Ostapchenko, S.

    2011-01-01

    The model-dependence of the relation between the inelastic and various minimum-bias proton-proton cross sections is analyzed, paying a special attention to the sensitivity of minimum-bias triggers to diffractive collisions. Concentrating on the trigger selections of the ATLAS experiment, the measured cross sections are compared to predictions of a number of hadronic Monte Carlo models used in the cosmic ray field. It is demonstrated that the ATLAS results are able to discriminate between different models and between certain theoretical approaches for soft multi-particle production. On the other hand, the strong model-dependence of the selection efficiency of the minimum-bias triggers prevents one from inferring high mass diffraction rate from the discussed data. Moreover, the measured cross sections prove to be insensitive to the production of low mass diffractive states in proton-proton collisions. Consequently, a reliable determination of the total inelastic cross section requires forward proton tracking by a dedicated experiment.

  15. Codon usage bias: causative factors, quantification methods and genome-wide patterns: with emphasis on insect genomes.

    Science.gov (United States)

    Behura, Susanta K; Severson, David W

    2013-02-01

    Codon usage bias refers to the phenomenon where specific codons are used more often than other synonymous codons during translation of genes, the extent of which varies within and among species. Molecular evolutionary investigations suggest that codon bias is manifested as a result of balance between mutational and translational selection of such genes and that this phenomenon is widespread across species and may contribute to genome evolution in a significant manner. With the advent of whole-genome sequencing of numerous species, both prokaryotes and eukaryotes, genome-wide patterns of codon bias are emerging in different organisms. Various factors such as expression level, GC content, recombination rates, RNA stability, codon position, gene length and others (including environmental stress and population size) can influence codon usage bias within and among species. Moreover, there has been a continuous quest towards developing new concepts and tools to measure the extent of codon usage bias of genes. In this review, we outline the fundamental concepts of evolution of the genetic code, discuss various factors that may influence biased usage of synonymous codons and then outline different principles and methods of measurement of codon usage bias. Finally, we discuss selected studies performed using whole-genome sequences of different insect species to show how codon bias patterns vary within and among genomes. We conclude with generalized remarks on specific emerging aspects of codon bias studies and highlight the recent explosion of genome-sequencing efforts on arthropods (such as twelve Drosophila species, species of ants, honeybee, Nasonia and Anopheles mosquitoes as well as the recent launch of a genome-sequencing project involving 5000 insects and other arthropods) that may help us to understand better the evolution of codon bias and its biological significance. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

  16. Dopamine receptor blockade attenuates the general incentive motivational effects of noncontingently delivered rewards and reward-paired cues without affecting their ability to bias action selection.

    Science.gov (United States)

    Ostlund, Sean B; Maidment, Nigel T

    2012-01-01

    Environmental cues affect our behavior in a variety of ways. Despite playing an invaluable role in guiding our daily activities, such cues also appear to trigger the harmful, compulsive behaviors that characterize addiction and other disorders of behavioral control. In instrumental conditioning, rewards and reward-paired cues bias action selection and invigorate reward-seeking behaviors, and appear to do so through distinct neurobehavioral processes. Although reward-paired cues are known to invigorate performance through a dopamine-dependent incentive motivational process, it is not known if dopamine also mediates the influence of rewards and reward-paired cues over action selection. The current study contrasted the effects of systemic administration of the nonspecific dopamine receptor antagonist flupentixol on response invigoration and action bias in Pavlovian-instrumental transfer, a test of cue-elicited responding, and in instrumental reinstatement, a test of noncontingent reward-elicited responding. Hungry rats were trained on two different stimulus-outcome relationships (eg, tone-grain pellets and noise-sucrose solution) and two different action-outcome relationships (eg, left press-grain and right press-sucrose). At test, we found that flupentixol pretreatment blocked the response invigoration generated by the cues but spared their ability to bias action selection to favor the action whose outcome was signaled by the cue being presented. The response-biasing influence of noncontingent reward deliveries was also unaffected by flupentixol. Interestingly, although flupentixol had a modest effect on the immediate response invigoration produced by those rewards, it was particularly potent in countering the lingering enhancement of responding produced by multiple reward deliveries. These findings indicate that dopamine mediates the general incentive motivational effects of noncontingent rewards and reward-paired cues but does not support their ability to bias

  17. Toward a clarification of the taxonomy of "bias" in epidemiology textbooks.

    Science.gov (United States)

    Schwartz, Sharon; Campbell, Ulka B; Gatto, Nicolle M; Gordon, Kirsha

    2015-03-01

    Epidemiology textbooks typically divide biases into 3 general categories-confounding, selection bias, and information bias. Despite the ubiquity of this categorization, authors often use these terms to mean different things. This hinders communication among epidemiologists and confuses students who are just learning about the field. To understand the sources of this problem, we reviewed current general epidemiology textbooks to examine how the authors defined and categorized biases. We found that much of the confusion arises from different definitions of "validity" and from a mixing of 3 overlapping organizational features in defining and differentiating among confounding, selection bias, and information bias: consequence, the result of the problem; cause, the processes that give rise to the problem; and cure, how these biases can be addressed once they occur. By contrast, a consistent taxonomy would provide (1) a clear and consistent definition of what unites confounding, selection bias, and information bias and (2) a clear articulation and consistent application of the feature that distinguishes these categories. Based on a distillation of these textbook discussions, we provide an example of a taxonomy that we think meets these criteria.

  18. Benchmarking by HbA1c in a national diabetes quality register--does measurement bias matter?

    Science.gov (United States)

    Carlsen, Siri; Thue, Geir; Cooper, John Graham; Røraas, Thomas; Gøransson, Lasse Gunnar; Løvaas, Karianne; Sandberg, Sverre

    2015-08-01

    Bias in HbA1c measurement could give a wrong impression of the standard of care when benchmarking diabetes care. The aim of this study was to evaluate how measurement bias in HbA1c results may influence the benchmarking process performed by a national diabetes register. Using data from 2012 from the Norwegian Diabetes Register for Adults, we included HbA1c results from 3584 patients with type 1 diabetes attending 13 hospital clinics, and 1366 patients with type 2 diabetes attending 18 GP offices. Correction factors for HbA1c were obtained by comparing the results of the hospital laboratories'/GP offices' external quality assurance scheme with the target value from a reference method. Compared with the uncorrected yearly median HbA1c values for hospital clinics and GP offices, EQA corrected HbA1c values were within ±0.2% (2 mmol/mol) for all but one hospital clinic whose value was reduced by 0.4% (4 mmol/mol). Three hospital clinics reduced the proportion of patients with poor glycemic control, one by 9% and two by 4%. For most participants in our study, correcting for measurement bias had little effect on the yearly median HbA1c value or the percentage of patients achieving glycemic goals. However, at three hospital clinics correcting for measurement bias had an important effect on HbA1c benchmarking results especially with regard to percentages of patients achieving glycemic targets. The analytical quality of HbA1c should be taken into account when comparing benchmarking results.

  19. Inviting parents to take part in paediatric palliative care research: A mixed-methods examination of selection bias

    OpenAIRE

    Crocker, Joanna C; Beecham, Emma; Kelly, Paula; Dinsdale, Andrew P; Hemsley, June; Jones, Louise; Bluebond-Langner, Myra

    2015-01-01

    Background: Recruitment to paediatric palliative care research is challenging, with high rates of non-invitation of eligible families by clinicians. The impact on sample characteristics is unknown. Aim: To investigate, using mixed methods, non-invitation of eligible families and ensuing selection bias in an interview study about parents? experiences of advance care planning (ACP). Design: We examined differences between eligible families invited and not invited to participate by clinicians us...

  20. A Single Session of Attentional Bias Modification Reduces Alcohol Craving and Implicit Measures of Alcohol Bias in Young Adult Drinkers.

    Science.gov (United States)

    Luehring-Jones, Peter; Louis, Courtney; Dennis-Tiwary, Tracy A; Erblich, Joel

    2017-12-01

    Attentional bias modification (ABM) techniques for reducing problematic alcohol consumption hold promise as highly accessible and cost-effective treatment approaches. A growing body of literature has examined ABM as a potentially efficacious intervention for reducing drinking and drinking-related cognitions in alcohol-dependent individuals as well as those at-risk of developing problem drinking habits. This study tested the effectiveness of a single session of visual probe-based ABM training in a cohort of 60 non-treatment-seeking young adult drinkers, with a focus on examining mechanisms underlying training efficacy. Participants were randomly assigned to a single session of active ABM training or a sham training condition in a laboratory setting. Measures of implicit drinking-related cognitions (alcohol Stroop and an Implicit Association Task) and attentional bias (AB; alcohol visual probe) were administered, and subjective alcohol craving was reported in response to in vivo alcohol cues. Results showed that active ABM training, relative to sham, resulted in significant differences in measures of implicit alcohol-related cognition, alcohol-related AB, and self-reports of alcohol craving. Mediation analysis showed that reductions in craving were fully mediated by ABM-related reductions in alcohol-Stroop interference scores, suggesting a previously undocumented relationship between the 2 measures. Results document the efficacy of brief ABM to reduce both implicit and explicit processes related to drinking, and highlight the potential intervention-relevance of alcohol-related implicit cognitions in social drinkers. Copyright © 2017 by the Research Society on Alcoholism.

  1. Measurement of the Tracer Gradient and Sampling System Bias of the Hot Fuel Examination Facility Stack Air Monitoring System

    Energy Technology Data Exchange (ETDEWEB)

    Glissmeyer, John A.; Flaherty, Julia E.

    2011-07-20

    This report describes tracer gas uniformity and bias measurements made in the exhaust air discharge of the Hot Fuel Examination Facility at Idaho National Laboratory. The measurements were a follow-up on earlier measurements which indicated a lack of mixing of the two ventilation streams being discharged via a common stack. The lack of mixing is detrimental to the accuracy of air emission measurements. The lack of mixing was confirmed in these new measurements. The air sampling probe was found to be out of alignment and that was corrected. The suspected sampling bias in the air sample stream was disproved.

  2. Minimum Bias Trigger Scintillators for ATLAS: Commissioning and Run 2 Initial Operation

    CERN Document Server

    Dano Hoffmann, Maria; The ATLAS collaboration

    2015-01-01

    The Minimum Bias Trigger Scintillators (MBTS) delivered the primary trigger for selecting events from low luminosity proton-proton, lead-lead and lead-proton collisions with the smallest possible bias during LHC Run 1 (2009-2013). Similarly, the MBTS will select events for the first Run 2 physics measurements, for instance charge multiplicity, proton-proton cross section, rapidity gap measurements, etc. at the unprecedented 13 TeV center of mass energy of proton-proton collisions. We will review the upgrades to the MBTS detector that have been implemented during the 2013-2014 shutdown. New scintillators have been installed to replace the radiation damaged ones, a modified optical readout scheme have been adopted to increase the light yield and an improved data acquisition chain has been used to cope with the few issues observed during Run 1 operations. Since late 2014, MBTS have been commissioned during cosmic data taking, first LHC beam splashes and single beam LHC fills. The goal is to have a fully commissi...

  3. The Pictorial Fire Stroop: A Measure of Processing Bias for Fire-Related Stimuli

    Science.gov (United States)

    Gallagher-Duffy, Joanne; MacKay, Sherri; Duffy, Jim; Sullivan-Thomas, Meara; Peterson-Badali, Michele

    2009-01-01

    Fire interest is a risk factor for firesetting. This study tested whether a fire-specific emotional Stroop task can effectively measure an information-processing bias for fire-related stimuli. Clinic-referred and nonreferred adolescents (aged 13-16 years) completed a pictorial "Fire Stroop," as well as a self-report fire interest questionnaire and…

  4. Model selection for marginal regression analysis of longitudinal data with missing observations and covariate measurement error.

    Science.gov (United States)

    Shen, Chung-Wei; Chen, Yi-Hau

    2015-10-01

    Missing observations and covariate measurement error commonly arise in longitudinal data. However, existing methods for model selection in marginal regression analysis of longitudinal data fail to address the potential bias resulting from these issues. To tackle this problem, we propose a new model selection criterion, the Generalized Longitudinal Information Criterion, which is based on an approximately unbiased estimator for the expected quadratic error of a considered marginal model accounting for both data missingness and covariate measurement error. The simulation results reveal that the proposed method performs quite well in the presence of missing data and covariate measurement error. On the contrary, the naive procedures without taking care of such complexity in data may perform quite poorly. The proposed method is applied to data from the Taiwan Longitudinal Study on Aging to assess the relationship of depression with health and social status in the elderly, accommodating measurement error in the covariate as well as missing observations. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Readdressing gender bias in the Coopersmith Self-Esteem Inventory-short form.

    Science.gov (United States)

    Chapman, Paula L; Mullis, Ann K

    2002-12-01

    The short form of the Coopersmith Self-Esteem Inventory (SEI) was evaluated for gender bias. The authors replicated a study by L. Francis and D. James (1998) and administered the SEI to 361 middle and high school students (146 boys, 2l5 girls). They found that gender bias existed in 6 of the 25 items on the SEI, with 5 of those items favoring boys. Because recent literature indicates that male and female adolescents experience problems in different areas of their lives, the authors suggest that researchers consider such differences when selecting items for a standardized measure.

  6. Contamination effects on fixed-bias Langmuir probes

    Energy Technology Data Exchange (ETDEWEB)

    Steigies, C. T. [Institut fuer Experimentelle und Angewandte Physik, Christian-Albrechts-Universitaet zu Kiel, 24098 Kiel (Germany); Barjatya, A. [Department of Physical Sciences, Embry-Riddle Aeronautical University, Daytona Beach, Florida 32114 (United States)

    2012-11-15

    Langmuir probes are standard instruments for plasma density measurements on many sounding rockets. These probes can be operated in swept-bias as well as in fixed-bias modes. In swept-bias Langmuir probes, contamination effects are frequently visible as a hysteresis between consecutive up and down voltage ramps. This hysteresis, if not corrected, leads to poorly determined plasma densities and temperatures. With a properly chosen sweep function, the contamination parameters can be determined from the measurements and correct plasma parameters can then be determined. In this paper, we study the contamination effects on fixed-bias Langmuir probes, where no hysteresis type effect is seen in the data. Even though the contamination is not evident from the measurements, it does affect the plasma density fluctuation spectrum as measured by the fixed-bias Langmuir probe. We model the contamination as a simple resistor-capacitor circuit between the probe surface and the plasma. We find that measurements of small scale plasma fluctuations (meter to sub-meter scale) along a rocket trajectory are not affected, but the measured amplitude of large scale plasma density variation (tens of meters or larger) is attenuated. From the model calculations, we determine amplitude and cross-over frequency of the contamination effect on fixed-bias probes for different contamination parameters. The model results also show that a fixed bias probe operating in the ion-saturation region is affected less by contamination as compared to a fixed bias probe operating in the electron saturation region.

  7. Bias in the Listeria monocytogenes enrichment procedure: Lineage 2 strains outcompete lineage 1 strains in University of Vermont selective enrichments

    DEFF Research Database (Denmark)

    Bruhn, Jesper Bartholin; Vogel, Birte Fonnesbech; Gram, Lone

    2005-01-01

    compounds in UVM I and II influenced this bias. The results of the present study demonstrate that the selective procedures used for isolation of L. monocytogenes may not allow a true representation of the types present in foods. Our results could have a significant impact on epidemiological studies...

  8. Reflecting Equity and Diversity. Part I: Guidelines and Procedure for Evaluating Bias in Instructional Materials. Part II: Bias Awareness Training Worksheets. Part III: Bias Awareness and Procedure Training Course.

    Science.gov (United States)

    Bebermeyer, Jim; Edmond, Mary, Ed.

    Reflecting a need to prepare students for working in diverse organizations, this document was developed to increase school officials' awareness of bias in instructional materials and help them select bias-free materials. A number of the examples illustrate situations dealing with diversity in the workplace. The guide is divided into three parts:…

  9. Sexual selection on male size drives the evolution of male-biased sexual size dimorphism via the prolongation of male development.

    Science.gov (United States)

    Rohner, Patrick T; Blanckenhorn, Wolf U; Puniamoorthy, Nalini

    2016-06-01

    Sexual size dimorphism (SSD) arises when the net effects of natural and sexual selection on body size differ between the sexes. Quantitative SSD variation between taxa is common, but directional intraspecific SSD reversals are rare. We combined micro- and macroevolutionary approaches to study geographic SSD variation in closely related black scavenger flies. Common garden experiments revealed stark intra- and interspecific variation: Sepsis biflexuosa is monomorphic across the Holarctic, while S. cynipsea (only in Europe) consistently exhibits female-biased SSD. Interestingly, S. neocynipsea displays contrasting SSD in Europe (females larger) and North America (males larger), a pattern opposite to the geographic reversal in SSD of S. punctum documented in a previous study. In accordance with the differential equilibrium model for the evolution of SSD, the intensity of sexual selection on male size varied between continents (weaker in Europe), whereas fecundity selection on female body size did not. Subsequent comparative analyses of 49 taxa documented at least six independent origins of male-biased SSD in Sepsidae, which is likely caused by sexual selection on male size and mediated by bimaturism. Therefore, reversals in SSD and the associated changes in larval development might be much more common and rapid and less constrained than currently assumed. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

  10. PREVALENCE OF CHRONIC DISEASES IN INDIVIDUALS ASSISTED BY THE FAMILY HEALTH PROGRAM IN NITEROI, BRAZIL: EVALUATION OF SELECTION BIAS AND PROTOCOL

    Directory of Open Access Journals (Sweden)

    Rosa Maria Luiza G, Mesquita Evandro T, Jorge Antonio José L, Correia Dayse MS, Lugon Josemir R, Kang HC, Yokoo EM, Wahrlich V

    2015-07-01

    Full Text Available Background: The strategy of the Family Health Program has been used as an alternative scenario for prevalence studies. This study intended to present the protocol of the Digitalis Study (DS, prevalence study of chronic diseases, to assess sources of possible selection bias and estimate their impact on the prevalence of self-reported hypertension, diabetes, and myocardial infarction. Methods: Randomization was performed between 38 160 registered individuals with 45 to 99 years by the Family Health Program .Differences between the sources of selection bias (non-acceptance, non-attendance, substitutions were observed for gender and age. Results: Of the 1,190 residents contacted, 67.1% agreed to participate. There were 144 residents who were not randomly selected but whose participation was confirmed (substitutes. Women and individuals in the intermediate age groups and the prevalence of hypertension were higher among substitutes compared with the randomly selected individuals. Conclusion: The approach of the DS was adequate for the purposes of estimating prevalences, but there was a significant percentage of non-participation. The randomization strategy did not assume outdated records; alternative schedules for visits were not provided for; follow-up at the invitation stage was not sufficient to prevent substitutions and the inclusion of substitutes with a higher prevalence of hypertension.

  11. Work required for selective quantum measurement

    Science.gov (United States)

    Konishi, Eiji

    2018-06-01

    In quantum mechanics, we define the measuring system M in a selective measurement by two conditions. Firstly, when we define the measured system S as the system in which the non-selective measurement part acts, M is independent from the measured system S as a quantum system in the sense that any time-dependent process in the total system S  +  M is divisible into parts for S and M. Secondly, when we can separate S and M from each other without changing the unitary equivalence class of the state of S from that obtained by the partial trace of M, the eigenstate selection in the selective measurement cannot be realized. In order for such a system M to exist, we show that in one selective measurement of an observable of a quantum system S 0 of particles in S, there exists a negative entropy transfer from M to S that can be directly transformed into an amount of Helmholtz free energy of where T is the thermodynamic temperature of the system S. Equivalently, an extra amount of work, , is required to be done by the system M.

  12. Bias in tensor based morphometry Stat-ROI measures may result in unrealistic power estimates.

    Science.gov (United States)

    Thompson, Wesley K; Holland, Dominic

    2011-07-01

    A series of reports have recently appeared using tensor based morphometry statistically-defined regions of interest, Stat-ROIs, to quantify longitudinal atrophy in structural MRIs from the Alzheimer's Disease Neuroimaging Initiative (ADNI). This commentary focuses on one of these reports, Hua et al. (2010), but the issues raised here are relevant to the others as well. Specifically, we point out a temporal pattern of atrophy in subjects with Alzheimer's disease and mild cognitive impairment whereby the majority of atrophy in two years occurs within the first 6 months, resulting in overall elevated estimated rates of change. Using publicly-available ADNI data, this temporal pattern is also found in a group of identically-processed healthy controls, strongly suggesting that methodological bias is corrupting the measures. The resulting bias seriously impacts the validity of conclusions reached using these measures; for example, sample size estimates reported by Hua et al. (2010) may be underestimated by a factor of five to sixteen. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Media bias and advertising: Evidence from a German car magazine

    OpenAIRE

    Dewenter, Ralf; Heimeshoff, Ulrich

    2014-01-01

    This paper investigates the existence of a possible media bias by analyzing the impact of auto- mobile manufacturer’s advertisements on automobile reviews in a leading German car maga- zine. By accounting for both endogeneity and sample selection using a two-step procedure, we find a positive impact of advertising volumes on test scores. The main advantage of our study is the measurement of technical characteristics of cars to explain test scores. Due to this kind of measurement, we avoid ser...

  14. The Accuracy and Bias of Single-Step Genomic Prediction for Populations Under Selection

    Directory of Open Access Journals (Sweden)

    Wan-Ling Hsu

    2017-08-01

    Full Text Available In single-step analyses, missing genotypes are explicitly or implicitly imputed, and this requires centering the observed genotypes using the means of the unselected founders. If genotypes are only available for selected individuals, centering on the unselected founder mean is not straightforward. Here, computer simulation is used to study an alternative analysis that does not require centering genotypes but fits the mean μg of unselected individuals as a fixed effect. Starting with observed diplotypes from 721 cattle, a five-generation population was simulated with sire selection to produce 40,000 individuals with phenotypes, of which the 1000 sires had genotypes. The next generation of 8000 genotyped individuals was used for validation. Evaluations were undertaken with (J or without (N μg when marker covariates were not centered; and with (JC or without (C μg when all observed and imputed marker covariates were centered. Centering did not influence accuracy of genomic prediction, but fitting μg did. Accuracies were improved when the panel comprised only quantitative trait loci (QTL; models JC and J had accuracies of 99.4%, whereas models C and N had accuracies of 90.2%. When only markers were in the panel, the 4 models had accuracies of 80.4%. In panels that included QTL, fitting μg in the model improved accuracy, but had little impact when the panel contained only markers. In populations undergoing selection, fitting μg in the model is recommended to avoid bias and reduction in prediction accuracy due to selection.

  15. Removing Visual Bias in Filament Identification: A New Goodness-of-fit Measure

    Science.gov (United States)

    Green, C.-E.; Cunningham, M. R.; Dawson, J. R.; Jones, P. A.; Novak, G.; Fissel, L. M.

    2017-05-01

    Different combinations of input parameters to filament identification algorithms, such as disperse and filfinder, produce numerous different output skeletons. The skeletons are a one-pixel-wide representation of the filamentary structure in the original input image. However, these output skeletons may not necessarily be a good representation of that structure. Furthermore, a given skeleton may not be as good of a representation as another. Previously, there has been no mathematical “goodness-of-fit” measure to compare output skeletons to the input image. Thus far this has been assessed visually, introducing visual bias. We propose the application of the mean structural similarity index (MSSIM) as a mathematical goodness-of-fit measure. We describe the use of the MSSIM to find the output skeletons that are the most mathematically similar to the original input image (the optimum, or “best,” skeletons) for a given algorithm, and independently of the algorithm. This measure makes possible systematic parameter studies, aimed at finding the subset of input parameter values returning optimum skeletons. It can also be applied to the output of non-skeleton-based filament identification algorithms, such as the Hessian matrix method. The MSSIM removes the need to visually examine thousands of output skeletons, and eliminates the visual bias, subjectivity, and limited reproducibility inherent in that process, representing a major improvement upon existing techniques. Importantly, it also allows further automation in the post-processing of output skeletons, which is crucial in this era of “big data.”

  16. Bias due to sample selection in propensity score matching for a supportive housing program evaluation in New York City.

    Directory of Open Access Journals (Sweden)

    Sungwoo Lim

    Full Text Available OBJECTIVES: Little is known about influences of sample selection on estimation in propensity score matching. The purpose of the study was to assess potential selection bias using one-to-one greedy matching versus optimal full matching as part of an evaluation of supportive housing in New York City (NYC. STUDY DESIGN AND SETTINGS: Data came from administrative data for 2 groups of applicants who were eligible for an NYC supportive housing program in 2007-09, including chronically homeless adults with a substance use disorder and young adults aging out of foster care. We evaluated the 2 matching methods in their ability to balance covariates and represent the original population, and in how those methods affected outcomes related to Medicaid expenditures. RESULTS: In the population with a substance use disorder, only optimal full matching performed well in balancing covariates, whereas both methods created representative populations. In the young adult population, both methods balanced covariates effectively, but only optimal full matching created representative populations. In the young adult population, the impact of the program on Medicaid expenditures was attenuated when one-to-one greedy matching was used, compared with optimal full matching. CONCLUSION: Given covariate balancing with both methods, attenuated program impacts in the young adult population indicated that one-to-one greedy matching introduced selection bias.

  17. Sources of Response Bias in Older Ethnic Minorities: A Case of Korean American Elderly

    Science.gov (United States)

    Kim, Miyong T.; Ko, Jisook; Yoon, Hyunwoo; Kim, Kim B.; Jang, Yuri

    2015-01-01

    The present study was undertaken to investigate potential sources of response bias in empirical research involving older ethnic minorities and to identify prudent strategies to reduce those biases, using Korean American elderly (KAE) as an example. Data were obtained from three independent studies of KAE (N=1,297; age ≥60) in three states (Florida, New York, and Maryland) from 2000 to 2008. Two common measures, Pearlin’s Mastery Scale and the CES-D scale, were selected for a series of psychometric tests based on classical measurement theory. Survey items were analyzed in depth, using psychometric properties generated from both exploratory factor analysis and confirmatory factor analysis as well as correlational analysis. Two types of potential sources of bias were identified as the most significant contributors to increases in error variances for these psychological instruments. Error variances were most prominent when (1) items were not presented in a manner that was culturally or contextually congruent with respect to the target population and/or (2) the response anchors for items were mixed (e.g., positive vs. negative). The systemic patterns and magnitudes of the biases were also cross-validated for the three studies. The results demonstrate sources and impacts of measurement biases in studies of older ethnic minorities. The identified response biases highlight the need for re-evaluation of current measurement practices, which are based on traditional recommendations that response anchors should be mixed or that the original wording of instruments should be rigidly followed. Specifically, systematic guidelines for accommodating cultural and contextual backgrounds into instrument design are warranted. PMID:26049971

  18. Bias correction by use of errors-in-variables regression models in studies with K-X-ray fluorescence bone lead measurements.

    Science.gov (United States)

    Lamadrid-Figueroa, Héctor; Téllez-Rojo, Martha M; Angeles, Gustavo; Hernández-Ávila, Mauricio; Hu, Howard

    2011-01-01

    In-vivo measurement of bone lead by means of K-X-ray fluorescence (KXRF) is the preferred biological marker of chronic exposure to lead. Unfortunately, considerable measurement error associated with KXRF estimations can introduce bias in estimates of the effect of bone lead when this variable is included as the exposure in a regression model. Estimates of uncertainty reported by the KXRF instrument reflect the variance of the measurement error and, although they can be used to correct the measurement error bias, they are seldom used in epidemiological statistical analyzes. Errors-in-variables regression (EIV) allows for correction of bias caused by measurement error in predictor variables, based on the knowledge of the reliability of such variables. The authors propose a way to obtain reliability coefficients for bone lead measurements from uncertainty data reported by the KXRF instrument and compare, by the use of Monte Carlo simulations, results obtained using EIV regression models vs. those obtained by the standard procedures. Results of the simulations show that Ordinary Least Square (OLS) regression models provide severely biased estimates of effect, and that EIV provides nearly unbiased estimates. Although EIV effect estimates are more imprecise, their mean squared error is much smaller than that of OLS estimates. In conclusion, EIV is a better alternative than OLS to estimate the effect of bone lead when measured by KXRF. Copyright © 2010 Elsevier Inc. All rights reserved.

  19. Personality Traits and Susceptibility to Behavioral Biases among a Sample of Polish Stock Market Investors

    Directory of Open Access Journals (Sweden)

    Rzeszutek Marcin

    2015-09-01

    Full Text Available The aim of this paper is to investigate whether susceptibility to selected behavioral biases (overconfidence, mental accounting and sunk-cost fallacy is correlated with the Eysenck’s [1978] personality traits (impulsivity, venturesomeness, and empathy. This study was conducted on a sample of 90 retail investors frequently investing on the Warsaw Stock Exchange. Participants filled out a survey made up of two parts: 1 three situational exercises, which assessed susceptibility to behavioral biases and 2 an Impulsiveness Questionnaire, which measures impulsivity, venturesomeness, and empathy. The results demonstrated the relationship between venturesomeness and susceptibility to all behavioral biases explored in this study. We find that higher level of venturesomeness was linked with a lower probability of all behavioral biases included in this study.

  20. Bias against research on gender bias.

    Science.gov (United States)

    Cislak, Aleksandra; Formanowicz, Magdalena; Saguy, Tamar

    2018-01-01

    The bias against women in academia is a documented phenomenon that has had detrimental consequences, not only for women, but also for the quality of science. First, gender bias in academia affects female scientists, resulting in their underrepresentation in academic institutions, particularly in higher ranks. The second type of gender bias in science relates to some findings applying only to male participants, which produces biased knowledge. Here, we identify a third potentially powerful source of gender bias in academia: the bias against research on gender bias. In a bibliometric investigation covering a broad range of social sciences, we analyzed published articles on gender bias and race bias and established that articles on gender bias are funded less often and published in journals with a lower Impact Factor than articles on comparable instances of social discrimination. This result suggests the possibility of an underappreciation of the phenomenon of gender bias and related research within the academic community. Addressing this meta-bias is crucial for the further examination of gender inequality, which severely affects many women across the world.

  1. Does neurocognitive function affect cognitive bias toward an emotional stimulus? Association between general attentional ability and attentional bias toward threat

    Directory of Open Access Journals (Sweden)

    Yuko eHakamata

    2014-08-01

    Full Text Available Background: Although poorer cognitive performance has been found to be associated with anxiety, it remains unclear whether neurocognitive function affects biased cognitive processing toward emotional information. We investigated whether general cognitive function evaluated with a standard neuropsychological test predicts biased cognition, focusing on attentional bias toward threat.Methods: One hundred and five healthy young adults completed a dot-probe task measuring attentional bias and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS measuring general cognitive function, which consists of five domains: immediate memory, visuospatial/constructional, language, attention, and delayed memory. Stepwise multiple regression analysis was performed to examine the relationships between attentional bias and cognitive function. Results: The attentional domain was the best predictor of attentional bias toward threat (β = -0.26, p = 0.006. Within the attentional domain, digit symbol coding was negatively correlated with attentional bias (r = -0.28, p = 0.005.Conclusions: The present study provides the first evidence that general attentional ability, which was assessed with a standard neuropsychological test, affects attentional bias toward threatening information. Individual cognitive profiles might be important for the measurement and modification of cognitive biases.

  2. Measurements of the asymmetric dynamic sheath around a pulse biased sphere immersed in flowing metal plasma

    Science.gov (United States)

    Wu, Hongchen; Anders, André

    2008-08-01

    A long-probe technique was utilized to record the expansion and retreat of the dynamic sheath around a spherical substrate immersed in pulsed cathode arc metal plasma. Positively biased, long cylindrical probes were placed on the side and downstream of a negatively pulsed biased stainless steel sphere of 1 in. (25.4 mm) diameter. The amplitude and width of the negative high voltage pulses (HVPs) were 2 kV, 5 kV, 10 kV, and 2 µs, 4 µs, 10 µs, respectively. The variation of the probe (electron) current during the HVP is a direct measure for the sheath expansion and retreat. Maximum sheath sizes were determined for the different parameters of the HVP. The expected rarefaction zone behind the biased sphere (wake) due to the fast plasma flow was clearly established and quantified.

  3. Unreliability as a Threat to Understanding Psychopathology: The Cautionary Tale of Attentional Bias

    Science.gov (United States)

    Rodebaugh, Thomas L.; Scullin, Rachel B.; Langer, Julia K.; Dixon, David J.; Huppert, Jonathan D.; Bernstein, Amit; Zvielli, Ariel; Lenze, Eric J.

    2016-01-01

    The use of unreliable measures constitutes a threat to our understanding of psychopathology, because advancement of science using both behavioral and biologically-oriented measures can only be certain if such measurements are reliable. Two pillars of NIMH’s portfolio – the Research Domain Criteria (RDoC) initiative for psychopathology and the target engagement initiative in clinical trials – cannot succeed without measures that possess the high reliability necessary for tests involving mediation and selection based on individual differences. We focus on the historical lack of reliability of attentional bias measures as an illustration of how reliability can pose a threat to our understanding. Our own data replicate previous findings of poor reliability for traditionally-used scores, which suggests a serious problem with the ability to test theories regarding attentional bias. This lack of reliability may also suggest problems with the assumption (in both theory and the formula for the scores) that attentional bias is consistent and stable across time. In contrast, measures accounting for attention as a dynamic process in time show good reliability in our data. The field is sorely in need of research reporting findings and reliability for attentional bias scores using multiple methods, including those focusing on dynamic processes over time. We urge researchers to test and report reliability of all measures, considering findings of low reliability not just as a nuisance but as an opportunity to modify and improve upon the underlying theory. Full assessment of reliability of measures will maximize the possibility that RDoC (and psychological science more generally) will succeed. PMID:27322741

  4. Latest Minimum Bias and Underlying Event Measurements at ATLAS

    CERN Document Server

    Kar, Deepak; The ATLAS collaboration

    2017-01-01

    While the modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes, the studies of the Underlying Event (UE) shed light on the description of both soft and hard QCD processes at hadron colliders. The ATLAS collaboration has provided measurements of the inclusive charged-particle multiplicity and its dependence on transverse momentum and pseudorapidity in special data sets with low LHC beam currents, recorded at center-of-mass energies of 8 TeV and 13 TeV. Moreover, results on the number and transverse-momentum sum of charged particles as a function of the leading high pT track in events taken at a center-of-mass energy of 13 TeV are presented. These results are separated in the towards, transverse, and away from the leading track and allow to test the modelling of the Underlying Event in modern MC generators. Furthermore, event-shape variables based on charged particles have been measured in Z-events and have been compared with the predictions of different st...

  5. Quasi-experimental study designs series-paper 6: risk of bias assessment.

    Science.gov (United States)

    Waddington, Hugh; Aloe, Ariel M; Becker, Betsy Jane; Djimeu, Eric W; Hombrados, Jorge Garcia; Tugwell, Peter; Wells, George; Reeves, Barney

    2017-09-01

    Rigorous and transparent bias assessment is a core component of high-quality systematic reviews. We assess modifications to existing risk of bias approaches to incorporate rigorous quasi-experimental approaches with selection on unobservables. These are nonrandomized studies using design-based approaches to control for unobservable sources of confounding such as difference studies, instrumental variables, interrupted time series, natural experiments, and regression-discontinuity designs. We review existing risk of bias tools. Drawing on these tools, we present domains of bias and suggest directions for evaluation questions. The review suggests that existing risk of bias tools provide, to different degrees, incomplete transparent criteria to assess the validity of these designs. The paper then presents an approach to evaluating the internal validity of quasi-experiments with selection on unobservables. We conclude that tools for nonrandomized studies of interventions need to be further developed to incorporate evaluation questions for quasi-experiments with selection on unobservables. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Bias by default? A means for a priori interface measurement

    Energy Technology Data Exchange (ETDEWEB)

    Cottam, Joseph A.; Blaha, Leslie M.

    2017-10-03

    Systems have biases. Their interfaces naturally guide a user toward specific patterns of action. For example, modern word-processors and spreadsheets are both capable of taking word wrapping, checking spelling, storing tables, and calculating formulas. You could write a paper in a spreadsheet or could do simple business modeling in a word-processor. However, their interfaces naturally communicate which function they are designed for. Visual analytic interfaces also have biases. In this paper, we outline why simple Markov models are a plausible tool for investigating that bias and how they might be applied. We also discuss some anticipated difficulties in such modeling and touch briefly on what some Markov model extensions might provide.

  7. Attention processes in chronic fatigue syndrome: attentional bias for health-related threat and the role of attentional control.

    Science.gov (United States)

    Hou, Ruihua; Moss-Morris, Rona; Risdale, Anna; Lynch, Jeannette; Jeevaratnam, Preshan; Bradley, Brendan P; Mogg, Karin

    2014-01-01

    Cognitive behavioural models of chronic fatigue syndrome (CFS) propose that attention processes, specifically, enhanced selective attention to health-threat related cues, may play an important role in symptom maintenance. The current study investigated attentional bias towards health-threat stimuli in CFS. It also examined whether individuals with CFS have impaired executive attention, and whether this was related to attentional bias. 27 participants with CFS and 35 healthy controls completed a Visual Probe Task measuring attentional bias, and an Attention Network Test measuring executive attention, alerting and orienting. Participants also completed self-report measures of CFS and mood symptoms. Compared to the control group, the CFS group showed greater attentional bias for health-threat words than pictures; and the CFS group was significantly impaired in executive attention. Furthermore, CFS individuals with poor executive attention showed greater attentional bias to health-threat related words, compared not only to controls but also to CFS individuals with good executive attention. Thus, this study revealed a significant relationship between attentional bias and executive attention in CFS: attentional bias to threat was primarily evident in those with impaired executive attention control. Taking account of individual differences in executive attention control in current intervention models may be beneficial for CFS. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Dwalingen in de methodologie. II. Bias door vragenlijsten

    DEFF Research Database (Denmark)

    Pouwer, F; Van Der Ploeg, Henk M; Bramsen, I

    1998-01-01

    Some characteristics of self-report questionnaires can result in bias in responding. When a test item or a questionnaire is biased, the observed scores form an imprecise measurement of reality as a consequence of systematic errors of measurement. Causes of such bias are: unclear instructions, vague...

  9. Beyond assembly bias: exploring secondary halo biases for cluster-size haloes

    Science.gov (United States)

    Mao, Yao-Yuan; Zentner, Andrew R.; Wechsler, Risa H.

    2018-03-01

    Secondary halo bias, commonly known as `assembly bias', is the dependence of halo clustering on a halo property other than mass. This prediction of the Λ Cold Dark Matter cosmology is essential to modelling the galaxy distribution to high precision and interpreting clustering measurements. As the name suggests, different manifestations of secondary halo bias have been thought to originate from halo assembly histories. We show conclusively that this is incorrect for cluster-size haloes. We present an up-to-date summary of secondary halo biases of high-mass haloes due to various halo properties including concentration, spin, several proxies of assembly history, and subhalo properties. While concentration, spin, and the abundance and radial distribution of subhaloes exhibit significant secondary biases, properties that directly quantify halo assembly history do not. In fact, the entire assembly histories of haloes in pairs are nearly identical to those of isolated haloes. In general, a global correlation between two halo properties does not predict whether or not these two properties exhibit similar secondary biases. For example, assembly history and concentration (or subhalo abundance) are correlated for both paired and isolated haloes, but follow slightly different conditional distributions in these two cases. This results in a secondary halo bias due to concentration (or subhalo abundance), despite the lack of assembly bias in the strict sense for cluster-size haloes. Due to this complexity, caution must be exercised in using any one halo property as a proxy to study the secondary bias due to another property.

  10. Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

    Science.gov (United States)

    Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

    2018-07-01

    Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

  11. Selective forces and mutational biases drive stop codon usage in the human genome: a comparison with sense codon usage.

    Science.gov (United States)

    Trotta, Edoardo

    2016-05-17

    The three stop codons UAA, UAG, and UGA signal the termination of mRNA translation. As a result of a mechanism that is not adequately understood, they are normally used with unequal frequencies. In this work, we showed that selective forces and mutational biases drive stop codon usage in the human genome. We found that, in respect to sense codons, stop codon usage was affected by stronger selective forces but was less influenced by neutral mutational biases. UGA is the most frequent termination codon in human genome. However, UAA was the preferred stop codon in genes with high breadth of expression, high level of expression, AT-rich coding sequences, housekeeping functions, and in gene ontology categories with the largest deviation from expected stop codon usage. Selective forces associated with the breadth and the level of expression favoured AT-rich sequences in the mRNA region including the stop site and its proximal 3'-UTR, but acted with scarce effects on sense codons, generating two regions, upstream and downstream of the stop codon, with strongly different base composition. By favouring low levels of GC-content, selection promoted labile local secondary structures at the stop site and its proximal 3'-UTR. The compositional and structural context favoured by selection was surprisingly emphasized in the class of ribosomal proteins and was consistent with sequence elements that increase the efficiency of translational termination. Stop codons were also heterogeneously distributed among chromosomes by a mechanism that was strongly correlated with the GC-content of coding sequences. In human genome, the nucleotide composition and the thermodynamic stability of stop codon site and its proximal 3'-UTR are correlated with the GC-content of coding sequences and with the breadth and the level of gene expression. In highly expressed genes stop codon usage is compositionally and structurally consistent with highly efficient translation termination signals.

  12. Measurements of the asymmetric dynamic sheath around a pulse biased sphere immersed in flowing metal plasma

    International Nuclear Information System (INIS)

    Wu Hongchen; Anders, Andre

    2008-01-01

    A long-probe technique was utilized to record the expansion and retreat of the dynamic sheath around a spherical substrate immersed in pulsed cathode arc metal plasma. Positively biased, long cylindrical probes were placed on the side and downstream of a negatively pulsed biased stainless steel sphere of 1 in. (25.4 mm) diameter. The amplitude and width of the negative high voltage pulses (HVPs) were 2 kV, 5 kV, 10 kV, and 2 μs, 4 μs, 10 μs, respectively. The variation of the probe (electron) current during the HVP is a direct measure for the sheath expansion and retreat. Maximum sheath sizes were determined for the different parameters of the HVP. The expected rarefaction zone behind the biased sphere (wake) due to the fast plasma flow was clearly established and quantified.

  13. Direct measurement of the charge distribution along a biased carbon nanotube bundle using electron holography

    DEFF Research Database (Denmark)

    Beleggia, Marco; Kasama, Takeshi; Dunin-Borkowski, Rafal E.

    2011-01-01

    Nanowires and nanotubes can be examined in the transmission electron microscope under an applied bias. Here we introduce a model-independent method, which allows the charge distribution along a nanowire or nanotube to be measured directly from the Laplacian of an electron holographic phase image....

  14. Measurement invariance versus selection invariance: Is fair selection possible?

    NARCIS (Netherlands)

    Borsboom, D.; Romeijn, J.W.; Wicherts, J.M.

    2008-01-01

    This article shows that measurement invariance (defined in terms of an invariant measurement model in different groups) is generally inconsistent with selection invariance (defined in terms of equal sensitivity and specificity across groups). In particular, when a unidimensional measurement

  15. Measurement invariance versus selection invariance : Is fair selection possible?

    NARCIS (Netherlands)

    Borsboom, Denny; Romeijn, Jan-Willem; Wicherts, Jelte M.

    This article shows that measurement invariance (defined in terms of an invariant measurement model in different groups) is generally inconsistent with selection invariance (defined in terms of equal sensitivity and specificity across groups). In particular, when a unidimensional measurement

  16. A model-based correction for outcome reporting bias in meta-analysis.

    Science.gov (United States)

    Copas, John; Dwan, Kerry; Kirkham, Jamie; Williamson, Paula

    2014-04-01

    It is often suspected (or known) that outcomes published in medical trials are selectively reported. A systematic review for a particular outcome of interest can only include studies where that outcome was reported and so may omit, for example, a study that has considered several outcome measures but only reports those giving significant results. Using the methodology of the Outcome Reporting Bias (ORB) in Trials study of (Kirkham and others, 2010. The impact of outcome reporting bias in randomised controlled trials on a cohort of systematic reviews. British Medical Journal 340, c365), we suggest a likelihood-based model for estimating the effect of ORB on confidence intervals and p-values in meta-analysis. Correcting for bias has the effect of moving estimated treatment effects toward the null and hence more cautious assessments of significance. The bias can be very substantial, sometimes sufficient to completely overturn previous claims of significance. We re-analyze two contrasting examples, and derive a simple fixed effects approximation that can be used to give an initial estimate of the effect of ORB in practice.

  17. Active and Adaptive Learning from Biased Data with Applications in Astronomy

    DEFF Research Database (Denmark)

    Kremer, Jan

    This thesis addresses the problem of machine learning from biased datasets in the context of astronomical applications. In astronomy there are many cases in which the training sample does not follow the true distribution. The thesis examines different types of biases and proposes algorithms...... set. Against this background, the thesis begins with a survey of active learning algorithms for the support vector machine. If the cost of additional labeling is prohibitive, unlabeled data can often be utilized instead and the sample selection bias can be overcome through domain adaptation, that is...... to handle them. During learning and when applying the predictive model, active learning enables algorithms to select training examples from a pool of unlabeled data and to request the labels. This allows for selecting examples that maximize the algorithm's accuracy despite an initial bias in the training...

  18. Looking on the bright side: biased attention and the human serotonin transporter gene.

    Science.gov (United States)

    Fox, Elaine; Ridgewell, Anna; Ashwin, Chris

    2009-05-22

    Humans differ in terms of biased attention for emotional stimuli and these biases can confer differential resilience and vulnerability to emotional disorders. Selective processing of positive emotional information, for example, is associated with enhanced sociability and well-being while a bias for negative material is associated with neuroticism and anxiety. A tendency to selectively avoid negative material might also be associated with mental health and well-being. The neurobiological mechanisms underlying these cognitive phenotypes are currently unknown. Here we show for the first time that allelic variation in the promotor region of the serotonin transporter gene (5-HTTLPR) is associated with differential biases for positive and negative affective pictures. Individuals homozygous for the long allele (LL) showed a marked bias to selectively process positive affective material alongside selective avoidance of negative affective material. This potentially protective pattern was absent among individuals carrying the short allele (S or SL). Thus, allelic variation on a common genetic polymorphism was associated with the tendency to selectively process positive or negative information. The current study is important in demonstrating a genotype-related alteration in a well-established processing bias, which is a known risk factor in determining both resilience and vulnerability to emotional disorders.

  19. The personal interview: assessing the potential for personality similarity to bias the selection of orthopaedic residents.

    Science.gov (United States)

    Quintero, Andres J; Segal, Lee S; King, Tonya S; Black, Kevin P

    2009-10-01

    The selection of medical students for training in orthopaedic surgery consists of an objective screening of cognitive skills to secure interviews for the brightest candidates, followed by subjective measures of candidates to confirm whether applicants are worthy of further consideration. The personal interview and its potential biased impact on the orthopaedic workforce were evaluated. During 2004-2006 at the Penn State College of Medicine, the authors performed a prospective cohort study in which 30 consenting interviewers and 135 interviewees completed the Myers-Briggs Type Indicator before the interviews. Completed surveys were evaluated after submitting the resident selection list to the National Residency Matching Program, and candidate rankings based solely on the personal interview were analyzed. Clinicians ranked candidates more favorably when they shared certain personality preferences (P = .044) and when they shared the preference groupings of the quadrant extrovert-sensing and either the function pair sensing-thinking (P = .007) or the temperament sensing-judging (P = .003), or the function pair sensing-feeling and the temperament sensing-judging (P = .029). No associations existed between personality preferences and interviewee rankings performed by basic scientists and resident interviewers. The results support the hypothesis that, within the department studied, there was a significant association between similarities in personality type and the rankings that individual faculty interviewers assigned to applicants at the completion of each interview session. The authors believe that it is important for the faculty member to recognize that this tendency exists. Finally, promoting diversity within the admission committee may foster a diverse resident body and orthopaedic workforce.

  20. Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 2. Biases and homogenization

    Science.gov (United States)

    Kennedy, J. J.; Rayner, N. A.; Smith, R. O.; Parker, D. E.; Saunby, M.

    2011-07-01

    Changes in instrumentation and data availability have caused time-varying biases in estimates of global and regional average sea surface temperature. The size of the biases arising from these changes are estimated and their uncertainties evaluated. The estimated biases and their associated uncertainties are largest during the period immediately following the Second World War, reflecting the rapid and incompletely documented changes in shipping and data availability at the time. Adjustments have been applied to reduce these effects in gridded data sets of sea surface temperature and the results are presented as a set of interchangeable realizations. Uncertainties of estimated trends in global and regional average sea surface temperature due to bias adjustments since the Second World War are found to be larger than uncertainties arising from the choice of analysis technique, indicating that this is an important source of uncertainty in analyses of historical sea surface temperatures. Despite this, trends over the twentieth century remain qualitatively consistent.

  1. Girl child and gender bias.

    Science.gov (United States)

    Chowdhry, D P

    1995-01-01

    This article identifies gender bias against female children and youth in India. Gender bias is based on centuries-old religious beliefs and sayings from ancient times. Discrimination is reflected in denial or ignorance of female children's educational, health, nutrition, and recreational needs. Female infanticide and selective abortion of female fetuses are other forms of discrimination. The task of eliminating or reducing gender bias will involve legal, developmental, political, and administrative measures. Public awareness needs to be created. There is a need to reorient the education and health systems and to advocate for gender equality. The government of India set the following goals for the 1990s: to protect the survival of the girl child and practice safe motherhood; to develop the girl child in general; and to protect vulnerable girl children in different circumstances and in special groups. The Health Authorities should monitor the laws carefully to assure marriage after the minimum age, ban sex determination of the fetus, and monitor the health and nutrition of pre-school girls and nursing and pregnant mothers. Mothers need to be encouraged to breast feed, and to breast feed equally between genders. Every village and slum area needs a mini health center. Maternal mortality must decline. Primary health centers and hospitals need more women's wards. Education must be universally accessible. Enrollments should be increased by educating rural tribal and slum parents, reducing distances between home and school, making curriculum more relevant to girls, creating more female teachers, and providing facilities and incentives for meeting the needs of girl students. Supplementary income could be provided to families for sending girls to school. Recreational activities must be free of gender bias. Dowry, sati, and devdasi systems should be banned.

  2. Simulation of HPIB propagation in biased charge collector

    International Nuclear Information System (INIS)

    Li Hongyu; Qiu Aici

    2004-01-01

    A 2.5D PIC simulation using KARAT code for inner charge propagation within biased charge collector for measuring HPIB is presented. The simulation results indicate that the charges were neutralized but the current non-neutralized in the biased charge collector. The influence of ions collected vs biased voltage of the collector was also simulated. -800 V biased voltage can meet the measurement of 500 keV HPIB, and this is consistent with the experimental results

  3. Worry or craving? A selective review of evidence for food-related attention biases in obese individuals, eating-disorder patients, restrained eaters and healthy samples.

    Science.gov (United States)

    Werthmann, Jessica; Jansen, Anita; Roefs, Anne

    2015-05-01

    Living in an 'obesogenic' environment poses a serious challenge for weight maintenance. However, many people are able to maintain a healthy weight indicating that not everybody is equally susceptible to the temptations of this food environment. The way in which someone perceives and reacts to food cues, that is, cognitive processes, could underlie differences in susceptibility. An attention bias for food could be such a cognitive factor that contributes to overeating. However, an attention bias for food has also been implicated with restrained eating and eating-disorder symptomatology. The primary aim of the present review was to determine whether an attention bias for food is specifically related to obesity while also reviewing evidence for attention biases in eating-disorder patients, restrained eaters and healthy-weight individuals. Another aim was to systematically examine how selective attention for food relates (causally) to eating behaviour. Current empirical evidence on attention bias for food within obese samples, eating-disorder patients, and, even though to a lesser extent, in restrained eaters is contradictory. However, present experimental studies provide relatively consistent evidence that an attention bias for food contributes to subsequent food intake. This review highlights the need to distinguish not only between different (temporal) attention bias components, but also to take different motivations (craving v. worry) and their impact on attentional processing into account. Overall, the current state of research suggests that biased attention could be one important cognitive mechanism by which the food environment tempts us into overeating.

  4. A study of total measurement error in tomographic gamma scanning to assay nuclear material with emphasis on a bias issue for low-activity samples

    International Nuclear Information System (INIS)

    Burr, T.L.; Mercer, D.J.; Prettyman, T.H.

    1998-01-01

    Field experience with the tomographic gamma scanner to assay nuclear material suggests that the analysis techniques can significantly impact the assay uncertainty. For example, currently implemented image reconstruction methods exhibit a positive bias for low-activity samples. Preliminary studies indicate that bias reduction could be achieved at the expense of increased random error variance. In this paper, the authors examine three possible bias sources: (1) measurement error in the estimated transmission matrix, (2) the positivity constraint on the estimated mass of nuclear material, and (3) improper treatment of the measurement error structure. The authors present results from many small-scale simulation studies to examine this bias/variance tradeoff for a few image reconstruction methods in the presence of the three possible bias sources

  5. Large-scale assembly bias of dark matter halos

    Energy Technology Data Exchange (ETDEWEB)

    Lazeyras, Titouan; Musso, Marcello; Schmidt, Fabian, E-mail: titouan@mpa-garching.mpg.de, E-mail: mmusso@sas.upenn.edu, E-mail: fabians@mpa-garching.mpg.de [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching (Germany)

    2017-03-01

    We present precise measurements of the assembly bias of dark matter halos, i.e. the dependence of halo bias on other properties than the mass, using curved 'separate universe' N-body simulations which effectively incorporate an infinite-wavelength matter overdensity into the background density. This method measures the LIMD (local-in-matter-density) bias parameters b {sub n} in the large-scale limit. We focus on the dependence of the first two Eulerian biases b {sup E} {sup {sub 1}} and b {sup E} {sup {sub 2}} on four halo properties: the concentration, spin, mass accretion rate, and ellipticity. We quantitatively compare our results with previous works in which assembly bias was measured on fairly small scales. Despite this difference, our findings are in good agreement with previous results. We also look at the joint dependence of bias on two halo properties in addition to the mass. Finally, using the excursion set peaks model, we attempt to shed new insights on how assembly bias arises in this analytical model.

  6. Selective reporting bias of harm outcomes within studies: findings from a cohort of systematic reviews.

    Science.gov (United States)

    Saini, Pooja; Loke, Yoon K; Gamble, Carrol; Altman, Douglas G; Williamson, Paula R; Kirkham, Jamie J

    2014-11-21

    To determine the extent and nature of selective non-reporting of harm outcomes in clinical studies that were eligible for inclusion in a cohort of systematic reviews. Cohort study of systematic reviews from two databases. Outcome reporting bias in trials for harm outcomes (ORBIT II) in systematic reviews from the Cochrane Library and a separate cohort of systematic reviews of adverse events. 92 systematic reviews of randomised controlled trials and non-randomised studies published in the Cochrane Library between issue 9, 2012 and issue 2, 2013 (Cochrane cohort) and 230 systematic reviews published between 1 January 2007 and 31 December 2011 in other publications, synthesising data on harm outcomes (adverse event cohort). A 13 point classification system for missing outcome data on harm was developed and applied to the studies. 86% (79/92) of reviews in the Cochrane cohort did not include full data from the main harm outcome of interest of each review for all of the eligible studies included within that review; 76% (173/230) for the adverse event cohort. Overall, the single primary harm outcome was inadequately reported in 76% (705/931) of the studies included in the 92 reviews from the Cochrane cohort and not reported in 47% (4159/8837) of the 230 reviews in the adverse event cohort. In a sample of primary studies not reporting on the single primary harm outcome in the review, scrutiny of the study publication revealed that outcome reporting bias was suspected in nearly two thirds (63%, 248/393). The number of reviews suspected of outcome reporting bias as a result of missing or partially reported harm related outcomes from at least one eligible study is high. The declaration of important harms and the quality of the reporting of harm outcomes must be improved in both primary studies and systematic reviews. © Saini et al 2014.

  7. Magnetic field measurements on the perpendicular biased RF booster cavity for the proposed TRIUMF KAON Factory

    International Nuclear Information System (INIS)

    Enchevich, I.B.; Poirier, R.L.

    1992-08-01

    The successful operation of the full scale KAON Factory Ferrite tuned Booster Accelerating Cavity Prototype allowed us to do ac magnetic field measurements in the tuner. The field measured is close to that calculated. The measured data are discussed. They may be used for reliable computation of the perturbation of the beam dynamics due to the ferrite biasing magnetic field. Methods to compensate the disturbing magnetic fields are discussed. 7 refs., 7 figs

  8. An Approach to Addressing Selection Bias in Survival Analysis

    Science.gov (United States)

    Carlin, Caroline S.; Solid, Craig A.

    2014-01-01

    This work proposes a frailty model that accounts for non-random treatment assignment in survival analysis. Using Monte Carlo simulation, we found that estimated treatment parameters from our proposed endogenous selection survival model (esSurv) closely parallel the consistent two-stage residual inclusion (2SRI) results, while offering computational and interpretive advantages. The esSurv method greatly enhances computational speed relative to 2SRI by eliminating the need for bootstrapped standard errors, and generally results in smaller standard errors than those estimated by 2SRI. In addition, esSurv explicitly estimates the correlation of unobservable factors contributing to both treatment assignment and the outcome of interest, providing an interpretive advantage over the residual parameter estimate in the 2SRI method. Comparisons with commonly used propensity score methods and with a model that does not account for non-random treatment assignment show clear bias in these methods that is not mitigated by increased sample size. We illustrate using actual dialysis patient data comparing mortality of patients with mature arteriovenous grafts for venous access to mortality of patients with grafts placed but not yet ready for use at the initiation of dialysis. We find strong evidence of endogeneity (with estimate of correlation in unobserved factors ρ̂ = 0.55), and estimate a mature-graft hazard ratio of 0.197 in our proposed method, with a similar 0.173 hazard ratio using 2SRI. The 0.630 hazard ratio from a frailty model without a correction for the non-random nature of treatment assignment illustrates the importance of accounting for endogeneity. PMID:24845211

  9. Procedures for Dealing with Optimism Bias in Transport Planning

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Glenting, Carsten; Rønnest, Arne Kvist

    of the document are to provide empirically based optimism bias up-lifts for selected reference classes of transport infrastructure projects and provide guidance on using the established uplifts to produce more realistic forecasts for the individual project's capital expenditures. Furthermore, the underlying...... causes and institutional context for optimism bias in British transport projects are discussed and some possibilities for reducing optimism bias in project preparation and decision-making are identified....

  10. On the relative independence of thinking biases and cognitive ability.

    Science.gov (United States)

    Stanovich, Keith E; West, Richard F

    2008-04-01

    In 7 different studies, the authors observed that a large number of thinking biases are uncorrelated with cognitive ability. These thinking biases include some of the most classic and well-studied biases in the heuristics and biases literature, including the conjunction effect, framing effects, anchoring effects, outcome bias, base-rate neglect, "less is more" effects, affect biases, omission bias, myside bias, sunk-cost effect, and certainty effects that violate the axioms of expected utility theory. In a further experiment, the authors nonetheless showed that cognitive ability does correlate with the tendency to avoid some rational thinking biases, specifically the tendency to display denominator neglect, probability matching rather than maximizing, belief bias, and matching bias on the 4-card selection task. The authors present a framework for predicting when cognitive ability will and will not correlate with a rational thinking tendency. (c) 2008 APA, all rights reserved.

  11. Looking on the bright side: biased attention and the human serotonin transporter gene

    OpenAIRE

    Fox, Elaine; Ridgewell, Anna; Ashwin, Chris

    2009-01-01

    Humans differ in terms of biased attention for emotional stimuli and these biases can confer differential resilience and vulnerability to emotional disorders. Selective processing of positive emotional information, for example, is associated with enhanced sociability and well-being while a bias for negative material is associated with neuroticism and anxiety. A tendency to selectively avoid negative material might also be associated with mental health and well-being. The neurobiological mecha...

  12. Validation of a novel attentional bias modification task: the future may be in the cards.

    Science.gov (United States)

    Notebaert, Lies; Clarke, Patrick J F; Grafton, Ben; MacLeod, Colin

    2015-02-01

    Attentional bias modification (ABM) is a promising therapeutic tool aimed at changing patterns of attentional selectivity associated with heightened anxiety. A number of studies have successfully implemented ABM using the modified dot-probe task. However others have not achieved the attentional change required to achieve emotional benefits, highlighting the need for new ABM methods. The current study compared the effectiveness of a newly developed ABM task against the traditional dot-probe ABM task. The new person-identity-matching (PIM) task presented participants with virtual cards, each depicting a happy and angry person. The task encourages selective attention toward or away from threat by requiring participants to make matching judgements between two cards, based either on the identities of the happy faces, or of the angry faces. Change in attentional bias achieved by both ABM tasks was measured by a dot-probe assessment task. Their impact on emotional vulnerability was assessed by measuring negative emotional reactions to a video stressor. The PIM task succeeded in modifying attentional bias, and exerting an impact on emotional reactivity, whereas this was not the case for the dot-probe task. These results are considered in relation to the potential clinical utility of the current task in comparison to traditional ABM methodologies. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Behavioral and ERP measures of attentional bias to threat in the dot-probe task: Poor reliability and lack of correlation with anxiety

    Directory of Open Access Journals (Sweden)

    Emily S. Kappenman

    2014-12-01

    Full Text Available The dot-probe task is often considered a gold standard in the field for investigating attentional bias to threat. However, serious issues with the task have been raised. Specifically, a number of studies have demonstrated that the traditional reaction time measure of attentional bias to threat in the dot-probe task has poor internal reliability and poor test-retest reliability. In addition, although threatening stimuli capture attention in other paradigms, attentional bias to threat has not usually been found in typical research participants in the dot-probe task. However, when attention is measured in the dot-probe task with the N2pc component of the event-related potential (ERP waveform, substantial attentional orienting to threat is observed, and the internal reliability is moderate. To provide a rigorous comparison of the reliability of this N2pc measure and the conventional behavioral measure, as well as to examine the relationship of these measures to anxiety, the present study examined the N2pc in conjunction with reaction time in the dot-probe task in a large sample of participants (N = 96. As in previous studies, reaction time showed no bias to threatening images across the sample and exhibited poor internal reliability. Moreover, this measure did not relate to trait anxiety. By contrast, the N2pc revealed a significant initial shift of attention to threat, and this measure was internally reliable. However, the N2pc was not correlated with trait anxiety, indicating that it does not provide a meaningful index of individual differences in anxiety in the dot-probe task. Together, these results indicate a serious need to develop new tasks and methods to more reliably investigate attentional bias to threat and its relationship to anxiety in both clinical and non-clinical populations.

  14. Evaluation of point-of-care analyzers' ability to reduce bias in conductivity-based hematocrit measurement during cardiopulmonary bypass

    NARCIS (Netherlands)

    Teerenstra, S.; Steinfelder-Visscher, J.; Gunnewiek, J.K.; Weerwind, P.W.

    2014-01-01

    Most point-of-care testing analyzers use the conductivity method to measure hematocrit (hct). During open-heart surgery, blood-conductivity is influenced by shifts in electrolyte and colloid concentrations caused by infusion media used, and this may lead to considerable bias in the hct measurement.

  15. Biased attention retraining in dysphoria: a failure to replicate.

    Science.gov (United States)

    Mastikhina, Liza; Dobson, Keith

    2017-04-01

    The present study replicated Wells and Beevers [(2010). Biased attention and dysphoria: Manipulating selective attention reduces subsequent depressive symptoms. Cognition & Emotion, 24, 719-728] and examined the longitudinal effects of attentional retraining on symptoms of depression. Dysphoric undergraduate psychology students were randomly assigned into either a neutral or control training condition. Training was administered using a dot-probe task that presented participants with pairs of pictures (of sad and neutral content) that were followed by a probe that participants had to respond to. Training took place over four sessions during a two-week period, followed by a final follow-up session two weeks later. Mood was measured at baseline, post-training, and at follow-up. All participants showed a significant reduction in depressive symptoms throughout the study, F(1.7, 73.55) = 21.19, p attentional retraining did not demonstrate any advantage over the control condition. Results were inconsistent with those of Wells and Beevers [(2010). Biased attention and dysphoria: Manipulating selective attention reduces subsequent depressive symptoms. Cognition & Emotion, 24, 719-728]. Implications of the findings on research on attentional retraining in the context of depression are discussed.

  16. Religious Attitudes and Home Bias

    OpenAIRE

    C. Reggiani; G. Rossini

    2008-01-01

    Home bias affects trade in goods, services and financial assets. It is mostly generated by "natural" trade barriers. Among these dividers we may list many behavioral and sociological factors, such as status quo biases and a few kind of ‘embeddedness’. Unfortunately these factors are difficult to measure. An important part of ‘embeddedness’ may be related to religious attitudes. Is there any relation between economic home bias and religious attitudes at the individual tier? Our aim is to provi...

  17. Large-scale galaxy bias

    Science.gov (United States)

    Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian

    2018-02-01

    This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

  18. Measurement of food-related approach-avoidance biases: Larger biases when food stimuli are task relevant

    NARCIS (Netherlands)

    Lender, A.; Meule, A.; Rinck, M.; Brockmeyer, T.; Blechert, J.

    2018-01-01

    Strong implicit responses to food have evolved to avoid energy depletion but contribute to overeating in today's affluent environments. The Approach-Avoidance Task (AAT) supposedly assesses implicit biases in response to food stimuli: Participants push pictures on a monitor "away" or pull them

  19. Recognizing and reducing cognitive bias in clinical and forensic neurology.

    Science.gov (United States)

    Satya-Murti, Saty; Lockhart, Joseph

    2015-10-01

    In medicine, cognitive errors form the basis of bias in clinical practice. Several types of bias are common and pervasive, and may lead to inaccurate diagnosis or treatment. Forensic and clinical neurology, even when aided by current technologies, are still dependent on cognitive interpretations, and therefore prone to bias. This article discusses 4 common biases that can lead the clinician astray. They are confirmation bias (selective gathering of and neglect of contradictory evidence); base rate bias (ignoring or misusing prevailing base rate data); hindsight bias (oversimplification of past causation); and good old days bias (the tendency for patients to misremember and exaggerate their preinjury functioning). We briefly describe strategies adopted from the field of psychology that could minimize bias. While debiasing is not easy, reducing such errors requires awareness and acknowledgment of our susceptibility to these cognitive distortions.

  20. Estimatining biases in the stellar dynamical black hole mass measurements in barred galaxies and prospects for measuring SMBH masses with JWST

    Science.gov (United States)

    Valluri, Monica; Vasiliev, Eugene; Bentz, Misty; Shen, Juntai

    2018-04-01

    Although 60% of disk galaxies are barred, stellar dynamical measurements of the masses of supermassive black holes (SMBH) in barred galaxies have always been obtained under the assumption that the bulges are axisymmetric. We use N-body simulations with self-consistently grown SMBHs in barred and unbarred galaxies to create a suite of mock Integral Field Spectrographic (IFS) datasets for galaxies with various observed orientations. We then apply an axisymmetric orbit superposition code to these mock IFS datasets to assess the reliability with which SMBH masses can be recovered. We also assess which disk and bar orientations give rise to biases. We use these simulations to assess whether or not existing SMBH measurements in barred galaxies are likely to be biased. We also present a brief preview of our JWST Early Release Science proposal to study the nuclear dynamics of nearby Seyfert I galaxy NGC 4151 with the NIRSpec Integral Field Spectrograph and describe how simulations of disk galaxies will used to create mock NIRSpec data to prepare for the real data.

  1. Attentional bias modification based on visual probe task: methodological issues, results and clinical relevance

    Directory of Open Access Journals (Sweden)

    Fernanda Machado Lopes

    2015-12-01

    Full Text Available Introduction: Attentional bias, the tendency that a person has to drive or maintain attention to a specific class of stimuli, may play an important role in the etiology and persistence of mental disorders. Attentional bias modification has been studied as a form of additional treatment related to automatic processing. Objectives: This systematic literature review compared and discussed methods, evidence of success and potential clinical applications of studies about attentional bias modification (ABM using a visual probe task. Methods: The Web of Knowledge, PubMed and PsycInfo were searched using the keywords attentional bias modification, attentional bias manipulation and attentional bias training. We selected empirical studies about ABM training using a visual probe task written in English and published between 2002 and 2014. Results: Fifty-seven studies met inclusion criteria. Most (78% succeeded in training attention in the predicted direction, and in 71% results were generalized to other measures correlated with the symptoms. Conclusions: ABM has potential clinical utility, but to standardize methods and maximize applicability, future studies should include clinical samples and be based on findings of studies about its effectiveness.

  2. Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

    Science.gov (United States)

    Wang, Y.; Hioki, S.; Yang, P.; Di Girolamo, L.; Fu, D.

    2017-12-01

    The precise estimation of two important cloud optical and microphysical properties, cloud particle optical thickness and cloud particle effective radius, is fundamental in the study of radiative energy budget and hydrological cycle. In retrieving these two properties, an appropriate selection of ice particle surface roughness is important because it substantially affects the single-scattering properties. At present, using a predetermined ice particle shape without spatial and temporal variations is a common practice in satellite-based retrieval. This approach leads to substantial uncertainties in retrievals. The cloud radiances measured by each of the cameras of the Multi-angle Imaging SpectroRadiometer (MISR) instrument are used to estimate spherical albedo values at different scattering angles. By analyzing the directional distribution of estimated spherical albedo values, the degree of ice particle surface roughness is estimated. With an optimal degree of ice particle roughness, cloud optical thickness and effective radius are retrieved based on a bi-spectral shortwave technique in conjunction with two Moderate Resolution Imaging Spectroradiometer (MODIS) bands centered at 0.86 and 2.13 μm. The seasonal biases of retrieved cloud optical and microphysical properties, caused by the uncertainties in ice particle roughness, are investigated by using one year of MISR-MODIS fused data.

  3. Time Biases in laser ranging measurements; impacts on geodetic products (Reference Frame and Orbitography)

    Science.gov (United States)

    Belli, A.; Exertier, P.; Lemoine, F. G.; Chinn, D. S.; Zelensky, N. P.

    2017-12-01

    The GGOS objectives are to maintain a geodetic network with an accuracy of 1 mm and a stability of 0.1 mm per year. For years, the laser ranging technique, which provide very accurate absolute distances to geodetic targets enable to determine the scale factor as well as coordinates of the geocenter. In order to achieve this goal, systematic errors appearing in the laser ranging measurements must be considered and solved. In addition to Range Bias (RB), which is the primary source of uncertainty of the technique, Time Bias (TB) has been recently detected by using the Time Transfer by Laser Link (T2L2) space instrument capability on-board the satellite Jason-2. Instead of determining TB through the precise orbit determination that is applied to commonly used geodetic targets like LAGEOS to estimate global geodetic products, we have developed, independently, a dedicated method to transfer time between remote satellite laser ranging stations. As a result, the evolving clock phase shift to UTC of around 30 stations has been determined under the form of time series of time bias per station from 2008 to 2016 with an accuracy of 3-4 ns. It demonstrated the difficulty, in terms of Time & Frequency used technologies, to locally maintain accuracy and long term stability at least in the range of 100 ns that is the current requirement for time measurements (UTC) for the laser ranging technique. Because some laser ranging stations oftently exceed this limit (from 100 ns to a few μs) we have been studying these effects first on the precision orbit determination itself, second on the station positioning. We discuss the impact of TB on LAGEOS and Jason-2 orbits, which appears to affect the along-track component essentially. We also investigate the role of TB in global geodetic parameters as the station coordinates. Finally, we propose to provide the community with time series of time bias of laser ranging stations, under the form of a data- handling-file in order to be included in

  4. A method for additive bias correction in cross-cultural surveys

    DEFF Research Database (Denmark)

    Scholderer, Joachim; Grunert, Klaus G.; Brunsø, Karen

    2001-01-01

    additive bias from cross-cultural data. The procedure involves four steps: (1) embed a potentially biased item in a factor-analytic measurement model, (2) test for the existence of additive bias between populations, (3) use the factor-analytic model to estimate the magnitude of the bias, and (4) replace......Measurement bias in cross-cultural surveys can seriously threaten the validity of hypothesis tests. Direct comparisons of means depend on the assumption that differences in observed variables reflect differences in the underlying constructs, and not an additive bias that may be caused by cultural...... differences in the understanding of item wording or response category labels. However, experience suggests that additive bias can be found more often than not. Based on the concept of partial measurement invariance (Byrne, Shavelson and Muthén, 1989), the present paper develops a procedure for eliminating...

  5. Attentional Bias towards Positive Emotion Predicts Stress Resilience.

    Science.gov (United States)

    Thoern, Hanna A; Grueschow, Marcus; Ehlert, Ulrike; Ruff, Christian C; Kleim, Birgit

    2016-01-01

    There is extensive evidence for an association between an attentional bias towards emotionally negative stimuli and vulnerability to stress-related psychopathology. Less is known about whether selective attention towards emotionally positive stimuli relates to mental health and stress resilience. The current study used a modified Dot Probe task to investigate if individual differences in attentional biases towards either happy or angry emotional stimuli, or an interaction between these biases, are related to self-reported trait stress resilience. In a nonclinical sample (N = 43), we indexed attentional biases as individual differences in reaction time for stimuli preceded by either happy or angry (compared to neutral) face stimuli. Participants with greater attentional bias towards happy faces (but not angry faces) reported higher trait resilience. However, an attentional bias towards angry stimuli moderated this effect: The attentional bias towards happy faces was only predictive for resilience in those individuals who also endorsed an attentional bias towards angry stimuli. An attentional bias towards positive emotional stimuli may thus be a protective factor contributing to stress resilience, specifically in those individuals who also endorse an attentional bias towards negative emotional stimuli. Our findings therefore suggest a novel target for prevention and treatment interventions addressing stress-related psychopathology.

  6. Media Bias and Advertising: Evidence from German Car Magazines

    OpenAIRE

    Dewenter, Ralf; Heimeshoff, Ulrich

    2011-01-01

    This paper investigates the existence of a possible media bias by analyzing the impact of automobile manufactures' advertisements on automobile reviews in German car magazines. By accounting for both endogeneity and sample selection we find a positive impact of advertising volumes on test scores. Moreover, also a home bias in terms of higher scores for German cars is observable. We account these results as some evidence for a media bias, induced by the two-sidedness of the markets.

  7. Large-scale galaxy bias

    Science.gov (United States)

    Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian

    2018-01-01

    Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

  8. Implementation of linear bias corrections for calorimeters at Mound

    International Nuclear Information System (INIS)

    Barnett, T.M.

    1993-01-01

    In the past, Mound has generally made relative bias corrections as part of the calibration of individual calorimeters. The correction made was the same over the entire operating range of the calorimeter, regardless of the magnitude of the range. Recently, an investigation was performed to check the relevancy of using linear bias corrections to calibrate the calorimeters. The bias is obtained by measuring calibrated plutonium and/or electrical heat standards over the operating range of the calorimeter. The bias correction is then calculated using a simple least squares fit (y = mx + b) of the bias in milliwatts over the operating range of the calorimeter in watts. The equation used is B i = B 0 + (B w * W m ), where B i is the bias at any given power in milliwatts, B 0 is the intercept (absolute bias in milliwatts), B w is the slope (relative bias in milliwatts per watt), and W m is the measured power in watts. The results of the study showed a decrease in the random error of bias corrected data for most of the calorimeters which are operated over a large wattage range (greater than an order of magnitude). The linear technique for bias correction has been fully implemented at Mound and has been included in the Technical Manual, ''A Measurement Control Program for Radiometric Calorimeters at Mound'' (MD-21900)

  9. A permutation test to analyse systematic bias and random measurement errors of medical devices via boosting location and scale models.

    Science.gov (United States)

    Mayr, Andreas; Schmid, Matthias; Pfahlberg, Annette; Uter, Wolfgang; Gefeller, Olaf

    2017-06-01

    Measurement errors of medico-technical devices can be separated into systematic bias and random error. We propose a new method to address both simultaneously via generalized additive models for location, scale and shape (GAMLSS) in combination with permutation tests. More precisely, we extend a recently proposed boosting algorithm for GAMLSS to provide a test procedure to analyse potential device effects on the measurements. We carried out a large-scale simulation study to provide empirical evidence that our method is able to identify possible sources of systematic bias as well as random error under different conditions. Finally, we apply our approach to compare measurements of skin pigmentation from two different devices in an epidemiological study.

  10. delta-biased Josephson tunnel junctions

    DEFF Research Database (Denmark)

    Monaco, R.; Mygind, Jesper; Koshelet, V.

    2010-01-01

    Abstract: The behavior of a long Josephson tunnel junction drastically depends on the distribution of the dc bias current. We investigate the case in which the bias current is fed in the central point of a one-dimensional junction. Such junction configuration has been recently used to detect...... the persistent currents circulating in a superconducting loop. Analytical and numerical results indicate that the presence of fractional vortices leads to remarkable differences from the conventional case of uniformly distributed dc bias current. The theoretical findings are supported by detailed measurements...

  11. Australia's Bond Home Bias

    OpenAIRE

    Anil V. Mishra; Umaru B. Conteh

    2014-01-01

    This paper constructs the float adjusted measure of home bias and explores the determinants of bond home bias by employing the International Monetary Fund's high quality dataset (2001 to 2009) on cross-border bond investment. The paper finds that Australian investors' prefer investing in countries with higher economic development and more developed bond markets. Exchange rate volatility appears to be an impediment for cross-border bond investment. Investors prefer investing in countries with ...

  12. Does neurocognitive function affect cognitive bias toward an emotional stimulus? Association between general attentional ability and attentional bias toward threat

    OpenAIRE

    Hakamata, Yuko; Matsui, Mie; Tagaya, Hirokuni

    2014-01-01

    Background: Although poorer cognitive performance has been found to be associated with anxiety, it remains unclear whether neurocognitive function affects biased cognitive processing toward emotional information. We investigated whether general cognitive function evaluated with a standard neuropsychological test predicts biased cognition, focusing on attentional bias toward threat. Methods: One hundred and five healthy young adults completed a dot-probe task measuring attentional bias and ...

  13. [Attentional bias and emotional suppression in borderline personality disorder].

    Science.gov (United States)

    Fernando, Silvia Carvalho; Griepenstroh, Julia; Urban, Sabine; Driessen, Martin; Beblo, Thomas

    2014-01-01

    Emotion regulation dysfunctions marked by negative affectivity are a core feature of borderline personality disorder (BPD). In addition, patients with BPD show disturbed attentional processes which become particularly apparent in the domain of selective attention when emotional stimuli are presented (negative attentional bias). Assuming that emotion regulation is linked to attentional deployment processes, this study aimed (1) to determine whether a negative attentional bias is established by using film clips of fearful faces and (2) to investigate the association between dysfunctional emotion regulation strategies (emotional suppression) and negative attention bias in BPD. We investigated 18 inpatients with BPD and 18 healthy control participants using the modified version of the fearful face-paradigm to assess the inhibition of emotional stimuli. We also administered self-report emotion regulation questionnaires. Compared to the healthy controls, patients with BPD showed significant longer reaction times during the emotional versus the neutral film stimuli in the modified fearful face-paradigm. With regard to the second hypothesis, we failed to find an association between the negative attentional bias and the habitual use of emotional suppression in BPD. In this study, we could confirm an attentional bias for negative stimuli, using complex, dynamic material. Future studies need to address the impact of confounding variables (e. g. comorbid disorders) on the relationship between maladaptive emotion regulation and selective attentional bias.

  14. Accuracy and differential bias in copy number measurement of CCL3L1 in association studies with three auto-immune disorders.

    Science.gov (United States)

    Carpenter, Danielle; Walker, Susan; Prescott, Natalie; Schalkwijk, Joost; Armour, John Al

    2011-08-18

    Copy number variation (CNV) contributes to the variation observed between individuals and can influence human disease progression, but the accurate measurement of individual copy numbers is technically challenging. In the work presented here we describe a modification to a previously described paralogue ratio test (PRT) method for genotyping the CCL3L1/CCL4L1 copy variable region, which we use to ascertain CCL3L1/CCL4L1 copy number in 1581 European samples. As the products of CCL3L1 and CCL4L1 potentially play a role in autoimmunity we performed case control association studies with Crohn's disease, rheumatoid arthritis and psoriasis clinical cohorts. We evaluate the PRT methodology used, paying particular attention to accuracy and precision, and highlight the problems of differential bias in copy number measurements. Our PRT methods for measuring copy number were of sufficient precision to detect very slight but systematic differential bias between results from case and control DNA samples in one study. We find no evidence for an association between CCL3L1 copy number and Crohn's disease, rheumatoid arthritis or psoriasis. Differential bias of this small magnitude, but applied systematically across large numbers of samples, would create a serious risk of false positive associations in copy number, if measured using methods of lower precision, or methods relying on single uncorroborated measurements. In this study the small differential bias detected by PRT in one sample set was resolved by a simple pre-treatment by restriction enzyme digestion.

  15. Accuracy and differential bias in copy number measurement of CCL3L1 in association studies with three auto-immune disorders

    Directory of Open Access Journals (Sweden)

    Carpenter Danielle

    2011-08-01

    Full Text Available Abstract Background Copy number variation (CNV contributes to the variation observed between individuals and can influence human disease progression, but the accurate measurement of individual copy numbers is technically challenging. In the work presented here we describe a modification to a previously described paralogue ratio test (PRT method for genotyping the CCL3L1/CCL4L1 copy variable region, which we use to ascertain CCL3L1/CCL4L1 copy number in 1581 European samples. As the products of CCL3L1 and CCL4L1 potentially play a role in autoimmunity we performed case control association studies with Crohn's disease, rheumatoid arthritis and psoriasis clinical cohorts. Results We evaluate the PRT methodology used, paying particular attention to accuracy and precision, and highlight the problems of differential bias in copy number measurements. Our PRT methods for measuring copy number were of sufficient precision to detect very slight but systematic differential bias between results from case and control DNA samples in one study. We find no evidence for an association between CCL3L1 copy number and Crohn's disease, rheumatoid arthritis or psoriasis. Conclusions Differential bias of this small magnitude, but applied systematically across large numbers of samples, would create a serious risk of false positive associations in copy number, if measured using methods of lower precision, or methods relying on single uncorroborated measurements. In this study the small differential bias detected by PRT in one sample set was resolved by a simple pre-treatment by restriction enzyme digestion.

  16. Radon measurements-discussion of error estimates for selected methods

    International Nuclear Information System (INIS)

    Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav

    2010-01-01

    The main sources of uncertainties for grab sampling, short-term (charcoal canisters) and long term (track detectors) measurements are: systematic bias of reference equipment; random Poisson and non-Poisson errors during calibration; random Poisson and non-Poisson errors during measurements. The origins of non-Poisson random errors during calibration are different for different kinds of instrumental measurements. The main sources of uncertainties for retrospective measurements conducted by surface traps techniques can be divided in two groups: errors of surface 210 Pb ( 210 Po) activity measurements and uncertainties of transfer from 210 Pb surface activity in glass objects to average radon concentration during this object exposure. It's shown that total measurement error of surface trap retrospective technique can be decreased to 35%.

  17. Assessing cross-cultural item bias in questionnaires: Acculturation and the Measurement of Social Support and Family Cohesion for Adolescents

    OpenAIRE

    Hemert, Dianne A. van; Baerveldt, Chris; Vermande, Marjolijn

    2001-01-01

    Amethod is presented for evaluating the presence and size of cross-cultural item biases. The examined items concern parental support and family cohesion in a Likert-type questionnaire for adolescents in The Netherlands. Each evaluated item has two versions, a collectivist and an individualistic one, that measure the same theoretical construct. The standardized difference between the score means of the item versions, called the ?e score, gives an indication of the cultural bias of the item. As...

  18. Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling.

    Science.gov (United States)

    Biro, Peter A

    2013-02-01

    Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

  19. Declining Bias and Gender Wage Discrimination? A Meta-Regression Analysis

    Science.gov (United States)

    Jarrell, Stephen B.; Stanley, T. D.

    2004-01-01

    The meta-regression analysis reveals that there is a strong tendency for discrimination estimates to fall and wage discrimination exist against the woman. The biasing effect of researchers' gender of not correcting for selection bias has weakened and changes in labor market have made it less important.

  20. Attentional bias in math anxiety.

    Science.gov (United States)

    Rubinsten, Orly; Eidlin, Hili; Wohl, Hadas; Akibli, Orly

    2015-01-01

    Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety (MA) as well (i.e., a persistent negative reaction to math). Twenty seven participants (14 with high levels of MA and 13 with low levels of MA) were presented with a novel computerized numerical version of the well established dot probe task. One of six types of prime stimuli, either math related or typically neutral, was presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks) that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks). Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in MA. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words). These findings suggest that attentional bias is linked to unduly intense MA symptoms.

  1. Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

    Science.gov (United States)

    Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

    2018-05-01

    High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  2. The CogBIAS longitudinal study protocol: cognitive and genetic factors influencing psychological functioning in adolescence.

    Science.gov (United States)

    Booth, Charlotte; Songco, Annabel; Parsons, Sam; Heathcote, Lauren; Vincent, John; Keers, Robert; Fox, Elaine

    2017-12-29

    Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample. CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships. CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.

  3. Niche construction, sources of selection and trait coevolution.

    Science.gov (United States)

    Laland, Kevin; Odling-Smee, John; Endler, John

    2017-10-06

    Organisms modify and choose components of their local environments. This 'niche construction' can alter ecological processes, modify natural selection and contribute to inheritance through ecological legacies. Here, we propose that niche construction initiates and modifies the selection directly affecting the constructor, and on other species, in an orderly, directed and sustained manner. By dependably generating specific environmental states, niche construction co-directs adaptive evolution by imposing a consistent statistical bias on selection. We illustrate how niche construction can generate this evolutionary bias by comparing it with artificial selection. We suggest that it occupies the middle ground between artificial and natural selection. We show how the perspective leads to testable predictions related to: (i) reduced variance in measures of responses to natural selection in the wild; (ii) multiple trait coevolution, including the evolution of sequences of traits and patterns of parallel evolution; and (iii) a positive association between niche construction and biodiversity. More generally, we submit that evolutionary biology would benefit from greater attention to the diverse properties of all sources of selection.

  4. The impact of stroke unit care on outcome in a Scottish stroke population, taking into account case mix and selection bias.

    Science.gov (United States)

    Turner, Melanie; Barber, Mark; Dodds, Hazel; Dennis, Martin; Langhorne, Peter; Macleod, Mary Joan

    2015-03-01

    Randomised trials indicate that stroke unit care reduces morbidity and mortality after stroke. Similar results have been seen in observational studies but many have not corrected for selection bias or independent predictors of outcome. We evaluated the effect of stroke unit compared with general ward care on outcomes after stroke in Scotland, adjusting for case mix by incorporating the six simple variables (SSV) model, also taking into account selection bias and stroke subtype. We used routine data from National Scottish datasets for acute stroke patients admitted between 2005 and 2011. Patients who died within 3 days of admission were excluded from analysis. The main outcome measures were survival and discharge home. Multivariable logistic regression was used to estimate the OR for survival, and adjustment was made for the effect of the SSV model and for early mortality. Cox proportional hazards model was used to estimate the hazard of death within 365 days. There were 41 692 index stroke events; 79% were admitted to a stroke unit at some point during their hospital stay and 21% were cared for in a general ward. Using the SSV model, we obtained a receiver operated curve of 0.82 (SE 0.002) for mortality at 6 months. The adjusted OR for survival at 7 days was 3.11 (95% CI 2.71 to 3.56) and at 1 year 1.43 (95% CI 1.34 to 1.54) while the adjusted OR for being discharged home was 1.19 (95% CI 1.11 to 1.28) for stroke unit care. In routine practice, stroke unit admission is associated with a greater likelihood of discharge home and with lower mortality up to 1 year, after correcting for known independent predictors of outcome, and excluding early non-modifiable mortality. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  5. Investor’s Commitment Bias and Escalation of Firm’s Investment Decision

    Directory of Open Access Journals (Sweden)

    Anis JARBOUI

    2012-12-01

    Full Text Available This study examines the reasons of perseverance in firm’s investment decision. It shows the possible influence of three closely related features which are: firm’s financial indicators, investor’s risk profile, and investor’s commitment bias, on a firm’s investment decisions escalation. This study aims to provide evidence as to whether investor considers the financial and risk’s perception features (financial strength and risk profile to persevere his initial investment decision while he notes a high level of commitment bias. The proposed model of this paper uses GLM univariate data analyses to examine this relationship. Investor’s risk profile and his commitment bias have been measured by means of a questionnaire comprising several items. As for the selected sample, it has been composed of some 360 Tunisian individual investors. Our results have revealed that investors pay more attention to keep their psychology comfort than their financial comfort. It exposed the importance of the investor’s commitment bias and its risk perception in explaining investment decision escalation. Moreover results shows that there is strong and significant empirical relationship linking the escalatory behavior in investment decision and the interaction effects between the three independent variables. This means that, in practice, investors consider the three factors simultaneously.

  6. A procedure for eliminating additive bias from cross-cultural survey data

    DEFF Research Database (Denmark)

    Scholderer, Joachim; Grunert, Klaus G.; Brunsø, Karen

    2005-01-01

    additive bias from cross-cultural data. The procedure involves four steps: (1) embed a potentially biased item in a factor-analytic measurement model, (2) test for the existence of additive bias between populations, (3) use the factor-analytic model to estimate the magnitude of the bias, and (4) replace......Measurement bias in cross-cultural surveys can seriously threaten the validity of hypothesis tests. Direct comparisons of means depend on the assumption that differences in observed variables reflect differences in the underlying constructs, and not an additive bias that may be caused by cultural...... differences in the understanding of item wording or response category labels. However, experience suggests that additive bias can be found more often than not. Based on the concept of partial measurement invariance (Byrne, Shavelson and Muthén 1989), the present paper develops a procedure for eliminating...

  7. Attention bias for social threat in youth with tic disorders: Links with tic severity and social anxiety.

    Science.gov (United States)

    Pile, Victoria; Robinson, Sally; Topor, Marta; Hedderly, Tammy; Lau, Jennifer Y F

    2018-06-07

    Many individuals with Tourette syndrome and chronic tic disorders (TS/CTDs) report poor social functioning and comorbid social anxiety. Yet limited research has investigated the role of cognitive factors that highlight social threats in youth with TS/CTD, and whether these biases underlie tic severity and co-occurring social anxiety. This study examined whether selective attention to social threat is enhanced young people with TS/CTDs compared to healthy controls, and whether attention biases are associated with tic severity and social anxiety. Twenty seven young people with TS/CTDs and 25 matched control participants completed an experimental measure of attention bias toward/away from threat stimuli. A clinician-rated interview measuring tic severity/impairment (YGTSS Total Score) and questionnaire measures of social anxiety were completed by participants and their parents. Young people with TS/CTD showed an attention bias to social threat words (relative to benign words) compared to controls but no such bias for social threat faces. Attention bias for social threat words was associated with increasing YGTSS Total Score and parent-reported social anxiety in the TS/CTDs group. Mediation analysis revealed a significant indirect path between YGTSS Total Score and social anxiety, via attention to social threat. Tentatively, these associations appeared to be driven by impairment rather than tic severity scores. Preliminary data suggests that youth with TS/CTD have enhanced attention to threat, compared to controls, and this is associated with impairment and social anxiety. Attention to threat could offer a cognitive mechanism connecting impairment and social anxiety, and so be a valuable trans-diagnostic treatment target.

  8. Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data : An illustration with health-related quality of life data from thirteen measurement occasions

    NARCIS (Netherlands)

    Verdam, M.G.E.; Oort, F.J.

    2014-01-01

    Highlights: - Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data. - A method for the investigation of measurement bias with Kronecker product restricted models. - Application of these methods to health-related quality of life data

  9. AC bias operation of the perpendicular biased ferrite tuned cavity for the TRIUMF KAON Factory booster synchrotron

    International Nuclear Information System (INIS)

    Poirier, R.L.; Enegren, T.A.; Enchevich, I.B.

    1991-05-01

    The RF cavity for the booster synchrotron requires a frequency swing from 46 MHz at a repetition rate of 50 Hz and a maximum accelerating gap voltage of 65 kV. A DC biased prototype cavity built at LANL using perpendicular-biased yttrium-garnet ferrites, rather than the more conventional parallel-biased NiZn ferrites, has now undergone major reconstruction at TRIUMF for AC bias operation. RF signal level measurements have shown that the frequency swing at a repetition rate of 50 Hz can be accomplished and still handle the eddy current losses in the cavity structures with minimal effect on the magnetizing field. The prototype cavity is now undergoing high power RF tests with full power AC bias operation. The results of these tests and operational experience is reported. (Author) ref., 6 figs

  10. Potential sources of bias in the use of Escherichia coli to measure waterborne diarrhoea risk in low-income settings.

    Science.gov (United States)

    Ercumen, Ayse; Arnold, Benjamin F; Naser, Abu Mohd; Unicomb, Leanne; Colford, John M; Luby, Stephen P

    2017-01-01

    Escherichia coli is the standard water quality indicator for diarrhoea risk. Yet, the association between E. coli and diarrhoea is inconsistent across studies without a systematic assessment of methodological differences behind this variation. Most studies measure water quality cross-sectionally with diarrhoea, risking exposure misclassification and reverse causation. Studies use different recall windows for self-reported diarrhoea; longer periods increase potential outcome misclassification through misrecall. Control of confounding is inconsistent across studies. Additionally, diarrhoea measured in unblinded intervention trials can present courtesy bias. We utilised measurements from a randomised trial of water interventions in Bangladesh to assess how these factors affect the E. coli-diarrhoea association. We compared cross-sectional versus prospective measurements of water quality and diarrhoea, 2-versus 7-day symptom recall periods, estimates with and without controlling for confounding and using measurements from control versus intervention arms of the trial. In the control arm, 2-day diarrhoea prevalence, measured prospectively 1 month after water quality, significantly increased with log 10 E. coli (PR = 1.50, 1.02-2.20). This association weakened when we used 7-day recall (PR = 1.18, 0.88-1.57), cross-sectional measurements of E. coli and diarrhoea (PR = 1.11, 0.79-1.56) or did not control for confounding (PR = 1.20, 0.88-1.62). Including data from intervention arms led to less interpretable associations, potentially due to courtesy bias, effect modification and/or reverse causation. By systematically addressing potential sources of bias, our analysis demonstrates a clear relationship between E. coli in drinking water and diarrhoea, suggesting that the continued use of E. coli as an indicator of waterborne diarrhoea risk is justified. © 2016 John Wiley & Sons Ltd.

  11. Removing Malmquist bias from linear regressions

    Science.gov (United States)

    Verter, Frances

    1993-01-01

    Malmquist bias is present in all astronomical surveys where sources are observed above an apparent brightness threshold. Those sources which can be detected at progressively larger distances are progressively more limited to the intrinsically luminous portion of the true distribution. This bias does not distort any of the measurements, but distorts the sample composition. We have developed the first treatment to correct for Malmquist bias in linear regressions of astronomical data. A demonstration of the corrected linear regression that is computed in four steps is presented.

  12. Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions

    NARCIS (Netherlands)

    Verdam, Mathilde G. E.; Oort, Frans J.

    2014-01-01

    Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data. A method for the investigation of measurement bias with Kronecker product restricted models. Application of these methods to health-related quality of life data from bone

  13. Reporting bias in medical research - a narrative review

    Directory of Open Access Journals (Sweden)

    Kölsch Heike

    2010-04-01

    Full Text Available Abstract Reporting bias represents a major problem in the assessment of health care interventions. Several prominent cases have been described in the literature, for example, in the reporting of trials of antidepressants, Class I anti-arrhythmic drugs, and selective COX-2 inhibitors. The aim of this narrative review is to gain an overview of reporting bias in the medical literature, focussing on publication bias and selective outcome reporting. We explore whether these types of bias have been shown in areas beyond the well-known cases noted above, in order to gain an impression of how widespread the problem is. For this purpose, we screened relevant articles on reporting bias that had previously been obtained by the German Institute for Quality and Efficiency in Health Care in the context of its health technology assessment reports and other research work, together with the reference lists of these articles. We identified reporting bias in 40 indications comprising around 50 different pharmacological, surgical (e.g. vacuum-assisted closure therapy, diagnostic (e.g. ultrasound, and preventive (e.g. cancer vaccines interventions. Regarding pharmacological interventions, cases of reporting bias were, for example, identified in the treatment of the following conditions: depression, bipolar disorder, schizophrenia, anxiety disorder, attention-deficit hyperactivity disorder, Alzheimer's disease, pain, migraine, cardiovascular disease, gastric ulcers, irritable bowel syndrome, urinary incontinence, atopic dermatitis, diabetes mellitus type 2, hypercholesterolaemia, thyroid disorders, menopausal symptoms, various types of cancer (e.g. ovarian cancer and melanoma, various types of infections (e.g. HIV, influenza and Hepatitis B, and acute trauma. Many cases involved the withholding of study data by manufacturers and regulatory agencies or the active attempt by manufacturers to suppress publication. The ascertained effects of reporting bias included the

  14. Study of the Dependency on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter

    Science.gov (United States)

    Gottardi, L.; Bruijn, M.; denHartog, R.; Hoevers, H.; deKorte, P.; vanderKuur, J.; Linderman, M.; Adams, J.; Bailey, C.; Bandler, S.; hide

    2012-01-01

    At SRON we are studying the performance of a Goddard Space Flight Center single pixel TES microcalorimeter operated in an AC bias configuration. For x-ray photons at 6 keV the pixel shows an x-ray energy resolution Delta E(sub FWHM) = 3.7 eV, which is about a factor 2 worse than the energy resolution observed in an identical DC-biased pixel. In order to better understand the reasons for this discrepancy we characterized the detector as a function of temperature, bias working point and applied perpendicular magnetic field. A strong periodic dependency of the detector noise on the TES AC bias voltage is measured. We discuss the results in the framework of the recently observed weak-link behaviour of a TES microcalorimeter.

  15. Principles in selecting human capital measurements and metrics

    Directory of Open Access Journals (Sweden)

    Pharny D. Chrysler-Fox

    2014-09-01

    Research purpose: The study explored principles in selecting human capital measurements,drawing on the views and recommendations of human resource management professionals,all experts in human capital measurement. Motivation for the study: The motivation was to advance the understanding of selectingappropriate and strategic valid measurements, in order for human resource practitioners tocontribute to creating value and driving strategic change. Research design, approach and method: A qualitative approach, with purposively selectedcases from a selected panel of human capital measurement experts, generated a datasetthrough unstructured interviews, which were analysed thematically. Main findings: Nineteen themes were found. They represent a process that considers thecentrality of the business strategy and a systemic integration across multiple value chains inthe organisation through business partnering, in order to select measurements and generatemanagement level-appropriate information. Practical/managerial implications: Measurement practitioners, in partnership withmanagement from other functions, should integrate the business strategy across multiplevalue chains in order to select measurements. Analytics becomes critical in discoveringrelationships and formulating hypotheses to understand value creation. Higher educationinstitutions should produce graduates able to deal with systems thinking and to operatewithin complexity. Contribution: This study identified principles to select measurements and metrics. Noticeableis the move away from the interrelated scorecard perspectives to a systemic view of theorganisation in order to understand value creation. In addition, the findings may help toposition the human resource management function as a strategic asset.

  16. Sex allocation in fungus-growing ants: worker or queen control without symbiont-induced female bias

    DEFF Research Database (Denmark)

    Dijkstra, Michiel B.; Boomsma, Jacobus Jan

    2008-01-01

    The fungal cultivars of fungus-growing ants are vertically transmitted by queens but not males. Selection would therefore favor cultivars that bias the ants' sex ratio towards gynes, beyond the gyne bias that is optimal for workers and queens. We measured sex allocation in 190 colonies of six...... sympatric fungus-growing ant species. As predicted from relatedness, female bias was greater in four singly mated Sericomyrmex and Trachymyrmex species than in two multiply mated Acromyrmex species. Colonies tended to raise mainly a single sex, which could be partly explained by variation in queen number......, colony fecundity, and fungal garden volume for Acromyrmex and Sericomyrmex, but not for Trachymyrmex. Year of collection, worker number and mating frequency of Acromyrmex queens did not affect the colony sex ratios. We used a novel sensitivity analysis to compare the population sex allocation ratios...

  17. Effects of acute dopamine precusor depletion on immediate reward selection bias and working memory depend on catechol-O-methyltransferase genotype.

    Science.gov (United States)

    Kelm, Mary Katherine; Boettiger, Charlotte A

    2013-12-01

    Little agreement exists as to acute dopamine (DA) manipulation effects on intertemporal choice in humans. We previously found that catechol-O-methyltransferase (COMT) Val158Met genotype predicts individual differences in immediate reward selection bias among adults. Moreover, we and others have shown that the relationship between COMT genotype and immediate reward bias is inverted in adolescents. No previous pharmacology studies testing DA manipulation effects on intertemporal choice have accounted for COMT genotype, and many have included participants in the adolescent age range (18-21 years) as adults. Moreover, many studies have included female participants without strict cycle phase control, although recent evidence demonstrates that cyclic estradiol elevations interact with COMT genotype to affect DA-dependent cognition. These factors may have interacted with DA manipulations in past studies, potentially occluding detection of effects. Therefore, we predicted that, among healthy male adults (ages 22-40 years), frontal DA tone, as indexed by COMT genotype, would interact with acute changes in DA signaling to affect intertemporal choice. In a double-blind, placebo-controlled design, we decreased central DA via administration of an amino acid beverage deficient in the DA precursors, phenylalanine and tyrosine, and tested effects on immediate reward bias in a delay-discounting (DD) task and working memory (WM) in an n-back task. We found no main effect of beverage on DD or WM performance but did find significant beverage*genotype effects. These results suggest that the effect of DA manipulations on DD depends on individual differences in frontal DA tone, which may have impeded some past efforts to characterize DA's role in immediate reward bias in humans.

  18. Contributions of speed and accuracy to translational selection in bacteria.

    Directory of Open Access Journals (Sweden)

    Wenqi Ran

    Full Text Available Among bacteria, we have previously shown that species that are capable of rapid growth have stronger selection on codon usage than slow growing species, and possess higher numbers of rRNA and tRNA genes. This suggests that fast-growers are adapted for fast protein synthesis. There is also considerable evidence that codon usage is influenced by accuracy of translation, and some authors have argued that accuracy is more important than speed. Here we compare the strength of the two effects by studying the codon usages in high and low expression genes and on conserved and variable sites within high expression genes. We introduce a simple statistical method that can be used to assess the significance and the strength of the two types of bias in the same sets of sequences. We compare our statistical measure of codon bias to the common used codon adaptation index, and show that the new measure is preferable for three reasons for the purposes of this analysis. Across a large sample of bacterial genomes, both effects from speed and accuracy are clearly visible, although the speed effect appears to be much stronger than the accuracy effect and is found to be significant in a larger proportion of genomes. It is also difficult to explain the correlation of codon bias in the high expression genes with growth rates and numbers of copies of tRNA and rRNA genes on the basis of selection for accuracy. Hence we conclude that selection for translational speed is a dominant effect in driving codon usage bias in fast-growing bacteria, with selection for accuracy playing a small supplementary role.

  19. Young children seek out biased information about social groups.

    Science.gov (United States)

    Over, Harriet; Eggleston, Adam; Bell, Jenny; Dunham, Yarrow

    2018-05-01

    Understanding the origins of prejudice necessitates exploring the ways in which children participate in the construction of biased representations of social groups. We investigate whether young children actively seek out information that supports and extends their initial intergroup biases. In Studies 1 and 2, we show that children choose to hear a story that contains positive information about their own group and negative information about another group rather than a story that contains negative information about their own group and positive information about the other group. In a third study, we show that children choose to present biased information to others, thus demonstrating that the effects of information selection can start to propagate through social networks. In Studies 4 and 5, we further investigate the nature of children's selective information seeking and show that children prefer ingroup-favouring information to other types of biased information and even to balanced, unbiased information. Together, this work shows that children are not merely passively recipients of social information; they play an active role in the creation and transmission of intergroup attitudes. © 2017 John Wiley & Sons Ltd.

  20. Codon usage bias in phylum Actinobacteria: relevance to environmental adaptation and host pathogenicity.

    Science.gov (United States)

    Lal, Devi; Verma, Mansi; Behura, Susanta K; Lal, Rup

    2016-10-01

    Actinobacteria are Gram-positive bacteria commonly found in soil, freshwater and marine ecosystems. In this investigation, bias in codon usages of ninety actinobacterial genomes was analyzed by estimating different indices of codon bias such as Nc (effective number of codons), SCUO (synonymous codon usage order), RSCU (relative synonymous codon usage), as well as sequence patterns of codon contexts. The results revealed several characteristic features of codon usage in Actinobacteria, as follows: 1) C- or G-ending codons are used frequently in comparison with A- and U ending codons; 2) there is a direct relationship of GC content with use of specific amino acids such as alanine, proline and glycine; 3) there is an inverse relationship between GC content and Nc estimates, 4) there is low SCUO value (Actinobacteria, extreme GC content and codon bias are driven by mutation rather than natural selection; (2) traits like aerobicity are associated with effective natural selection and therefore low GC content and low codon bias, demonstrating the role of both mutational bias and translational selection in shaping the habitat and phenotype of actinobacterial species. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  1. Attentional Bias in Math Anxiety

    Directory of Open Access Journals (Sweden)

    Orly eRubinsten

    2015-10-01

    Full Text Available Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety as well (i.e., a persistent negative reaction to math. Twenty seven participants (14 with high levels of math anxiety and 13 with low levels of math anxiety were presented with a novel computerized numerical version of the well established dot probe task. One of 6 types of prime stimuli, either math related or typically neutral, were presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks. Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in math anxiety. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words. These findings suggest that attentional bias is linked to unduly intense math anxiety symptoms.

  2. Quality of reporting and risk of bias in therapeutic otolaryngology publications.

    Science.gov (United States)

    Kaper, N M; Swart, K M A; Grolman, W; Van Der Heijden, G J M G

    2018-01-01

    High-quality trials have the potential to influence clinical practice. Ten otolaryngology journals with the highest 2011 impact factors were selected and publications from 2010 were extracted. From all medical journals, the 20 highest impact factor journals were selected, and publications related to otolaryngology for 2010 and 2011 were extracted. For all publications, the reporting quality and risk of bias were assessed. The impact factor was 1.8-2.8 for otolaryngology journals and 6.0-101.8 for medical journals. Of 1500 otolaryngology journal articles, 262 were therapeutic studies; 94 had a high reporting quality and 5 a low risk of bias. Of 10 967 medical journal articles, 76 were therapeutic studies; 57 had a high reporting quality and 8 a low risk of bias. Reporting quality was high for 45 per cent of otolaryngology-related publications and 9 per cent met quality standards. General journals had higher impact factors than otolaryngology journals. Reporting quality was higher and risk of bias lower in general journals than in otolaryngology journals. Nevertheless, 76 per cent of articles in high impact factor journals carried a high risk of bias. Better reported and designed studies are the goal, with less risk of bias, especially in otolaryngology journals.

  3. New method for eliminating the statistical bias in highly turbulent flow measurements

    International Nuclear Information System (INIS)

    Nakao, S.I.; Terao, Y.; Hirata, K.I.; Kitakyushu Industrial Research Institute, Fukuoka, Japan)

    1987-01-01

    A simple method was developed for eliminating statistical bias which can be applied to highly turbulent flows with the sparse and nonuniform seeding conditions. Unlike the method proposed so far, a weighting function was determined based on the idea that the statistical bias could be eliminated if the asymmetric form of the probability density function of the velocity data were corrected. Moreover, the data more than three standard deviations away from the mean were discarded to remove the apparent turbulent intensity resulting from noise. The present method was applied to data obtained in the wake of a block, which provided local turbulent intensities up to about 120 percent, it was found to eliminate the statistical bias with high accuracy. 9 references

  4. Neural signal for counteracting pre-action bias in the centromedian thalamic nucleus

    Directory of Open Access Journals (Sweden)

    Takafumi eMinamimoto

    2014-01-01

    Full Text Available Most of our daily actions are selected and executed involuntarily under familiar situations by the guidance of internal drives, such as motivation. The behavioral tendency or biasing towards one over others reflects the action-selection process in advance of action execution (i.e., pre-action bias. Facing unexpected situations, however, pre-action bias should be withdrawn and replaced by an alternative that is suitable for the situation (i.e., counteracting bias. To understand the neural mechanism for the counteracting process, we studied the neural activity of the thalamic centromedian (CM nucleus in monkeys performing GO-NOGO task with asymmetrical or symmetrical reward conditions. The monkeys reacted to GO signal faster in large-reward condition, indicating behavioral bias toward large reward. In contrast, they responded slowly in small-reward condition, suggesting a conflict between internal drive and external demand. We found that neurons in the CM nucleus exhibited phasic burst discharges after GO and NOGO instructions especially when they were associated with small reward. The small-reward preference was positively correlated with the strength of behavioral bias toward large reward. The small-reward preference disappeared when only NOGO action was requested. The timing of activation predicted the timing of action opposed to bias. These results suggest that CM signals the discrepancy between internal pre-action bias and external demand, and mediates the counteracting process — resetting behavioral bias and leading to execution of opposing action.

  5. Interpopulation Comparison of Sex-Biased Mortality and Sexual Size Dimorphism in Sea-Run Masu Salmon, Oncorhynchus masou.

    Science.gov (United States)

    Tamate, Tsuyoshi

    2015-08-01

    Evolutionary ecologists often expect that natural and sexual selection result in systematic co-occurrence patterns of sex-biased mortality and sexual size dimorphism (SSD) within animal species. However, whether such patterns actually occur in wild animals is poorly examined. The following expectation, the larger sex suffers higher mortality, was primarily tested here for apparently native sea-run masu salmon (Oncorhynchus masou) in three populations in Hokkaido, Japan. Field surveys on sex ratios, body sizes, and ages of smolts and returning adults revealed that two of the three populations exhibited an expected pattern, a female-biased marine mortality and SSD, but one population demonstrated an unexpected co-occurrence of male-biased marine mortality and female-biased SSD. These female-biased SSDs were attributed to faster marine growth of females because of no sex difference in smolt body size. It has been previously suggested that breeding selection favoring large size generally act more strongly in females than in males in Japanese anadromous masu, as there is a weak sexual selection on adult males but universally intensive natural selection on adult females. Thus, this hypothesis explains female-biased SSDs well in all study populations. Interpopulation variation in sex-biased mortality found here might result from differences in marine predation and/or fishing pressures, given that selection driving female-biased SSD makes females forage more aggressively than males during the marine phase. Taken together, these results raise the possibility that evolutionary forces have shaped adaptive sex-specific foraging strategies under relationships between growth and mortality, resulting in co-occurrence patterns of sex-biased mortality and SSD within animal species.

  6. Untold stories: biases and selection effects in research with victims of trafficking for sexual exploitation.

    Science.gov (United States)

    Brunovskis, Anette; Surtees, Rebecca

    2010-01-01

    Recent discussions of trafficking research have included calls for more innovative studies and new methodologies in order to move beyond the current trafficking narrative, which is often based on unrepresentative samples and overly simplified images. While new methods can potentially play a role in expanding the knowledge base on trafficking, this article argues that the solution is not entirely about applying new methods, but as much about using current methods to greater effect and with careful attention to their limitations and ethical constraints. Drawing on the authors' experience in researching trafficking issues in a number of projects over the past decade, the article outlines and exemplifies some of the methodological and ethical issues to be considered and accommodated when conducting research with trafficked persons -- including unrepresentative samples; access to respondents; selection biases by "gatekeepers" and self selection by potential respondents. Such considerations should inform not only how research is undertaken but also how this information is read and understood. Moreover, many of these considerations equally apply when considering the application of new methods within this field. The article maintains that a better understanding of how these issues come into play and inform trafficking research will translate into tools for conducting improved research in this field and, by implication, new perspectives on human trafficking.

  7. Specificity and overlap of attention and memory biases in depression.

    Science.gov (United States)

    Marchetti, Igor; Everaert, Jonas; Dainer-Best, Justin; Loeys, Tom; Beevers, Christopher G; Koster, Ernst H W

    2018-01-01

    Attentional and memory biases are viewed as crucial cognitive processes underlying symptoms of depression. However, it is still unclear whether these two biases are uniquely related to depression or whether they show substantial overlap. We investigated the degree of specificity and overlap of attentional and memory biases for depressotypic stimuli in relation to depression and anxiety by means of meta-analytic commonality analysis. By including four published studies, we considered a pool of 463 healthy and subclinically depressed individuals, different experimental paradigms, and different psychological measures. Memory bias is reliably and strongly related to depression and, specifically, to symptoms of negative mood, worthlessness, feelings of failure, and pessimism. Memory bias for negative information was minimally related to anxiety. Moreover, neither attentional bias nor the overlap between attentional and memory biases were significantly related to depression. Limitations include cross-sectional nature of the study. Our study showed that, across different paradigms and psychological measures, memory bias (and not attentional bias) represents a primary mechanism in depression. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. The relative age effect in the German Football TID Programme: biases in motor performance diagnostics and effects on single motor abilities and skills in groups of selected players.

    Science.gov (United States)

    Votteler, Andreas; Höner, Oliver

    2014-01-01

    This study examined the disturbing effects of relative age on the talent identification process in the talent development programme of the German Football Association. The bias in the selection rate was examined via the extent of relative age effects. The bias in motor performance diagnostics was analysed by comparing the motor performance of selected players with normal motor development. The mechanisms underlying the relative age biases in motor performance were examined by modelling the direct and indirect effects of relative age on single motor performance tests for sprint, running agility, dribbling and ball passing and control. Data from 10,130 selected football players from the U12 to U15 age groups were collected in autumn 2010. The birth distribution differed significantly from the reference population with approximately 61% of the players born in the first half of the year. The selection probability was approximately two times higher for players born in the first quarter of the year than for players born in the last quarter. Revised motor performance diagnostics showed better results on average for relatively younger players. Path analysis revealed significant direct and indirect relative age effects for physiologically demanding tests and almost no effects for technically demanding tests. Large sample sizes allowed high resolution in relative age with additional informational content and multivariate modelling of the complex relationships among relative age, physical development and motor performance. The results are discussed on how relative age affects the effectiveness and fairness of talent identification and development processes.

  9. Classification based upon gene expression data: bias and precision of error rates.

    Science.gov (United States)

    Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

    2007-06-01

    Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

  10. Does exclusion of protest zeros and warm-glow bidders cause selection bias in Contingent Valuation?

    DEFF Research Database (Denmark)

    Grammatikopoulou, Ioanna; Olsen, Søren Bøye; Pouta, Eija

    A great issue of concern in valuation studies is whether respondents provide trustworthy and reliable answers conditional on the perceived information. Respondent may report either a higher than the true Willingness-To-Pay (WTP) due to warm glow or embedding effects or zero WTP which is lower than...... the true WTP due to protest behavior. We conduct a contingent valuation study to estimate the WTP for conserving a Natura 2000 wetland area in Greece. We find that 54% of the positive bidders exert warm glow motivations while 29% of all responses can be classified as protest zero bids. We employ three....... Our findings show that removal of warm glow positive bidders does not distort the WTP estimate in any significant way. However, using the same approach for protest zero bidders, we find strong evidence of selection bias associated with removal of protest zero responses. Specifically, WTP estimates...

  11. Measuring Disparities: Bias in the SF-36v2 among Spanish-speaking Medical Patients

    Science.gov (United States)

    Sudano, Joseph J.; Perzynski, Adam; Love, Thomas E.; Lewis, Steven A.; Murray, Patrick M.; Huber, Gail; Ruo, Bernice; Baker, David W.

    2011-01-01

    Background Many national surveys have found substantial differences in self-reported overall health (SROH) between Spanish-speaking Hispanics and other racial/ethnic groups. However, because cultural and language differences may create measurement bias, it is unclear whether observed differences in SROH reflect true differences in health. Objectives This study uses a cross-sectional survey to investigate psychometric properties of the SF-36v2 for subjects across four racial/ethnic and language groups. Multi-group latent variable modeling was used to test increasingly stringent criteria for measurement equivalence. Subjects Our sample (N = 1281) included 383 non-Hispanic whites, 368 non-Hispanic blacks, 206 Hispanics interviewed in English and 324 Hispanics interviewed in Spanish recruited from outpatient medical clinics in two large urban areas. Results We found weak factorial invariance across the four groups. However, there was no strong factorial invariance. The overall fit of the model was substantially worse (change in CFI > .02, RMSEA change > .003) after requiring equal intercepts across all groups. Further comparisons established that the equality constraints on the intercepts for Spanish-speaking Hispanics were responsible for the decrement to model fit. Conclusions Observed differences between SF-36v2 scores for Spanish speaking Hispanics are systematically biased relative to the other three groups. The lack of strong invariance suggests the need for caution when comparing SF-36v2 mean scores of Spanish-speaking Hispanics with those of other groups. However, measurement equivalence testing for this study supports correlational or multivariate latent variable analyses of SF-36v2 responses across all four subgroups, since these analyses require only weak factorial invariance. PMID:21430580

  12. Bias, Confounding, and Interaction: Lions and Tigers, and Bears, Oh My!

    Science.gov (United States)

    Vetter, Thomas R; Mascha, Edward J

    2017-09-01

    Epidemiologists seek to make a valid inference about the causal effect between an exposure and a disease in a specific population, using representative sample data from a specific population. Clinical researchers likewise seek to make a valid inference about the association between an intervention and outcome(s) in a specific population, based upon their randomly collected, representative sample data. Both do so by using the available data about the sample variable to make a valid estimate about its corresponding or underlying, but unknown population parameter. Random error in an experiment can be due to the natural, periodic fluctuation or variation in the accuracy or precision of virtually any data sampling technique or health measurement tool or scale. In a clinical research study, random error can be due to not only innate human variability but also purely chance. Systematic error in an experiment arises from an innate flaw in the data sampling technique or measurement instrument. In the clinical research setting, systematic error is more commonly referred to as systematic bias. The most commonly encountered types of bias in anesthesia, perioperative, critical care, and pain medicine research include recall bias, observational bias (Hawthorne effect), attrition bias, misclassification or informational bias, and selection bias. A confounding variable is a factor associated with both the exposure of interest and the outcome of interest. A confounding variable (confounding factor or confounder) is a variable that correlates (positively or negatively) with both the exposure and outcome. Confounding is typically not an issue in a randomized trial because the randomized groups are sufficiently balanced on all potential confounding variables, both observed and nonobserved. However, confounding can be a major problem with any observational (nonrandomized) study. Ignoring confounding in an observational study will often result in a "distorted" or incorrect estimate of

  13. Motion, identity and the bias toward agency

    Directory of Open Access Journals (Sweden)

    Chris eFields

    2014-08-01

    Full Text Available The well-documented human bias toward agency as a cause and therefore an explanation of observed events is typically attributed to evolutionary selection for a social brain. Based on a review of developmental and adult behavioral and neurocognitive data, it is argued that the bias toward agency is a result of the default human solution, developed during infancy, to the computational requirements of object re-identification over gaps in observation of more than a few seconds. If this model is correct, overriding the bias toward agency to construct mechanistic explanations of observed events requires structure-mapping inferences, implemented by the pre-motor action planning system, that replace agents with mechanisms as causes of unobserved changes in contextual or featural properties of objects. Experiments that would test this model are discussed.

  14. Hemispheric biases and the control of visuospatial attention: an ERP study

    Directory of Open Access Journals (Sweden)

    Banich Marie T

    2005-08-01

    Full Text Available Abstract Background We examined whether individual differences in hemispheric utilization can interact with the intrinsic attentional biases of the cerebral hemispheres. Evidence suggests that the hemispheres have competing biases to direct attention contralaterally, with the left hemisphere (LH having a stronger bias than the right hemisphere. There is also evidence that individuals have characteristic biases to utilize one hemisphere more than the other for processing information, which can induce a bias to direct attention to contralateral space. We predicted that LH-biased individuals would display a strong rightward attentional bias, which would create difficulty in selectively attending to target stimuli in the left visual field (LVF as compared to right in the performance of a bilateral flanker task. Results Consistent with our hypothesis, flanker interference effects were found on the N2c event-related brain potential and error rate for LH-biased individuals in the Attend-LVF condition. The error rate effect was correlated with the degree of hemispheric utilization bias for the LH-Bias group. Conclusion We conclude that hemispheric utilization bias can enhance a hemisphere's contralateral attentional bias, at least for individuals with a LH utilization bias. Hemispheric utilization bias may play an important and largely unrecognized role in visuospatial attention.

  15. How and how much does RAD-seq bias genetic diversity estimates?

    Science.gov (United States)

    Cariou, Marie; Duret, Laurent; Charlat, Sylvain

    2016-11-08

    RAD-seq is a powerful tool, increasingly used in population genomics. However, earlier studies have raised red flags regarding possible biases associated with this technique. In particular, polymorphism on restriction sites results in preferential sampling of closely related haplotypes, so that RAD data tends to underestimate genetic diversity. Here we (1) clarify the theoretical basis of this bias, highlighting the potential confounding effects of population structure and selection, (2) confront predictions to real data from in silico digestion of full genomes and (3) provide a proof of concept toward an ABC-based correction of the RAD-seq bias. Under a neutral and panmictic model, we confirm the previously established relationship between the true polymorphism and its RAD-based estimation, showing a more pronounced bias when polymorphism is high. Using more elaborate models, we show that selection, resulting in heterogeneous levels of polymorphism along the genome, exacerbates the bias and leads to a more pronounced underestimation. On the contrary, spatial genetic structure tends to reduce the bias. We confront the neutral and panmictic model to "ideal" empirical data (in silico RAD-sequencing) using full genomes from natural populations of the fruit fly Drosophila melanogaster and the fungus Shizophyllum commune, harbouring respectively moderate and high genetic diversity. In D. melanogaster, predictions fit the model, but the small difference between the true and RAD polymorphism makes this comparison insensitive to deviations from the model. In the highly polymorphic fungus, the model captures a large part of the bias but makes inaccurate predictions. Accordingly, ABC corrections based on this model improve the estimations, albeit with some imprecisions. The RAD-seq underestimation of genetic diversity associated with polymorphism in restriction sites becomes more pronounced when polymorphism is high. In practice, this means that in many systems where

  16. Analysis of tag-position bias in MPSS technology

    Directory of Open Access Journals (Sweden)

    Rattray Magnus

    2006-04-01

    Full Text Available Abstract Background Massively Parallel Signature Sequencing (MPSS technology was recently developed as a high-throughput technology for measuring the concentration of mRNA transcripts in a sample. It has previously been observed that the position of the signature tag in a transcript (distance from 3' end can affect the measurement, but this effect has not been studied in detail. Results We quantify the effect of tag-position bias in Classic and Signature MPSS technology using published data from Arabidopsis, rice and human. We investigate the relationship between measured concentration and tag-position using nonlinear regression methods. The observed relationship is shown to be broadly consistent across different data sets. We find that there exist different and significant biases in both Classic and Signature MPSS data. For Classic MPSS data, genes with tag-position in the middle-range have highest measured abundance on average while genes with tag-position in the high-range, far from the 3' end, show a significant decrease. For Signature MPSS data, high-range tag-position genes tend to have a flatter relationship between tag-position and measured abundance. Thus, our results confirm that the Signature MPSS method fixes a substantial problem with the Classic MPSS method. For both Classic and Signature MPSS data there is a positive correlation between measured abundance and tag-position for low-range tag-position genes. Compared with the effects of mRNA length and number of exons, tag-position bias seems to be more significant in Arabadopsis. The tag-position bias is reflected both in the measured abundance of genes with a significant tag count and in the proportion of unexpressed genes identified. Conclusion Tag-position bias should be taken into consideration when measuring mRNA transcript abundance using MPSS technology, both in Classic and Signature MPSS methods.

  17. Codon Bias Patterns of E. coli's Interacting Proteins.

    Directory of Open Access Journals (Sweden)

    Maddalena Dilucca

    Full Text Available Synonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms. The biological meaning of this phenomenon, known as codon usage bias, is still controversial. In order to shed light on this point, we propose a new codon bias index, CompAI, that is based on the competition between cognate and near-cognate tRNAs during translation, without being tuned to the usage bias of highly expressed genes. We perform a genome-wide evaluation of codon bias for E.coli, comparing CompAI with other widely used indices: tAI, CAI, and Nc. We show that CompAI and tAI capture similar information by being positively correlated with gene conservation, measured by the Evolutionary Retention Index (ERI, and essentiality, whereas, CAI and Nc appear to be less sensitive to evolutionary-functional parameters. Notably, the rate of variation of tAI and CompAI with ERI allows to obtain sets of genes that consistently belong to specific clusters of orthologous genes (COGs. We also investigate the correlation of codon bias at the genomic level with the network features of protein-protein interactions in E.coli. We find that the most densely connected communities of the network share a similar level of codon bias (as measured by CompAI and tAI. Conversely, a small difference in codon bias between two genes is, statistically, a prerequisite for the corresponding proteins to interact. Importantly, among all codon bias indices, CompAI turns out to have the most coherent distribution over the communities of the interactome, pointing to the significance of competition among cognate and near-cognate tRNAs for explaining codon usage adaptation. Notably, CompAI may potentially correlate with translation speed measurements, by accounting for the specific delay induced by wobble-pairing between codons and anticodons.

  18. Attentional bias for food cues in advertising among overweight and hungry children

    NARCIS (Netherlands)

    Folkvord, F.; Anschutz, D.J.; Buijzen, M.A.

    2015-01-01

    Attentional bias theory suggests that an increased motivation to receive or avoid a rewarding substance elevates automatic selective attention toward cues that are related to that specific substance. Until now, no study has examined attentional bias toward food cues in food advertisements, even

  19. Unconscious bias against introverts in the recruitment and selection process

    OpenAIRE

    Braathen, Vilde Marie Lie; Sørensen, Martine Waller

    2017-01-01

    Masteroppgave(MSc) in Master of Science in Leadership and Organizational Psychology - Handelshøyskolen BI, 2017 The current study is an attempt to expand upon the limited research area of unconscious bias against certain personality types that may emerge during the employment interview. We proposed that an extraverted personality type would be favoured in the employment interview, and this was based on the notion that the interview situation, which is inherently a social intera...

  20. Effectiveness of the Comalli Stroop Test as a measure of negative response bias.

    Science.gov (United States)

    Arentsen, Timothy J; Boone, Kyle Brauer; Lo, Tracy T Y; Goldberg, Hope E; Cottingham, Maria E; Victor, Tara L; Ziegler, Elizabeth; Zeller, Michelle A

    2013-01-01

    Practice guidelines recommend the use of multiple performance validity tests (PVTs) to detect noncredible performance during neuropsychological evaluations, and PVTs embedded in standard cognitive tests achieve this goal most efficiently. The present study examined the utility of the Comalli version of the Stroop Test as a measure of response bias in a large sample of "real world" noncredible patients (n = 129) as compared with credible neuropsychology clinic patients (n=233). The credible group performed significantly better than the noncredible group on all trials, but particularly on word-reading (Stroop A) and color-naming (Stroop B); cut-scores for Stroop A and Stroop B trials were associated with moderate sensitivity (49-53%) as compared to the low sensitivity found for the color interference trial (29%). Some types of diagnoses (including learning disability, severe traumatic brain injury, psychosis, and depression), very advanced age (⩾80), and lowered IQ were associated with increased rates of false positive identifications, suggesting the need for some adjustments to cut-offs in these subgroups. Despite some previous reports of an inverted Stroop effect (i.e., color-naming worse than color interference) in noncredible subjects, individual Stroop word reading and color naming trials were much more effective in identifying response bias.

  1. The role of vision, speed, and attention in overcoming directional biases during arm movements.

    Science.gov (United States)

    Dounskaia, Natalia; Goble, Jacob A

    2011-03-01

    Previous research has revealed directional biases (preferences to select movements in specific directions) during horizontal arm movements with the use of a free-stroke drawing task. The biases were interpreted as a result of a tendency to generate motion at either the shoulder or elbow (leading joint) and move the other (subordinate) joint predominantly passively to avoid neural effort for control of interaction torque. Here, we examined influence of vision, movement speed, and attention on the directional biases. Participants performed the free-stroke drawing task, producing center-out strokes in randomly selected directions. Movements were performed with and without vision and at comfortable and fast pace. A secondary, cognitive task was used to distract attention. Preferred directions remained the same in all conditions. Bias strength mildly increased without vision, especially during fast movements. Striking increases in bias strength were caused by the secondary task, pointing to additional cognitive load associated with selection of movements in the non-preferred directions. Further analyses demonstrated that the tendency to minimize active interference with interaction torque at the subordinate joint matched directional biases in all conditions. This match supports the explanation of directional biases as a result of a tendency to minimize neural effort for interaction torque control. The cognitive load may enhance this tendency in two ways, directly, by reducing neural capacity for interaction torque control, and indirectly, by decreasing capacity of working memory that stores visited directions. The obtained results suggest strong directional biases during daily activities because natural arm movements usually subserve cognitive tasks.

  2. Estimation of Received Signal Strength Distribution for Smart Meters with Biased Measurement Data Set

    DEFF Research Database (Denmark)

    Kielgast, Mathias Rønholt; Rasmussen, Anders Charly; Laursen, Mathias Hjorth

    2017-01-01

    This letter presents an experimental study and a novel modelling approach of the wireless channel of smart utility meters placed in basements or sculleries. The experimental data consist of signal strength measurements of consumption report packets. Since such packets are only registered if they ......This letter presents an experimental study and a novel modelling approach of the wireless channel of smart utility meters placed in basements or sculleries. The experimental data consist of signal strength measurements of consumption report packets. Since such packets are only registered...... if they can be decoded by the receiver, the part of the signal strength distribution that falls below the receiver sensitivity threshold is not observable. We combine a Rician fading model with a bias function that captures the cut-off in the observed signal strength measurements. Two sets of experimental...... data are analysed. It is shown that the proposed method offers an approximation of the distribution of the signal strength measurements that is better than a naïve Rician fitting....

  3. Using different Facebook advertisements to recruit men for an online mental health study: Engagement and selection bias

    Directory of Open Access Journals (Sweden)

    Isabella Choi

    2017-06-01

    Full Text Available A growing number of researchers are using Facebook to recruit for a range of online health, medical, and psychosocial studies. There is limited research on the representativeness of participants recruited from Facebook, and the content is rarely mentioned in the methods, despite some suggestion that the advertisement content affects recruitment success. This study explores the impact of different Facebook advertisement content for the same study on recruitment rate, engagement, and participant characteristics. Five Facebook advertisement sets (“resilience”, “happiness”, “strength”, “mental fitness”, and “mental health” were used to recruit male participants to an online mental health study which allowed them to find out about their mental health and wellbeing through completing six measures. The Facebook advertisements recruited 372 men to the study over a one month period. The cost per participant from the advertisement sets ranged from $0.55 to $3.85 Australian dollars. The “strength” advertisements resulted in the highest recruitment rate, but participants from this group were least engaged in the study website. The “strength” and “happiness” advertisements recruited more younger men. Participants recruited from the “mental health” advertisements had worse outcomes on the clinical measures of distress, wellbeing, strength, and stress. This study confirmed that different Facebook advertisement content leads to different recruitment rates and engagement with a study. Different advertisement also leads to selection bias in terms of demographic and mental health characteristics. Researchers should carefully consider the content of social media advertisements to be in accordance with their target population and consider reporting this to enable better assessment of generalisability.

  4. Working memory biasing of visual perception without awareness.

    Science.gov (United States)

    Pan, Yi; Lin, Bingyuan; Zhao, Yajun; Soto, David

    2014-10-01

    Previous research has demonstrated that the contents of visual working memory can bias visual processing in favor of matching stimuli in the scene. However, the extent to which such top-down, memory-driven biasing of visual perception is contingent on conscious awareness remains unknown. Here we showed that conscious awareness of critical visual cues is dispensable for working memory to bias perceptual selection mechanisms. Using the procedure of continuous flash suppression, we demonstrated that "unseen" visual stimuli during interocular suppression can gain preferential access to awareness if they match the contents of visual working memory. Strikingly, the very same effect occurred even when the visual cue to be held in memory was rendered nonconscious by masking. Control experiments ruled out the alternative accounts of repetition priming and different detection criteria. We conclude that working memory biases of visual perception can operate in the absence of conscious awareness.

  5. Attentional bias for craving-related (chocolate) food cues.

    Science.gov (United States)

    Kemps, Eva; Tiggemann, Marika

    2009-12-01

    In this study, we investigated attentional biases for craving-related food cues. A pictorial dot probe task was used to assess selective attentional processing of one particular highly desired food, namely chocolate, relative to that of other highly desired foods. In Experiment 1, we examined biased processing of chocolate cues in habitual (trait) chocolate cravers, whereas in Experiment 2 we investigated the effect of experimentally induced (state) chocolate cravings on such processing. As predicted, habitual chocolate cravers (Experiment 1) and individuals in whom a craving for chocolate was temporarily induced (Experiment 2) showed speeded detection of probes replacing chocolate-related pictures, demonstrating an attentional bias for chocolate cues. Subsequent examination indicated that in both experiments the observed attentional biases stemmed from difficulty in disengaging attention from chocolate cues rather than from a shift of attention toward such cues. The findings have important theoretical and practical implications.

  6. Biases in GNSS-Data Processing

    Science.gov (United States)

    Schaer, S. C.; Dach, R.; Lutz, S.; Meindl, M.; Beutler, G.

    2010-12-01

    Within the Global Positioning System (GPS) traditionally different types of pseudo-range measurements (P-code, C/A-code) are available on the first frequency that are tracked by the receivers with different technologies. For that reason, P1-C1 and P1-P2 Differential Code Biases (DCB) need to be considered in a GPS data processing with a mix of different receiver types. Since the Block IIR-M series of GPS satellites also provide C/A-code on the second frequency, P2-C2 DCB need to be added to the list of biases for maintenance. Potential quarter-cycle biases between different phase observables (specifically L2P and L2C) are another issue. When combining GNSS (currently GPS and GLONASS), careful consideration of inter-system biases (ISB) is indispensable, in particular when an adequate combination of individual GLONASS clock correction results from different sources (using, e.g., different software packages) is intended. Facing the GPS and GLONASS modernization programs and the upcoming GNSS, like the European Galileo and the Chinese Compass, an increasing number of types of biases is expected. The Center for Orbit Determination in Europe (CODE) is monitoring these GPS and GLONASS related biases for a long time based on RINEX files of the tracking network of the International GNSS Service (IGS) and in the frame of the data processing as one of the global analysis centers of the IGS. Within the presentation we give an overview on the stability of the biases based on the monitoring. Biases derived from different sources are compared. Finally, we give an outlook on the potential handling of such biases with the big variety of signals and systems expected in the future.

  7. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  8. Social biases determine spatiotemporal sparseness of ciliate mating heuristics.

    Science.gov (United States)

    Clark, Kevin B

    2012-01-01

    Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate's initial subjective bias, responsiveness, or preparedness, as defined by Stevens' Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The present

  9. Social biases determine spatiotemporal sparseness of ciliate mating heuristics

    Science.gov (United States)

    2012-01-01

    Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate’s initial subjective bias, responsiveness, or preparedness, as defined by Stevens’ Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The

  10. Assessing the extent of non-stationary biases in GCMs

    Science.gov (United States)

    Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

    2017-06-01

    General circulation models (GCMs) are the main tools for estimating changes in the climate for the future. The imperfect representation of climate models introduces biases in the simulations that need to be corrected prior to their use for impact assessments. Bias correction methods generally assume that the bias calculated over the historical period does not change and can be applied to the future. This study investigates this assumption by considering the extent and nature of bias non-stationarity using 20th century precipitation and temperature simulations from six CMIP5 GCMs across Australia. Four statistics (mean, standard deviation, 10th and 90th quantiles) in monthly and seasonal biases are obtained for three different time window lengths (10, 25 and 33 years) to examine the properties of bias over time. This approach is repeated for two different phases of the Interdecadal Pacific Oscillation (IPO), which is known to have strong influences on the Australian climate. It is found that bias non-stationarity at decadal timescales is indeed an issue over some of Australia for some GCMs. When considering interdecadal variability there are significant difference in the bias between positive and negative phases of the IPO. Regional analyses confirmed these findings with the largest differences seen on the east coast of Australia, where IPO impacts tend to be the strongest. The nature of the bias non-stationarity found in this study suggests that it will be difficult to modify existing bias correction approaches to account for non-stationary biases. A more practical approach for impact assessments that use bias correction maybe to use a selection of GCMs where the assumption of bias non-stationarity holds.

  11. A study of the Pythia 8 description of ATLAS minimum bias measurements with the Donnachie-Landshoff diffractive model

    CERN Document Server

    The ATLAS collaboration

    2016-01-01

    We present a new tune of the Pythia8 event generator, titled ``A3'' and suitable for inclusive QCD modelling, including minimum bias physics and pile-up overlay. The tuning uses the early Run~2 charged particle distribution and inelastic cross section results from ATLAS in addition to the Run~1 data used to construct previous minimum-bias tunes. For the first time, the tuning included a consideration of diffraction modelling parameters and a diffractive model other than the Pythia8 default is used in the final configuration. That resulted in a better descriptions of the measured inelastic cross-sections, and similar or better level of agreement compared to the currently used A2 tune for other distributions considered.

  12. Mutational Biases and GC-Biased Gene Conversion Affect GC Content in the Plastomes of Dendrobium Genus

    Directory of Open Access Journals (Sweden)

    Zhitao Niu

    2017-11-01

    Full Text Available The variation of GC content is a key genome feature because it is associated with fundamental elements of genome organization. However, the reason for this variation is still an open question. Different kinds of hypotheses have been proposed to explain the variation of GC content during genome evolution. However, these hypotheses have not been explicitly investigated in whole plastome sequences. Dendrobium is one of the largest genera in the orchid species. Evolutionary studies of the plastomic organization and base composition are limited in this genus. In this study, we obtained the high-quality plastome sequences of D. loddigesii and D. devonianum. The comparison results showed a nearly identical organization in Dendrobium plastomes, indicating that the plastomic organization is highly conserved in Dendrobium genus. Furthermore, the impact of three evolutionary forces—selection, mutational biases, and GC-biased gene conversion (gBGC—on the variation of GC content in Dendrobium plastomes was evaluated. Our results revealed: (1 consistent GC content evolution trends and mutational biases in single-copy (SC and inverted repeats (IRs regions; and (2 that gBGC has influenced the plastome-wide GC content evolution. These results suggest that both mutational biases and gBGC affect GC content in the plastomes of Dendrobium genus.

  13. Mutational Biases and GC-Biased Gene Conversion Affect GC Content in the Plastomes of Dendrobium Genus

    Science.gov (United States)

    Niu, Zhitao; Xue, Qingyun; Wang, Hui; Xie, Xuezhu; Zhu, Shuying; Liu, Wei; Ding, Xiaoyu

    2017-01-01

    The variation of GC content is a key genome feature because it is associated with fundamental elements of genome organization. However, the reason for this variation is still an open question. Different kinds of hypotheses have been proposed to explain the variation of GC content during genome evolution. However, these hypotheses have not been explicitly investigated in whole plastome sequences. Dendrobium is one of the largest genera in the orchid species. Evolutionary studies of the plastomic organization and base composition are limited in this genus. In this study, we obtained the high-quality plastome sequences of D. loddigesii and D. devonianum. The comparison results showed a nearly identical organization in Dendrobium plastomes, indicating that the plastomic organization is highly conserved in Dendrobium genus. Furthermore, the impact of three evolutionary forces—selection, mutational biases, and GC-biased gene conversion (gBGC)—on the variation of GC content in Dendrobium plastomes was evaluated. Our results revealed: (1) consistent GC content evolution trends and mutational biases in single-copy (SC) and inverted repeats (IRs) regions; and (2) that gBGC has influenced the plastome-wide GC content evolution. These results suggest that both mutational biases and gBGC affect GC content in the plastomes of Dendrobium genus. PMID:29099062

  14. Velocity Segregation and Systematic Biases In Velocity Dispersion Estimates with the SPT-GMOS Spectroscopic Survey

    Science.gov (United States)

    Bayliss, Matthew. B.; Zengo, Kyle; Ruel, Jonathan; Benson, Bradford A.; Bleem, Lindsey E.; Bocquet, Sebastian; Bulbul, Esra; Brodwin, Mark; Capasso, Raffaella; Chiu, I.-non; McDonald, Michael; Rapetti, David; Saro, Alex; Stalder, Brian; Stark, Antony A.; Strazzullo, Veronica; Stubbs, Christopher W.; Zenteno, Alfredo

    2017-03-01

    The velocity distribution of galaxies in clusters is not universal; rather, galaxies are segregated according to their spectral type and relative luminosity. We examine the velocity distributions of different populations of galaxies within 89 Sunyaev Zel’dovich (SZ) selected galaxy clusters spanning 0.28GMOS spectroscopic survey, supplemented by additional published spectroscopy, resulting in a final spectroscopic sample of 4148 galaxy spectra—2868 cluster members. The velocity dispersion of star-forming cluster galaxies is 17 ± 4% greater than that of passive cluster galaxies, and the velocity dispersion of bright (m< {m}* -0.5) cluster galaxies is 11 ± 4% lower than the velocity dispersion of our total member population. We find good agreement with simulations regarding the shape of the relationship between the measured velocity dispersion and the fraction of passive versus star-forming galaxies used to measure it, but we find a small offset between this relationship as measured in data and simulations, which suggests that our dispersions are systematically low by as much as 3% relative to simulations. We argue that this offset could be interpreted as a measurement of the effective velocity bias that describes the ratio of our observed velocity dispersions and the intrinsic velocity dispersion of dark matter particles in a published simulation result. Measuring velocity bias in this way suggests that large spectroscopic surveys can improve dispersion-based mass-observable scaling relations for cosmology even in the face of velocity biases, by quantifying and ultimately calibrating them out.

  15. Intrinsic frequency biases and profiles across human cortex.

    Science.gov (United States)

    Mellem, Monika S; Wohltjen, Sophie; Gotts, Stephen J; Ghuman, Avniel Singh; Martin, Alex

    2017-11-01

    Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical. NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across

  16. Blind Measurement Selection: A Random Matrix Theory Approach

    KAUST Repository

    Elkhalil, Khalil

    2016-12-14

    This paper considers the problem of selecting a set of $k$ measurements from $n$ available sensor observations. The selected measurements should minimize a certain error function assessing the error in estimating a certain $m$ dimensional parameter vector. The exhaustive search inspecting each of the $n\\\\choose k$ possible choices would require a very high computational complexity and as such is not practical for large $n$ and $k$. Alternative methods with low complexity have recently been investigated but their main drawbacks are that 1) they require perfect knowledge of the measurement matrix and 2) they need to be applied at the pace of change of the measurement matrix. To overcome these issues, we consider the asymptotic regime in which $k$, $n$ and $m$ grow large at the same pace. Tools from random matrix theory are then used to approximate in closed-form the most important error measures that are commonly used. The asymptotic approximations are then leveraged to select properly $k$ measurements exhibiting low values for the asymptotic error measures. Two heuristic algorithms are proposed: the first one merely consists in applying the convex optimization artifice to the asymptotic error measure. The second algorithm is a low-complexity greedy algorithm that attempts to look for a sufficiently good solution for the original minimization problem. The greedy algorithm can be applied to both the exact and the asymptotic error measures and can be thus implemented in blind and channel-aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also presented and sustain the efficiency of the proposed blind methods in reaching the performances of channel-aware algorithms.

  17. Biased Supervision

    OpenAIRE

    Josse Delfgaauw; Michiel Souverijn

    2014-01-01

    markdownabstract__Abstract__ When verifiable performance measures are imperfect, organizations often resort to subjective performance pay. This may give supervisors the power to direct employees towards tasks that mainly benefit the supervisor rather than the organization. We cast a principal-supervisor-agent model in a multitask setting, where the supervisor has an intrinsic preference towards specific tasks. We show that subjective performance pay based on evaluation by a biased supervisor ...

  18. Confirmation bias in web-based search: a randomized online study on the effects of expert information and social tags on information search and evaluation.

    Science.gov (United States)

    Schweiger, Stefan; Oeberst, Aileen; Cress, Ulrike

    2014-03-26

    The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective. The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts' evaluations. A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts' blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants' treatment recommendation after information search. Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; t173=7.67, Pinformation search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (F2,168=10.61, Pinformation as presented in blog posts, compared to supporting expert information (n=81), decreased the bias in information search with regard to blog post selection (F1,168=4.32, P=.04, partial eta squared=0.025). No significant effects were found for treatment recommendation (Ps>.33). We conclude that the psychotherapy bias is most effectively

  19. Risk of bias and confounding of observational studies of Zika virus infection: A scoping review of research protocols.

    Science.gov (United States)

    Reveiz, Ludovic; Haby, Michelle M; Martínez-Vega, Ruth; Pinzón-Flores, Carlos E; Elias, Vanessa; Smith, Emma; Pinart, Mariona; Broutet, Nathalie; Becerra-Posada, Francisco; Aldighieri, Sylvain; Van Kerkhove, Maria D

    2017-01-01

    Given the severity and impact of the current Zika virus (ZIKV) outbreak in the Americas, numerous countries have rushed to develop research studies to assess ZIKV and its potential health consequences. In an effort to ensure that studies are comprehensive, both internally and externally valid, and with reliable results, the World Health Organization, the Pan American Health Organization, Institut Pasteur, the networks of Fiocruz, the Consortia for the Standardization of Influenza Seroepidemiology (CONSISE) and the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) have generated six standardized clinical and epidemiological research protocols and questionnaires to address key public health questions on ZIKV. We conducted a systematic search of ongoing study protocols related to ZIKV research. We analyzed the content of protocols of 32 cohort studies and 13 case control studies for systematic bias that could produce erroneous results. Additionally we aimed to characterize the risks of bias and confounding in observational studies related to ZIKV and to propose ways to minimize them, including the use of six newly standardized research protocols. Observational studies of ZIKV face an array of challenges, including measurement of exposure and outcomes (microcephaly and Guillain-Barré Syndrome). Potential confounders need to be measured where known and controlled for in the analysis. Selection bias due to non-random selection is a significant issue, particularly in the case-control design, and losses to follow-up is equally important for the cohort design. Observational research seeking to answer key questions on the ZIKV should consider these restrictions and take precautions to minimize bias in an effort to provide reliable and valid results. Utilization of the standardized research protocols developed by the WHO, PAHO, Institut Pasteur, and CONSISE will harmonize the key methodological aspects of each study design to minimize bias at

  20. Risk of bias and confounding of observational studies of Zika virus infection: A scoping review of research protocols.

    Directory of Open Access Journals (Sweden)

    Ludovic Reveiz

    Full Text Available Given the severity and impact of the current Zika virus (ZIKV outbreak in the Americas, numerous countries have rushed to develop research studies to assess ZIKV and its potential health consequences. In an effort to ensure that studies are comprehensive, both internally and externally valid, and with reliable results, the World Health Organization, the Pan American Health Organization, Institut Pasteur, the networks of Fiocruz, the Consortia for the Standardization of Influenza Seroepidemiology (CONSISE and the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC have generated six standardized clinical and epidemiological research protocols and questionnaires to address key public health questions on ZIKV.We conducted a systematic search of ongoing study protocols related to ZIKV research. We analyzed the content of protocols of 32 cohort studies and 13 case control studies for systematic bias that could produce erroneous results. Additionally we aimed to characterize the risks of bias and confounding in observational studies related to ZIKV and to propose ways to minimize them, including the use of six newly standardized research protocols.Observational studies of ZIKV face an array of challenges, including measurement of exposure and outcomes (microcephaly and Guillain-Barré Syndrome. Potential confounders need to be measured where known and controlled for in the analysis. Selection bias due to non-random selection is a significant issue, particularly in the case-control design, and losses to follow-up is equally important for the cohort design.Observational research seeking to answer key questions on the ZIKV should consider these restrictions and take precautions to minimize bias in an effort to provide reliable and valid results. Utilization of the standardized research protocols developed by the WHO, PAHO, Institut Pasteur, and CONSISE will harmonize the key methodological aspects of each study design to

  1. Bias due to differential participation in case-control studies and review of available approaches for adjustment.

    Science.gov (United States)

    Aigner, Annette; Grittner, Ulrike; Becher, Heiko

    2018-01-01

    Low response rates in epidemiologic research potentially lead to the recruitment of a non-representative sample of controls in case-control studies. Problems in the unbiased estimation of odds ratios arise when characteristics causing the probability of participation are associated with exposure and outcome. This is a specific setting of selection bias and a realistic hazard in many case-control studies. This paper formally describes the problem and shows its potential extent, reviews existing approaches for bias adjustment applicable under certain conditions, compares and applies them. We focus on two scenarios: a characteristic C causing differential participation of controls is linked to the outcome through its association with risk factor E (scenario I), and C is additionally a genuine risk factor itself (scenario II). We further assume external data sources are available which provide an unbiased estimate of C in the underlying population. Given these scenarios, we (i) review available approaches and their performance in the setting of bias due to differential participation; (ii) describe two existing approaches to correct for the bias in both scenarios in more detail; (iii) present the magnitude of the resulting bias by simulation if the selection of a non-representative sample is ignored; and (iv) demonstrate the approaches' application via data from a case-control study on stroke. The bias of the effect measure for variable E in scenario I and C in scenario II can be large and should therefore be adjusted for in any analysis. It is positively associated with the difference in response rates between groups of the characteristic causing differential participation, and inversely associated with the total response rate in the controls. Adjustment in a standard logistic regression framework is possible in both scenarios if the population distribution of the characteristic causing differential participation is known or can be approximated well.

  2. Suspected survivor bias in case-control studies: stratify on survival time and use a negative control.

    Science.gov (United States)

    van Rein, Nienke; Cannegieter, Suzanne C; Rosendaal, Frits R; Reitsma, Pieter H; Lijfering, Willem M

    2014-02-01

    Selection bias in case-control studies occurs when control selection is inappropriate. However, selection bias due to improper case sampling is less well recognized. We describe how to recognize survivor bias (i.e., selection on exposed cases) and illustrate this with an example study. A case-control study was used to analyze the effect of statins on major bleedings during treatment with vitamin K antagonists. A total of 110 patients who experienced such bleedings were included 18-1,018 days after the bleeding complication and matched to 220 controls. A protective association of major bleeding for exposure to statins (odds ratio [OR]: 0.56; 95% confidence interval: 0.29-1.08) was found, which did not become stronger after adjustment for confounding factors. These observations lead us to suspect survivor bias. To identify this bias, results were stratified on time between bleeding event and inclusion, and repeated for a negative control (an exposure not related to survival): blood group non-O. The ORs for exposure to statins increased gradually to 1.37 with shorter time between outcome and inclusion, whereas ORs for the negative control remained constant, confirming our hypothesis. We recommend the presented method to check for overoptimistic results, that is, survivor bias in case-control studies. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Galaxy bias from galaxy-galaxy lensing in the DES Science Verification Data

    Energy Technology Data Exchange (ETDEWEB)

    Prat, J.; et al.

    2016-09-26

    We present a measurement of galaxy-galaxy lensing around a magnitude-limited ($i_{AB} < 22.5$) sample of galaxies selected from the Dark Energy Survey Science Verification (DES-SV) data. We split these lenses into three photometric-redshift bins from 0.2 to 0.8, and determine the product of the galaxy bias $b$ and cross-correlation coefficient between the galaxy and dark matter overdensity fields $r$ in each bin, using scales above 4 Mpc/$h$ comoving, where we find the linear bias model to be valid given our current uncertainties. We compare our galaxy bias results from galaxy-galaxy lensing with those obtained from galaxy clustering (Crocce et al. 2016) and CMB lensing (Giannantonio et al. 2016) for the same sample of galaxies, and find our measurements to be in good agreement with those in Crocce et al. (2016), while, in the lowest redshift bin ($z\\sim0.3$), they show some tension with the findings in Giannantonio et al. (2016). Our results are found to be rather insensitive to a large range of systematic effects. We measure $b\\cdot r$ to be $0.87\\pm 0.11$, $1.12 \\pm 0.16$ and $1.24\\pm 0.23$, respectively for the three redshift bins of width $\\Delta z = 0.2$ in the range $0.2measured biases at the 10-20% level, but it does not alter the main conclusion of this work: when comparing with Crocce et al. (2016) we do not find strong evidence for a cross-correlation parameter significantly below one in this galaxy sample, except possibly at the lowest redshift bin ($z\\sim 0.3$), where we find $r = 0.71 \\pm 0.11$ when using TPZ, and $0.83 \\pm 0.12$ with BPZ, assuming the difference between the results from the two probes can be solely attributed to the cross-correlation parameter.

  4. Electron-beam-induced current measurements with applied bias provide insight to locally resolved acceptor concentrations at p-n junctions

    Directory of Open Access Journals (Sweden)

    D. Abou-Ras

    2015-07-01

    Full Text Available Electron-beam-induced current (EBIC measurements have been employed for the investigation of the local electrical properties existing at various types of electrical junctions during the past decades. In the standard configuration, the device under investigation is analyzed under short-circuit conditions. Further insight into the function of the electrical junction can be obtained when applying a bias voltage. The present work gives insight into how EBIC measurements at applied bias can be conducted at the submicrometer level, at the example of CuInSe2 solar cells. From the EBIC profiles acquired across ZnO/CdS/CuInSe2/Mo stacks exhibiting p-n junctions with different net doping densities in the CuInSe2 layers, values for the width of the space-charge region, w, were extracted. For all net doping densities, these values decreased with increasing applied voltage. Assuming a linear relationship between w2 and the applied voltage, the resulting net doping densities agreed well with the ones obtained by means of capacitance-voltage measurements.

  5. The effects of self-focus on attentional biases in social anxiety:An ERP study.

    Science.gov (United States)

    Judah, Matt R; Grant, DeMond M; Carlisle, Nancy B

    2016-06-01

    Cognitive theories of social anxiety disorder suggest that biased attention plays a key role in maintaining symptoms. These biases include self-focus and attention to socially threatening stimuli in the environment. The goal of this study was to utilize ERPs that are elicited by a change detection task to examine biases in selective attention (i.e., N2pc) and working memory maintenance (i.e., contralateral delay activity; CDA). Additionally, the effect of self-focus was examined using false heart rate feedback. In support of the manipulation, self-focus cues resulted in greater self-reported self-consciousness and task interference, enhanced anterior P2 amplitude and reduced SPN amplitude. Moreover, P2 amplitude for self-focus cues was correlated with reduced task performance for socially anxious subjects only. The difference in P2 amplitude between self-focus and standard cues was correlated with social anxiety independent of depression. As hypothesized, socially anxious participants (n = 20) showed early selection and maintenance of disgust faces relative to neutral faces as indicated by the N2pc and CDA components. Nonanxious controls (n = 22) did not show these biases. During self-focus cues, controls showed marginal evidence of biased selection for disgust faces, whereas socially anxious subjects showed no bias in this condition. Controls showed an ipsilateral delay activity after being cued to attend to one hemifield. Overall, this study supports early and persistent attentional bias for social threat in socially anxious individuals. Furthermore, self-focus may disrupt these biases. These findings and supplementary data are discussed in light of cognitive models of social anxiety disorder, recent empirical findings, and treatment.

  6. A test to identify judgement bias in mice

    NARCIS (Netherlands)

    Boleij, H.; van't Klooster, J.; Lavrijsen, M.; Kirchhoff, S.; Arndt, S.S.; Ohl, F.

    2012-01-01

    Emotional states are known to affect cognitive processes. For example highly anxious individuals interpret ambiguous stimuli more negatively than low anxious people, an effect called negative judgement bias. Recently, the measurement of judgement bias has been used to try and indicate emotional

  7. Is racial bias malleable? Whites' lay theories of racial bias predict divergent strategies for interracial interactions.

    Science.gov (United States)

    Neel, Rebecca; Shapiro, Jenessa R

    2012-07-01

    How do Whites approach interracial interactions? We argue that a previously unexamined factor-beliefs about the malleability of racial bias-guides Whites' strategies for difficult interracial interactions. We predicted and found that those who believe racial bias is malleable favor learning-oriented strategies such as taking the other person's perspective and trying to learn why an interaction is challenging, whereas those who believe racial bias is fixed favor performance-oriented strategies such as overcompensating in the interaction and trying to end the interaction as quickly as possible. Four studies support these predictions. Whether measured (Studies 1, 3, and 4) or manipulated (Study 2), beliefs that racial bias is fixed versus malleable yielded these divergent strategies for difficult interracial interactions. Furthermore, beliefs about the malleability of racial bias are distinct from related constructs (e.g., prejudice and motivations to respond without prejudice; Studies 1, 3, and 4) and influence self-reported (Studies 1-3) and actual (Study 4) strategies in imagined (Studies 1-2) and real (Studies 3-4) interracial interactions. Together, these findings demonstrate that beliefs about the malleability of racial bias influence Whites' approaches to and strategies within interracial interactions. PsycINFO Database Record (c) 2012 APA, all rights reserved

  8. Rapid Evolution of Ovarian-Biased Genes in the Yellow Fever Mosquito (Aedes aegypti).

    Science.gov (United States)

    Whittle, Carrie A; Extavour, Cassandra G

    2017-08-01

    Males and females exhibit highly dimorphic phenotypes, particularly in their gonads, which is believed to be driven largely by differential gene expression. Typically, the protein sequences of genes upregulated in males, or male-biased genes, evolve rapidly as compared to female-biased and unbiased genes. To date, the specific study of gonad-biased genes remains uncommon in metazoans. Here, we identified and studied a total of 2927, 2013, and 4449 coding sequences (CDS) with ovary-biased, testis-biased, and unbiased expression, respectively, in the yellow fever mosquito Aedes aegypti The results showed that ovary-biased and unbiased CDS had higher nonsynonymous to synonymous substitution rates (dN/dS) and lower optimal codon usage (those codons that promote efficient translation) than testis-biased genes. Further, we observed higher dN/dS in ovary-biased genes than in testis-biased genes, even for genes coexpressed in nonsexual (embryo) tissues. Ovary-specific genes evolved exceptionally fast, as compared to testis- or embryo-specific genes, and exhibited higher frequency of positive selection. Genes with ovary expression were preferentially involved in olfactory binding and reception. We hypothesize that at least two potential mechanisms could explain rapid evolution of ovary-biased genes in this mosquito: (1) the evolutionary rate of ovary-biased genes may be accelerated by sexual selection (including female-female competition or male-mate choice) affecting olfactory genes during female swarming by males, and/or by adaptive evolution of olfactory signaling within the female reproductive system ( e.g. , sperm-ovary signaling); and/or (2) testis-biased genes may exhibit decelerated evolutionary rates due to the formation of mating plugs in the female after copulation, which limits male-male sperm competition. Copyright © 2017 by the Genetics Society of America.

  9. Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

    Directory of Open Access Journals (Sweden)

    Fernando A. Auat Cheein

    2013-01-01

    Full Text Available Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of the most significant measurement from both an estimation convergence perspective and the covariance matrix associated with the measurement. The selection criterion is independent from the nature of the measured variable. This criterion is used in conjunction with three Gaussian-based algorithms: the EIF (Extended Information Filter, the EKF (Extended Kalman Filter and the UKF (Unscented Kalman Filter. Nevertheless, the measurement selection criterion shown herein can also be applied to other Gaussian-based algorithms. Although this work is focused on environment modeling, the results shown herein can be applied to other Gaussian-based algorithm implementations. Mathematical descriptions and implementation results that validate the proposal are also included in this work.

  10. An experimental investigation of recruitment bias in eating pathology research.

    Science.gov (United States)

    Moss, Erin L; von Ranson, Kristin M

    2006-04-01

    Previous, uncontrolled research has suggested a bias may exist in recruiting participants for eating disorder research. Recruitment biases may affect sample representativeness and generalizability of findings. This experiment investigated whether revealing that a study's topic was related to eating disorders created a self-selection bias. Young women at a university responded to advertisements containing contrasting information about the nature of a single study. We recruited one group by advertising the study under the title "Disordered Eating in Young Women" (n = 251) and another group using the title "Consumer Preferences" (n = 259). Results indicated similar levels of eating pathology in both groups, so the different recruitment techniques did not engender self-selection. However, the consumer preferences group scored higher in self-reported social desirability. The level of information conveyed in study advertising does not impact reporting of eating disturbances among nonclinical samples, although there is evidence social desirability might. 2006 by Wiley Periodicals, Inc.

  11. Can decision biases improve insurance outcomes? An experiment on status quo bias in health insurance choice.

    Science.gov (United States)

    Krieger, Miriam; Felder, Stefan

    2013-06-19

    Rather than conforming to the assumption of perfect rationality in neoclassical economic theory, decision behavior has been shown to display a host of systematic biases. Properly understood, these patterns can be instrumentalized to improve outcomes in the public realm. We conducted a laboratory experiment to study whether decisions over health insurance policies are subject to status quo bias and, if so, whether experience mitigates this framing effect. Choices in two treatment groups with status quo defaults are compared to choices in a neutrally framed control group. A two-step design features sorting of subjects into the groups, allowing us to control for selection effects due to risk preferences. The results confirm the presence of a status quo bias in consumer choices over health insurance policies. However, this effect of the default framing does not persist as subjects repeat this decision in later periods of the experiment. Our results have implications for health care policy, for example suggesting that the use of non-binding defaults in health insurance can facilitate the spread of co-insurance policies and thereby help contain health care expenditure.

  12. Direct Extraction of InP/GaAsSb/InP DHBT Equivalent-Circuit Elements From S-Parameters Measured at Cut-Off and Normal Bias Conditions

    DEFF Research Database (Denmark)

    Johansen, Tom Keinicke; Leblanc, Rémy; Poulain, Julien

    2016-01-01

    A unique direct parameter extraction method for the small-signal equivalent-circuit model of InP/GaAsSb/InP double heterojunction bipolar transistors (DHBTs) is presented. $S$-parameters measured at cut-off bias are used, at first, to extract the distribution factor $X_{0}$ for the base-collector......A unique direct parameter extraction method for the small-signal equivalent-circuit model of InP/GaAsSb/InP double heterojunction bipolar transistors (DHBTs) is presented. $S$-parameters measured at cut-off bias are used, at first, to extract the distribution factor $X_{0}$ for the base......-collector capacitance at zero collector current and the collector-to-emitter overlap capacitance $C_{ceo}$ present in InP DHBT devices. Low-frequency $S$-parameters measured at normal bias conditions then allows the extraction of the external access resistances $R_{bx}$, $R_{e}$, and $R_{cx}$ as well as the intrinsic...

  13. Dark electrical bias effect on moisture-induced degradation in inverted lead halide perovskite solar cells measured by advanced chemical probes

    KAUST Repository

    Barbe, Jeremy; Kumar, Vikas; Newman, Michael; Lee, Harrison; Jain, Sagar Motilal; Chen, Hu; Charbonneau, Cé cile; Rodenburg, C; Tsoi, Wing

    2018-01-01

    Emerging lead halide perovskite materials have enormous potential for a range of optoelectronic devices, such as solar cells, light emitting diodes, transistors and lasers. However, the large-scale commercialization of these technologies will depend on the ability of the active material to be stable under environmental and operating conditions. In this work, we measured the first time the electrical bias-induced degradation of inverted perovskite solar cells in the dark in different environments and concluded that humidity coupled with electrical bias results in fast degradation of CH3NH3PbI3 into PbI2. Micro-Raman and photoluminescence show that the degradation starts from the edge of the cell due to moisture ingress. By using novel local Raman-transient photocurrent measurements, we were able to probe local ion migration at the degraded region and non-degraded region and found that the formation of PbI2 can passivate perovskite by reducing ion migration. The degradation is far from uniform across different grains as revealed by secondary electron hyperspectral imaging, an advanced scanning electron microscopy technique which allows probing the composition of individual grain from the cross-section. By using potential step chronoamperometry, we also found that the bias degradation is closely related to the density of mobile ions. The unique combination of established methods with several novel analytical tools provides an insight into the origin of the bias-degradation of inverted perovskite solar cells from nano-scale to cell level, and demonstrates the potential of these novel tools for studying the degradation in other perovskite systems.

  14. Dark electrical bias effect on moisture-induced degradation in inverted lead halide perovskite solar cells measured by advanced chemical probes

    KAUST Repository

    Barbe, Jeremy

    2018-02-12

    Emerging lead halide perovskite materials have enormous potential for a range of optoelectronic devices, such as solar cells, light emitting diodes, transistors and lasers. However, the large-scale commercialization of these technologies will depend on the ability of the active material to be stable under environmental and operating conditions. In this work, we measured the first time the electrical bias-induced degradation of inverted perovskite solar cells in the dark in different environments and concluded that humidity coupled with electrical bias results in fast degradation of CH3NH3PbI3 into PbI2. Micro-Raman and photoluminescence show that the degradation starts from the edge of the cell due to moisture ingress. By using novel local Raman-transient photocurrent measurements, we were able to probe local ion migration at the degraded region and non-degraded region and found that the formation of PbI2 can passivate perovskite by reducing ion migration. The degradation is far from uniform across different grains as revealed by secondary electron hyperspectral imaging, an advanced scanning electron microscopy technique which allows probing the composition of individual grain from the cross-section. By using potential step chronoamperometry, we also found that the bias degradation is closely related to the density of mobile ions. The unique combination of established methods with several novel analytical tools provides an insight into the origin of the bias-degradation of inverted perovskite solar cells from nano-scale to cell level, and demonstrates the potential of these novel tools for studying the degradation in other perovskite systems.

  15. Sampling bias in an internet treatment trial for depression.

    Science.gov (United States)

    Donkin, L; Hickie, I B; Christensen, H; Naismith, S L; Neal, B; Cockayne, N L; Glozier, N

    2012-10-23

    Internet psychological interventions are efficacious and may reduce traditional access barriers. No studies have evaluated whether any sampling bias exists in these trials that may limit the translation of the results of these trials into real-world application. We identified 7999 potentially eligible trial participants from a community-based health cohort study and invited them to participate in a randomized controlled trial of an online cognitive behavioural therapy programme for people with depression. We compared those who consented to being assessed for trial inclusion with nonconsenters on demographic, clinical and behavioural indicators captured in the health study. Any potentially biasing factors were then assessed for their association with depression outcome among trial participants to evaluate the existence of sampling bias. Of the 35 health survey variables explored, only 4 were independently associated with higher likelihood of consenting-female sex (odds ratio (OR) 1.11, 95% confidence interval (CI) 1.05-1.19), speaking English at home (OR 1.48, 95% CI 1.15-1.90) higher education (OR 1.67, 95% CI 1.46-1.92) and a prior diagnosis of depression (OR 1.37, 95% CI 1.22-1.55). The multivariate model accounted for limited variance (C-statistic 0.6) in explaining participation. These four factors were not significantly associated with either the primary trial outcome measure or any differential impact by intervention arm. This demonstrates that, among eligible trial participants, few factors were associated with the consent to participate. There was no indication that such self-selection biased the trial results or would limit the generalizability and translation into a public or clinical setting.

  16. Does gender bias influence awards given by societies?

    Science.gov (United States)

    Holmes, Mary Anne; Asher, Pranoti; Farrington, John; Fine, Rana; Leinen, Margaret S.; LeBoy, Phoebe

    2011-11-01

    AGU is a participant in a U.S. National Science Foundation (NSF)-funded project called Advancing Ways of Awarding Recognition in Disciplinary Societies (AWARDS), which seeks to examine whether gender bias affects selection of recipients of society awards. AGU is interested in learning why there is a higher proportion of female recipients of service and education awards over the past 2 decades. Combined with a lower rate of receipt of research awards, these results suggest that implicit (subconscious) bias in favor of male candidates still influences awardee selection. Six other professional societies (American Chemical Society, American Mathematical Society, American Society of Anesthesiologists, Mathematical Association of America, Society for Neuroscience, and Society for Industrial and Applied Mathematics) are participating in the project. Volunteers from each participant society attended an Association for Women in Science (AWIS)-sponsored workshop in May 2010 to examine data and review literature on best practices for fair selection of society awardees. A draft proposal for implementing these practices will be brought before the AGU Council and the Honors and Recognition Committee at their upcoming meetings.

  17. Exploring the repetition bias in voluntary task switching.

    Science.gov (United States)

    Mittelstädt, Victor; Dignath, David; Schmidt-Ott, Magdalena; Kiesel, Andrea

    2018-01-01

    In the voluntary task-switching paradigm, participants are required to randomly select tasks. We reasoned that the consistent finding of a repetition bias (i.e., participants repeat tasks more often than expected by chance) reflects reasonable adaptive task selection behavior to balance the goal of random task selection with the goals to minimize the time and effort for task performance. We conducted two experiments in which participants were provided with variable amount of preview for the non-chosen task stimuli (i.e., potential switch stimuli). We assumed that switch stimuli would initiate some pre-processing resulting in improved performance in switch trials. Results showed that reduced switch costs due to extra-preview in advance of each trial were accompanied by more task switches. This finding is in line with the characteristics of rational adaptive behavior. However, participants were not biased to switch tasks more often than chance despite large switch benefits. We suggest that participants might avoid effortful additional control processes that modulate the effects of preview on task performance and task choice.

  18. Measurement error in epidemiologic studies of air pollution based on land-use regression models.

    Science.gov (United States)

    Basagaña, Xavier; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Foraster, Maria; Marrugat, Jaume; Elosua, Roberto; Künzli, Nino

    2013-10-15

    Land-use regression (LUR) models are increasingly used to estimate air pollution exposure in epidemiologic studies. These models use air pollution measurements taken at a small set of locations and modeling based on geographical covariates for which data are available at all study participant locations. The process of LUR model development commonly includes a variable selection procedure. When LUR model predictions are used as explanatory variables in a model for a health outcome, measurement error can lead to bias of the regression coefficients and to inflation of their variance. In previous studies dealing with spatial predictions of air pollution, bias was shown to be small while most of the effect of measurement error was on the variance. In this study, we show that in realistic cases where LUR models are applied to health data, bias in health-effect estimates can be substantial. This bias depends on the number of air pollution measurement sites, the number of available predictors for model selection, and the amount of explainable variability in the true exposure. These results should be taken into account when interpreting health effects from studies that used LUR models.

  19. Mo-containing tetrahedral amorphous carbon deposited by dual filtered cathodic vacuum arc with selective pulsed bias voltage

    International Nuclear Information System (INIS)

    Pasaja, Nitisak; Sansongsiri, Sakon; Intarasiri, Saweat; Vilaithong, Thiraphat; Anders, Andre

    2007-01-01

    Metal-containing tetrahedral amorphous carbon films were produced by dual filtered cathodic vacuum arc plasma sources operated in sequentially pulsed mode. Negatively pulsed bias was applied to the substrate when carbon plasma was generated, whereas it was absent when the molybdenum plasma was presented. Film thickness was measured after deposition by profilometry. Glass slides with silver pads were used as substrates for the measurement of the sheet resistance. The microstructure and composition of the films were characterized by Raman spectroscopy and Rutherford backscattering, respectively. It was found that the electrical resistivity decreases with an increase of the Mo content, which can be ascribed to an increase of the sp 2 content and an increase of the sp 2 cluster size

  20. Negativity Bias in Dangerous Drivers.

    Directory of Open Access Journals (Sweden)

    Jing Chai

    Full Text Available The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.

  1. Sympathetic bias.

    Science.gov (United States)

    Levy, David M; Peart, Sandra J

    2008-06-01

    We wish to deal with investigator bias in a statistical context. We sketch how a textbook solution to the problem of "outliers" which avoids one sort of investigator bias, creates the temptation for another sort. We write down a model of the approbation seeking statistician who is tempted by sympathy for client to violate the disciplinary standards. We give a simple account of one context in which we might expect investigator bias to flourish. Finally, we offer tentative suggestions to deal with the problem of investigator bias which follow from our account. As we have given a very sparse and stylized account of investigator bias, we ask what might be done to overcome this limitation.

  2. Bias modification training can alter approach bias and chocolate consumption.

    Science.gov (United States)

    Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika

    2016-01-01

    Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Angular dependence of Si3N4 etch rates and the etch selectivity of SiO2 to Si3N4 at different bias voltages in a high-density C4F8 plasma

    International Nuclear Information System (INIS)

    Lee, Jin-Kwan; Lee, Gyeo-Re; Min, Jae-Ho; Moon, Sang Heup

    2007-01-01

    The dependence of Si 3 N 4 etch rates and the etch selectivity of SiO 2 to Si 3 N 4 on ion-incident angles was studied for different bias voltages in a high-density C 4 F 8 plasma. A Faraday cage and specially designed substrate holders were used to accurately control the angles of incident ions on the substrate surface. The normalized etch yield (NEY), defined as the etch yield obtained at a given ion-incident angle normalized to that obtained on a horizontal surface, was unaffected by the bias voltage in Si 3 N 4 etching, but it increased with the bias voltage in SiO 2 etching in the range of -100 to -300 V. The NEY changed showing a maximum with an increase in the ion-incident angle in the etching of both substrates. In the Si 3 N 4 etching, a maximum NEY of 1.7 was obtained at 70 deg. in the above bias voltage range. However, an increase in the NEY at high ion-incident angles was smaller for SiO 2 than for Si 3 N 4 and, consequently, the etch selectivity of SiO 2 to Si 3 N 4 decreased with an increase in the ion-incident angle. The etch selectivity decreased to a smaller extent at high bias voltage because the NEY of SiO 2 had increased. The characteristic changes in the NEY for different substrates could be correlated with the thickness of a steady-state fluorocarbon (CF x ) film formed on the substrates

  4. Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

    Energy Technology Data Exchange (ETDEWEB)

    Samuroff, Simon [Manchester U.

    2017-01-01

    This thesis sets out a practical guide to applying shear measurements as a cosmological tool. We first present one of two science-ready galaxy shape catalogues from Year 1 of the Dark Energy Survey (DES Y1), which covers 1500 square degrees in four bands $griz$, with a median redshift of $0.59$. We describe the shape measurement process implemented by the DES Y1 imshape catalogue, which contains 21.9 million high-quality $r$-band bulge/disc fits. In Chapter 3 a new suite of image simulations, referred to as Hoopoe, are presented. The Hoopoe dataset is tailored to DES Y1 and includes realistic blending, spatial masks and variation in the point spread function. We derive shear corrections, which we show are robust to changes in calibration method, galaxy binning and variance within the simulated dataset. Sources of systematic uncertainty in the simulation-based shear calibration are discussed, leading to a final estimate of the $1\\sigma$ uncertainties in the residual multiplica tive bias after calibration of 0.025. Chapter 4 describes an extension of the analysis on the Hoopoe simulations into a detailed investigation of the impact of galaxy neighbours on shape measurement and shear cosmology. Four mechanisms by which neighbours can have a non-negligible influence on shear measurement are identified. These effects, if ignored, would contribute a net multiplicative bias of $m \\sim 0.03 - 0.09$ in DES Y1, though the precise impact will depend on both the measurement code and the selection cuts applied. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $S_8 \\equiv \\sigma_8 (\\omegam /0.3)^{0.5}$ by $1.5 \\sigma$ towards low values. Finally, we use the Hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the cosmo logical

  5. The substitution bias of the consumer price index

    OpenAIRE

    Frenger, Petter

    2006-01-01

    Abstract: The paper uses elementary consumer theory to propose an inflation independent ratio definition of the substitution bias of the Laspeyres consumer price index, and derives an approximate substitution bias which depends on the size of the price change as measured by a norm in the Laspeyres plane and on the elasticity of substitution in the direction of the price change. This norm or distance measure can be interpreted as a price substitution index which yields useful in...

  6. Speed Biases With Real-Life Video Clips

    Directory of Open Access Journals (Sweden)

    Federica Rossi

    2018-03-01

    Full Text Available We live almost literally immersed in an artificial visual world, especially motion pictures. In this exploratory study, we asked whether the best speed for reproducing a video is its original, shooting speed. By using adjustment and double staircase methods, we examined speed biases in viewing real-life video clips in three experiments, and assessed their robustness by manipulating visual and auditory factors. With the tested stimuli (short clips of human motion, mixed human-physical motion, physical motion and ego-motion, speed underestimation was the rule rather than the exception, although it depended largely on clip content, ranging on average from 2% (ego-motion to 32% (physical motion. Manipulating display size or adding arbitrary soundtracks did not modify these speed biases. Estimated speed was not correlated with estimated duration of these same video clips. These results indicate that the sense of speed for real-life video clips can be systematically biased, independently of the impression of elapsed time. Measuring subjective visual tempo may integrate traditional methods that assess time perception: speed biases may be exploited to develop a simple, objective test of reality flow, to be used for example in clinical and developmental contexts. From the perspective of video media, measuring speed biases may help to optimize video reproduction speed and validate “natural” video compression techniques based on sub-threshold temporal squeezing.

  7. Salutary effects of an attention bias modification mobile application on biobehavioral measures of stress and anxiety during pregnancy.

    Science.gov (United States)

    Dennis-Tiwary, Tracy A; Denefrio, Samantha; Gelber, Shari

    2017-07-01

    Stress and anxiety during pregnancy are associated with a range of adverse health outcomes, but there is an unmet need for low-barrier treatments that target stress and anxiety. One such treatment approach, attention bias modification training (ABMT), targets the anxiety-related threat bias, a disruption in attention to and neural processing of threat-related information. It remains unclear, however, whether reducing treatment barriers via mobile delivery of ABMT is effective and whether ABMT efficacy varies depending on individual differences in neural processing of threat. The present study tested whether mobile, gamified ABMT reduced prenatal threat bias, anxiety and stress, and whether ABMT efficacy varied with individual differences in neural responses to threat. Participants were 29 women in their 19th-29th week of pregnancy, randomized to four weeks of an ABMT or placebo training (PT) version of the mobile app using a double-blind design. Self-report of anxiety, depression, and stress were obtained; salivary cortisol was collected at home and in lab in response to stressors to index biological stress reactivity. Threat bias was measured using a computerized attention assay during which EEG was recorded to generate event-related potentials (ERPs) to threat cues. Results showed lower levels of lab cortisol following ABMT versus PT. Although the main effect of ABMT on subjective anxiety was not significant, the magnitude of cortisol reduction was correlated with lower levels of subjective anxiety and threat bias. Those receiving ABMT also reported less anxiety when showing smaller ERPs to threat (P1, P2) prior to training, but, conversely reported more anxiety when showing larger ERPs to threat. Use of gamified, mobile ABMT reduced biobehavioral indices of prenatal stress and anxiety, but effects on anxiety varied with individual differences in cortisol response and neurocognitive indices of early attention to threat. Copyright © 2017 Elsevier B.V. All rights

  8. Treatment with escitalopram improves the attentional bias toward negative facial expressions in patients with major depressive disorders.

    Science.gov (United States)

    Zhou, Zhenhe; Cao, Suxia; Li, Hengfen; Li, Youhui

    2015-10-01

    We hypothesized that treatment with escitalopram would improve cognitive bias and contribute to the recovery process for patients with major depressive disorder (MDD). Many previous studies have established that patients with MDD tend to pay selective attention to negative stimuli. The assessment of the level of cognitive bias is regarded as a crucial dimension of treatment outcomes for MDD. To our knowledge, no prior studies have been reported on the effects of treatment with escitalopram on attentional bias in MDD, employing a dot probe task of facial expression. We studied 25 patients with MDD and 25 controls, and used a dot probe task of facial expression to measure cognitive bias. The patients' psychopathologies were rated using the Hamilton Depression Scale (HAMD) at baseline and after 8 weeks of treatment with escitalopram. All participants performed the facial expression dot probe task. The results revealed that the 8 week escitalopram treatment decreased the HAMD scores. The patients with MDD at baseline exhibited an attentional bias towards negative faces, however, no significant bias toward either negative or happy faces were observed in the controls. After the 8 week escitalopram treatment, no significant bias toward negative faces was observed in the patient group. In conclusion, patients with MDD pay more attention to negative facial expressions, and treatment with escitalopram improves this attentional bias toward negative facial expressions. This is the first study, to our knowledge, on the effects of treatment with escitalopram on attentional bias in patients with MDD that has employed a dot probe task of facial expression. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Combination of biased forecasts: Bias correction or bias based weights?

    OpenAIRE

    Wenzel, Thomas

    1999-01-01

    Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts, and on the other we calculate bias based weights. A simulation study gives some insight in the situations where we should use the different methods.

  10. Liberal bias and the five-factor model.

    Science.gov (United States)

    Charney, Evan

    2015-01-01

    Duarte et al. draw attention to the "embedding of liberal values and methods" in social psychological research. They note how these biases are often invisible to the researchers themselves. The authors themselves fall prey to these "invisible biases" by utilizing the five-factor model of personality and the trait of openness to experience as one possible explanation for the under-representation of political conservatives in social psychology. I show that the manner in which the trait of openness to experience is conceptualized and measured is a particularly blatant example of the very liberal bias the authors decry.

  11. Emotional sensitization highlights the attentional bias in blood-injection-injury phobics: an ERP study.

    Science.gov (United States)

    Sarlo, Michela; Buodo, Giulia; Devigili, Andrea; Munafò, Marianna; Palomba, Daniela

    2011-02-18

    The presence of an attentional bias towards disorder-related stimuli has not been consistently demonstrated in blood phobics. The present study was aimed at investigating whether or not an attentional bias, as measured by event-related potentials (ERPs), could be highlighted in blood phobics by inducing cognitive-emotional sensitization through the repetitive presentation of different disorder-related pictures. The mean amplitudes of the N100, P200, P300 and late positive potentials to picture onset were assessed along with subjective ratings of valence and arousal in 13 blood phobics and 12 healthy controls. Blood phobics, but not controls, showed a linear increase of subjective arousal over time, suggesting that cognitive-emotional sensitization did occur. The analysis of cortical responses showed larger N100 and smaller late positive potentials in phobics than in controls in response to mutilations. These findings suggest that cognitive-emotional sensitization induced an attentional bias in blood phobics during picture viewing, involving early selective encoding and late cognitive avoidance of disorder-related stimuli depicting mutilations. © 2010 Elsevier Ireland Ltd. All rights reserved.

  12. Source selection for cluster weak lensing measurements in the Hyper Suprime-Cam survey

    Science.gov (United States)

    Medezinski, Elinor; Oguri, Masamune; Nishizawa, Atsushi J.; Speagle, Joshua S.; Miyatake, Hironao; Umetsu, Keiichi; Leauthaud, Alexie; Murata, Ryoma; Mandelbaum, Rachel; Sifón, Cristóbal; Strauss, Michael A.; Huang, Song; Simet, Melanie; Okabe, Nobuhiro; Tanaka, Masayuki; Komiyama, Yutaka

    2018-03-01

    We present optimized source galaxy selection schemes for measuring cluster weak lensing (WL) mass profiles unaffected by cluster member dilution from the Subaru Hyper Suprime-Cam Strategic Survey Program (HSC-SSP). The ongoing HSC-SSP survey will uncover thousands of galaxy clusters to z ≲ 1.5. In deriving cluster masses via WL, a critical source of systematics is contamination and dilution of the lensing signal by cluster members, and by foreground galaxies whose photometric redshifts are biased. Using the first-year CAMIRA catalog of ˜900 clusters with richness larger than 20 found in ˜140 deg2 of HSC-SSP data, we devise and compare several source selection methods, including selection in color-color space (CC-cut), and selection of robust photometric redshifts by applying constraints on their cumulative probability distribution function (P-cut). We examine the dependence of the contamination on the chosen limits adopted for each method. Using the proper limits, these methods give mass profiles with minimal dilution in agreement with one another. We find that not adopting either the CC-cut or P-cut methods results in an underestimation of the total cluster mass (13% ± 4%) and the concentration of the profile (24% ± 11%). The level of cluster contamination can reach as high as ˜10% at R ≈ 0.24 Mpc/h for low-z clusters without cuts, while employing either the P-cut or CC-cut results in cluster contamination consistent with zero to within the 0.5% uncertainties. Our robust methods yield a ˜60 σ detection of the stacked CAMIRA surface mass density profile, with a mean mass of M200c = [1.67 ± 0.05(stat)] × 1014 M⊙/h.

  13. Estimation bias and bias correction in reduced rank autoregressions

    DEFF Research Database (Denmark)

    Nielsen, Heino Bohn

    2017-01-01

    This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...

  14. Attentional bias to betel quid cues: An eye tracking study.

    Science.gov (United States)

    Shen, Bin; Chiu, Meng-Chun; Li, Shuo-Heng; Huang, Guo-Joe; Liu, Ling-Jun; Ho, Ming-Chou

    2016-09-01

    The World Health Organization regards betel quid as a human carcinogen, and DSM-IV and ICD-10 dependence symptoms may develop with heavy use. This study, conducted in central Taiwan, investigated whether betel quid chewers can exhibit overt orienting to selectively respond to the betel quid cues. Twenty-four male chewers' and 23 male nonchewers' eye movements to betel-quid-related pictures and matched pictures were assessed during a visual probe task. The eye movement index showed that betel quid chewers were more likely to initially direct their gaze to the betel quid cues, t(23) = 3.70, p betel quid chewers' attentional bias. The results demonstrated that the betel quid chewers (but not the nonchewers) were more likely to initially direct their gaze to the betel quid cues, and spent more time and were more fixated on them. These findings suggested that when attention is directly measured through the eye tracking technique, this methodology may be more sensitive to detecting attentional biases in betel quid chewers. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  15. SpArcFiRe: morphological selection effects due to reduced visibility of tightly winding arms in distant spiral galaxies

    Science.gov (United States)

    Peng, Tianrui Rae; Edward English, John; Silva, Pedro; Davis, Darren R.; Hayes, Wayne B.

    2018-03-01

    The Galaxy Zoo project has provided a plethora of valuable morphological data on a large number of galaxies from various surveys, and their team have identified and/or corrected for many biases. Here we study a new bias related to spiral arm pitch angles, which first requires selecting a sample of spiral galaxies that show observable structure. One obvious way is to select galaxies using a threshold in spirality, which we define as the fraction of Galaxy Zoo humans who have reported seeing spiral structure. Using such a threshold, we use the automated tool SpArcFiRe (SPiral ARC FInder and REporter) to measure spiral arm pitch angles. We observe that the mean pitch angle of spiral arms increases linearly with redshift for 0.05 data to provide a spirality for each artificially degraded image. We find that SpARcFiRe's ability to accurately measure pitch angles decreases as the image degrades, but that spirality decreases more quickly in galaxies with tightly wound arms, leading to the selection effect. This new bias means one must be careful in selecting a sample on which to measure spiral structure. Finally, we also include a sensitivity analysis of SpArcFiRe's internal parameters.

  16. Understanding the faint red galaxy population using large-scale clustering measurements from SDSS DR7

    OpenAIRE

    Ross, Ashley; Tojeiro, Rita; Percival, Will

    2011-01-01

    We use data from the SDSS to investigate the evolution of the large-scale galaxy bias as a function of luminosity for red galaxies. We carefully consider correlation functions of galaxies selected from both photometric and spectroscopic data, and cross-correlations between them, to obtain multiple measurements of the large-scale bias. We find, for our most robust analyses, a strong increase in bias with luminosity for the most luminous galaxies, an intermediate regime where bias does not evol...

  17. A polar-region-adaptable systematic bias collaborative measurement method for shipboard redundant rotational inertial navigation systems

    Science.gov (United States)

    Wang, Lin; Wu, Wenqi; Wei, Guo; Lian, Junxiang; Yu, Ruihang

    2018-05-01

    The shipboard redundant rotational inertial navigation system (RINS) configuration, including a dual-axis RINS and a single-axis RINS, can satisfy the demand of marine INSs of especially high reliability as well as achieving trade-off between position accuracy and cost. Generally, the dual-axis RINS is the master INS, and the single-axis RINS is the hot backup INS for high reliability purposes. An integrity monitoring system performs a fault detection function to ensure sailing safety. However, improving the accuracy of the backup INS in case of master INS failure has not been given enough attention. Without the aid of any external information, a systematic bias collaborative measurement method based on an augmented Kalman filter is proposed for the redundant RINSs. Estimates of inertial sensor biases can be used by the built-in integrity monitoring system to monitor the RINS running condition. On the other hand, a position error prediction model is designed for the single-axis RINS to estimate the systematic error caused by its azimuth gyro bias. After position error compensation, the position information provided by the single-axis RINS still remains highly accurate, even if the integrity monitoring system detects a dual-axis RINS fault. Moreover, use of a grid frame as a navigation frame makes the proposed method applicable in any area, including the polar regions. Semi-physical simulation and experiments including sea trials verify the validity of the method.

  18. DTI measurements for Alzheimer’s classification

    Science.gov (United States)

    Maggipinto, Tommaso; Bellotti, Roberto; Amoroso, Nicola; Diacono, Domenico; Donvito, Giacinto; Lella, Eufemia; Monaco, Alfonso; Antonella Scelsi, Marzia; Tangaro, Sabina; Disease Neuroimaging Initiative, Alzheimer's.

    2017-03-01

    Diffusion tensor imaging (DTI) is a promising imaging technique that provides insight into white matter microstructure integrity and it has greatly helped identifying white matter regions affected by Alzheimer’s disease (AD) in its early stages. DTI can therefore be a valuable source of information when designing machine-learning strategies to discriminate between healthy control (HC) subjects, AD patients and subjects with mild cognitive impairment (MCI). Nonetheless, several studies have reported so far conflicting results, especially because of the adoption of biased feature selection strategies. In this paper we firstly analyzed DTI scans of 150 subjects from the Alzheimer’s disease neuroimaging initiative (ADNI) database. We measured a significant effect of the feature selection bias on the classification performance (p-value  informative content provided by DTI measurements for AD classification. Classification performances and biological insight, concerning brain regions related to the disease, provided by cross-validation analysis were both confirmed on the independent test.

  19. Can Decision Biases Improve Insurance Outcomes? An Experiment on Status Quo Bias in Health Insurance Choice

    Science.gov (United States)

    Krieger, Miriam; Felder, Stefan

    2013-01-01

    Rather than conforming to the assumption of perfect rationality in neoclassical economic theory, decision behavior has been shown to display a host of systematic biases. Properly understood, these patterns can be instrumentalized to improve outcomes in the public realm. We conducted a laboratory experiment to study whether decisions over health insurance policies are subject to status quo bias and, if so, whether experience mitigates this framing effect. Choices in two treatment groups with status quo defaults are compared to choices in a neutrally framed control group. A two-step design features sorting of subjects into the groups, allowing us to control for selection effects due to risk preferences. The results confirm the presence of a status quo bias in consumer choices over health insurance policies. However, this effect of the default framing does not persist as subjects repeat this decision in later periods of the experiment. Our results have implications for health care policy, for example suggesting that the use of non-binding defaults in health insurance can facilitate the spread of co-insurance policies and thereby help contain health care expenditure. PMID:23783222

  20. Can Decision Biases Improve Insurance Outcomes? An Experiment on Status Quo Bias in Health Insurance Choice

    Directory of Open Access Journals (Sweden)

    Stefan Felder

    2013-06-01

    Full Text Available Rather than conforming to the assumption of perfect rationality in neoclassical economic theory, decision behavior has been shown to display a host of systematic biases. Properly understood, these patterns can be instrumentalized to improve outcomes in the public realm. We conducted a laboratory experiment to study whether decisions over health insurance policies are subject to status quo bias and, if so, whether experience mitigates this framing effect. Choices in two treatment groups with status quo defaults are compared to choices in a neutrally framed control group. A two-step design features sorting of subjects into the groups, allowing us to control for selection effects due to risk preferences. The results confirm the presence of a status quo bias in consumer choices over health insurance policies. However, this effect of the default framing does not persist as subjects repeat this decision in later periods of the experiment. Our results have implications for health care policy, for example suggesting that the use of non-binding defaults in health insurance can facilitate the spread of co-insurance policies and thereby help contain health care expenditure.

  1. Implicit and Explicit Memory Bias in Opiate Dependent, Abstinent and Normal Individuals

    Directory of Open Access Journals (Sweden)

    Jafar Hasani

    2013-07-01

    Full Text Available Objective: The aim of current research was to assess implicit and explicit memory bias to drug related stimuli in opiate Dependent, abstinent and normal Individuals. Method: Three groups including opiate Dependent, abstinent and normal Individuals (n=25 were selected by available sampling method. After matching on the base of age, education level and type of substance use all participants assessed by recognition task (explicit memory bias and stem completion task (implicit memory bias. Results: The analysis of data showed that opiate dependent and abstinent groups in comparison with normal individual had implicit memory bias, whereas in explicit memory only opiate dependent individuals showed bias. Conclusion: The identification of explicit and implicit memory governing addiction may have practical implications in diagnosis, treatment and prevention of substance abuse.

  2. Presence of bias in radiographer plain film reading performance studies

    International Nuclear Information System (INIS)

    Brealey, S.; Scally, A.J.; Thomas, N.B.

    2002-01-01

    Purpose To raise awareness of the frequency of bias that can affect the quality of radiographer plain film reading performance studies. Methods Studies that assessed radiographer(s) plain film reading performance were located by searching electronic databases and grey literature, hand-searching journals, personal communication and scanning reference lists. Thirty studies were judged eligible from all data sources. Results A one-way analysis of variance (ANOVA) demonstrates no statistically significant difference (P=0.25) in the mean proportion of biases present from diagnostic accuracy (0.37), performance (0.42) and outcome (0.44) study designs. Pearson's correlation coefficient showed no statistically significant linear association between the proportion of biases present for the three different study designs and the year that the study was performed. The frequency of biases in film and observer selection and application of the reference standard was quite low. In contrast, many biases were present concerning independence of film reporting and comparison of reports for concordance. Conclusions The findings indicate variation in the presence of bias in radiographer plain film reading performance studies. The careful consideration of bias is an essential component of study quality and hence the validity of the evidence-base used to underpin radiographic reporting policy

  3. Measures and limits of models of fixation selection.

    Directory of Open Access Journals (Sweden)

    Niklas Wilming

    Full Text Available Models of fixation selection are a central tool in the quest to understand how the human mind selects relevant information. Using this tool in the evaluation of competing claims often requires comparing different models' relative performance in predicting eye movements. However, studies use a wide variety of performance measures with markedly different properties, which makes a comparison difficult. We make three main contributions to this line of research: First we argue for a set of desirable properties, review commonly used measures, and conclude that no single measure unites all desirable properties. However the area under the ROC curve (a classification measure and the KL-divergence (a distance measure of probability distributions combine many desirable properties and allow a meaningful comparison of critical model performance. We give an analytical proof of the linearity of the ROC measure with respect to averaging over subjects and demonstrate an appropriate correction of entropy-based measures like KL-divergence for small sample sizes in the context of eye-tracking data. Second, we provide a lower bound and an upper bound of these measures, based on image-independent properties of fixation data and between subject consistency respectively. Based on these bounds it is possible to give a reference frame to judge the predictive power of a model of fixation selection. We provide open-source python code to compute the reference frame. Third, we show that the upper, between subject consistency bound holds only for models that predict averages of subject populations. Departing from this we show that incorporating subject-specific viewing behavior can generate predictions which surpass that upper bound. Taken together, these findings lay out the required information that allow a well-founded judgment of the quality of any model of fixation selection and should therefore be reported when a new model is introduced.

  4. Mixotrophic phytoflagellate bacterivory field measurements strongly biased by standard approaches

    DEFF Research Database (Denmark)

    Anderson, Ruth; Jürgens, Klaus; Hansen, Per Juel

    2017-01-01

    Bacterivory among small (≤ 20 μm) phytoflagellates (SP) is increasingly recognized as a globally relevant phenomenon, impacting a wide range of aspects from primary production levels to marine fisheries. However, to correctly parametrize mixotrophic SP in biogeochemical and food web models, a bet...... mixotrophic SP. Overall, this case study indicates that applying the two commonly used premises outlined above can introduce significant biases and considerably alter our perception of mixotrophy in a given system......., a better understanding of the magnitude and regulation of in situ SP feeding is urgently needed. Current methods to determine SP bacterivory in the field may introduce biases by treating these organisms as equivalent to heterotrophic nanoflagellates (HNF). In the present case study we experimentally tested...... two generally employed assumptions of such studies: (A) bacterivory rates of the whole SP community and of distinct SP groups remain constant over `short´ time scales (hours to a day) and (B) SP community ingestion rates approximate the average ingestion rate of all feeding individuals. Food vacuole...

  5. Approach bias modification training and consumption: A review of the literature.

    Science.gov (United States)

    Kakoschke, Naomi; Kemps, Eva; Tiggemann, Marika

    2017-01-01

    Recent theoretical perspectives and empirical evidence have suggested that biased cognitive processing is an important contributor to unhealthy behaviour. Approach bias modification is a novel intervention in which approach biases for appetitive cues are modified. The current review of the literature aimed to evaluate the effectiveness of modifying approach bias for harmful consumption behaviours, including alcohol use, cigarette smoking, and unhealthy eating. Relevant publications were identified through a search of four electronic databases (PsycINFO, Google Scholar, ScienceDirect and Scopus) that were conducted between October and December 2015. Eligibility criteria included the use of a human adult sample, at least one session of avoidance training, and an outcome measure related to the behaviour of interest. The fifteen identified publications (comprising 18 individual studies) were coded on a number of characteristics, including consumption behaviour, participants, task, training and control conditions, number of training sessions and trials, outcome measure, and results. The results generally showed positive effects of approach-avoidance training, including reduced consumption behaviour in the laboratory, lower relapse rates, and improvements in self-reported measures of behaviour. Importantly, all studies (with one exception) that reported favourable consumption outcomes also demonstrated successful reduction of the approach bias for appetitive cues. Thus, the current review concluded that approach bias modification is effective for reducing both approach bias and unhealthy consumption behaviour. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence

    International Nuclear Information System (INIS)

    Subashi, Ergys; Choudhury, Kingshuk R.; Johnson, G. Allan

    2014-01-01

    Purpose: The pharmacokinetic parameters derived from dynamic contrast-enhanced (DCE) MRI have been used in more than 100 phase I trials and investigator led studies. A comparison of the absolute values of these quantities requires an estimation of their respective probability distribution function (PDF). The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. Methods: The variance in the SPGR signal intensity arises from quadrature detection and excitation flip angle inconsistency. The noise power was measured in 11 phantoms of contrast agent concentration in the range [0–1] mM (in steps of 0.1 mM) and in onein vivo acquisition of a tumor-bearing mouse. The distribution of the flip angle was determined in a uniform 10 mM CuSO 4 phantom using the spin echo double angle method. The PDF of a wide range of T1 values measured with the varying flip angle (VFA) technique was estimated through numerical simulations of the SPGR equation. The resultant uncertainty in contrast agent concentration was incorporated in the most common model of tracer exchange kinetics and the PDF of the derived pharmacokinetic parameters was studied numerically. Results: The VFA method is an unbiased technique for measuringT1 only in the absence of bias in excitation flip angle. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted uncertainty. The uncertainty in measuring K trans with SPGR pulse sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time (T1 0 ). The lowest achievable bias/uncertainty in estimating this parameter is approximately 20%–70% higher than the bias/uncertainty in the measurement of the pre-injection T1 map. The fractional volume parameters derived from the extended Tofts model were found to be

  7. Investigation of selection bias in the association of race with prevalent atrial fibrillation in a national cohort study: REasons for Geographic And Racial Differences in Stroke (REGARDS).

    Science.gov (United States)

    Thacker, Evan L; Soliman, Elsayed Z; Pulley, LeaVonne; Safford, Monika M; Howard, George; Howard, Virginia J

    2016-08-01

    Atrial fibrillation (AF) is diagnosed more commonly in whites than blacks in the United States. In epidemiologic studies, selection bias could induce a noncausal positive association of white race with prevalent AF if voluntary enrollment was influenced by both race and AF status. We investigated whether nonrandom enrollment biased the association of race with prevalent self-reported AF in the US-based REasons for Geographic And Racial Differences in Stroke Study (REGARDS). REGARDS had a two-stage enrollment process, allowing us to compare 30,183 fully enrolled REGARDS participants with 12,828 people who completed the first-stage telephone survey but did not complete the second-stage in-home visit to finalize their REGARDS enrollment (telephone-only participants). REGARDS enrollment was higher among whites (77.1%) than among blacks (62.3%) but did not differ by self-reported AF status. The prevalence of AF was 8.45% in whites and 5.86% in blacks adjusted for age, sex, income, education, and perceived general health. The adjusted white/black prevalence ratio of self-reported AF was 1.43 (95% CI, 1.32-1.56) among REGARDS participants and 1.38 (1.22-1.55) among telephone-only participants. These findings suggest that selection bias is not a viable explanation for the higher prevalence of self-reported AF among whites in population studies such as REGARDS. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Improved Correction of Misclassification Bias With Bootstrap Imputation.

    Science.gov (United States)

    van Walraven, Carl

    2018-07-01

    Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.

  9. A new diagnostic accuracy measure and cut-point selection criterion.

    Science.gov (United States)

    Dong, Tuochuan; Attwood, Kristopher; Hutson, Alan; Liu, Song; Tian, Lili

    2017-12-01

    Most diagnostic accuracy measures and criteria for selecting optimal cut-points are only applicable to diseases with binary or three stages. Currently, there exist two diagnostic measures for diseases with general k stages: the hypervolume under the manifold and the generalized Youden index. While hypervolume under the manifold cannot be used for cut-points selection, generalized Youden index is only defined upon correct classification rates. This paper proposes a new measure named maximum absolute determinant for diseases with k stages ([Formula: see text]). This comprehensive new measure utilizes all the available classification information and serves as a cut-points selection criterion as well. Both the geometric and probabilistic interpretations for the new measure are examined. Power and simulation studies are carried out to investigate its performance as a measure of diagnostic accuracy as well as cut-points selection criterion. A real data set from Alzheimer's Disease Neuroimaging Initiative is analyzed using the proposed maximum absolute determinant.

  10. Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior.

    Science.gov (United States)

    Frisch, Simon; Dshemuchadse, Maja; Görner, Max; Goschke, Thomas; Scherbaum, Stefan

    2015-11-01

    Selective attention biases information processing toward stimuli that are relevant for achieving our goals. However, the nature of this bias is under debate: Does it solely rely on the amplification of goal-relevant information or is there a need for additional inhibitory processes that selectively suppress currently distracting information? Here, we explored the processes underlying selective attention with a dynamic, modeling-based approach that focuses on the continuous evolution of behavior over time. We present two dynamic neural field models incorporating the diverging theoretical assumptions. Simulations with both models showed that they make similar predictions with regard to response times but differ markedly with regard to their continuous behavior. Human data observed via mouse tracking as a continuous measure of performance revealed evidence for the model solely based on amplification but no indication of persisting selective distracter inhibition.

  11. DC and AC biasing of a transition edge sensor microcalorimeter

    International Nuclear Information System (INIS)

    Cunningham, M.F.; Ullom, J.N.; Miyazaki, T.; Drury, O.; Loshak, A.; Berg, M.L. van den; Labov, S.E.

    2002-01-01

    We are developing AC-biased transition edge sensor (TES) microcalorimeters for use in large arrays with frequency-domain multiplexing. Using DC bias, we have achieved a resolution of 17 eV FWHM at 2.6 keV with a decay time of 90 μs and an effective detector diameter of 300 μm. We have successfully measured thermal pulses with a TES microcalorimeter operated with an AC bias. We present here preliminary results from a single pixel detector operated under DC and AC bias conditions

  12. Cognitive Biases for Emotional Faces in High- and Low-Trait Depressive Participants

    Directory of Open Access Journals (Sweden)

    Yi-Hsing Hsieh

    2004-10-01

    Full Text Available This study examined the association between trait depression and information-processing biases. Thirty participants were divided into high- and low-trait depressive groups based on the median of their depressive subscale scores according to the Basic Personality Inventory. Information-processing biases were measured using a deployment-of-attention task (DOAT and a recognition memory task (RMT. For the DOAT, participants saw one emotional face paired with a neutral face of the same person, and then were forced to choose on which face the color patch had first occurred. The percentage of participants' choices favoring the happy, angry, or sad faces represented the selective attentional bias score for each emotion, respectively. For the RMT, participants rated different types of emotional faces and subsequently discriminated old faces from new faces. The memory strength for each type of face was calculated from hit and false-positive rates, based on the signal detection theory. Compared with the low-trait depressive group, the high-trait depressive group showed a negative cognitive style. This was an enhanced recognition memory for sad faces and a weakened inhibition of attending to sad faces, suggesting that those with high depressive trait may be vulnerable to interpersonal withdrawal.

  13. Workplace ageism: discovering hidden bias.

    Science.gov (United States)

    Malinen, Sanna; Johnston, Lucy

    2013-01-01

    BACKGROUND/STUDY CONTEXT: Research largely shows no performance differences between older and younger employees, or that older workers even outperform younger employees, yet negative attitudes towards older workers can underpin discrimination. Unfortunately, traditional "explicit" techniques for assessing attitudes (i.e., self-report measures) have serious drawbacks. Therefore, using an approach that is novel to organizational contexts, the authors supplemented explicit with implicit (indirect) measures of attitudes towards older workers, and examined the malleability of both. This research consists of two studies. The authors measured self-report (explicit) attitudes towards older and younger workers with a survey, and implicit attitudes with a reaction-time-based measure of implicit associations. In addition, to test whether attitudes were malleable, the authors measured attitudes before and after a mental imagery intervention, where the authors asked participants in the experimental group to imagine respected and valued older workers from their surroundings. Negative, stable implicit attitudes towards older workers emerged in two studies. Conversely, explicit attitudes showed no age bias and were more susceptible to change intervention, such that attitudes became more positive towards older workers following the experimental manipulation. This research demonstrates the unconscious nature of bias against older workers, and highlights the utility of implicit attitude measures in the context of the workplace. In the current era of aging workforce and skill shortages, implicit measures may be necessary to illuminate hidden workplace ageism.

  14. Ironic effects of racial bias during interracial interactions.

    Science.gov (United States)

    Shelton, J Nicole; Richeson, Jennifer A; Salvatore, Jessica; Trawalter, Sophie

    2005-05-01

    Previous research has suggested that Blacks like White interaction partners who make an effort to appear unbiased more than those who do not. We tested the hypothesis that, ironically, Blacks perceive White interaction partners who are more racially biased more positively than less biased White partners, primarily because the former group must make more of an effort to control racial bias than the latter. White participants in this study completed the Implicit Association Test (IAT) as a measure of racial bias and then discussed race relations with either a White or a Black partner. Whites' IAT scores predicted how positively they were perceived by Black (but not White) interaction partners, and this relationship was mediated by Blacks' perceptions of how engaged the White participants were during the interaction. We discuss implications of the finding that Blacks may, ironically, prefer to interact with highly racially biased Whites, at least in short interactions.

  15. Examinations of Home Economics Textbooks for Sex Bias.

    Science.gov (United States)

    Weis, Susan F.

    1979-01-01

    Four analyses were conducted on a sample of 100 randomly selected, secondary home economics textbooks published between 1964 and 1974. Results indicated that the contents presented sex bias in language usage, in pictures portraying male and female role environments, and in role behaviors and expectations emphasized. (Author/JH)

  16. Evaluating codon bias perspective in barbiturase gene using ...

    African Journals Online (AJOL)

    Abdullah

    2014-01-08

    Jan 8, 2014 ... along with codon usage was done to reveal dynamics of gene evolution and expression ... analysis is a potent approach for detecting mutations, selection methods and finding rationale of biased and unbiased gene changes and hence, evolutionary ... in the perception of the molecular basics plus potential.

  17. Potential self-selection bias in a nested case-control study on indoor environmental factors and their association with asthma and allergic symptoms among pre-school children

    DEFF Research Database (Denmark)

    Bornehag, Carl-Gustaf; Sundell, Jan; Sigsgaard, T.

    2006-01-01

    , including health, building characteristics of the home, and socioeconomic factors between participating and non-participating families in a nested case-control study on asthma and allergy among children. Information was collected in a baseline questionnaire to the parents of 14,077 children aged 1-6 years...... in a first step. In a second step 2,156 of the children were invited to participate in a case-control study. Of these, 198 cases and 202 controls were finally selected. For identifying potential selection bias, information concerning all invited families in the case-control study was obtained from...

  18. Attention and memory bias to facial emotions underlying negative symptoms of schizophrenia.

    Science.gov (United States)

    Jang, Seon-Kyeong; Park, Seon-Cheol; Lee, Seung-Hwan; Cho, Yang Seok; Choi, Kee-Hong

    2016-01-01

    This study assessed bias in selective attention to facial emotions in negative symptoms of schizophrenia and its influence on subsequent memory for facial emotions. Thirty people with schizophrenia who had high and low levels of negative symptoms (n = 15, respectively) and 21 healthy controls completed a visual probe detection task investigating selective attention bias (happy, sad, and angry faces randomly presented for 50, 500, or 1000 ms). A yes/no incidental facial memory task was then completed. Attention bias scores and recognition errors were calculated. Those with high negative symptoms exhibited reduced attention to emotional faces relative to neutral faces; those with low negative symptoms showed the opposite pattern when faces were presented for 500 ms regardless of the valence. Compared to healthy controls, those with high negative symptoms made more errors for happy faces in the memory task. Reduced attention to emotional faces in the probe detection task was significantly associated with less pleasure and motivation and more recognition errors for happy faces in schizophrenia group only. Attention bias away from emotional information relatively early in the attentional process and associated diminished positive memory may relate to pathological mechanisms for negative symptoms.

  19. Evidence for Response Bias as a Source of Error Variance in Applied Assessment

    Science.gov (United States)

    McGrath, Robert E.; Mitchell, Matthew; Kim, Brian H.; Hough, Leaetta

    2010-01-01

    After 100 years of discussion, response bias remains a controversial topic in psychological measurement. The use of bias indicators in applied assessment is predicated on the assumptions that (a) response bias suppresses or moderates the criterion-related validity of substantive psychological indicators and (b) bias indicators are capable of…

  20. The Bias of the Gini Coefficient due to Grouping

    NARCIS (Netherlands)

    T.G.M. van Ourti (Tom); Ph. Clarke (Philip)

    2008-01-01

    textabstractWe propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order correction term is obtained from studying the estimator of the Gini index within a measurement error framework. In addition, it reveals an intuitive formula for the

  1. Averaging Bias Correction for Future IPDA Lidar Mission MERLIN

    Science.gov (United States)

    Tellier, Yoann; Pierangelo, Clémence; Wirth, Martin; Gibert, Fabien

    2018-04-01

    The CNES/DLR MERLIN satellite mission aims at measuring methane dry-air mixing ratio column (XCH4) and thus improving surface flux estimates. In order to get a 1% precision on XCH4 measurements, MERLIN signal processing assumes an averaging of data over 50 km. The induced biases due to the non-linear IPDA lidar equation are not compliant with accuracy requirements. This paper analyzes averaging biases issues and suggests correction algorithms tested on realistic simulated scenes.

  2. Exchange bias studied with polarized neutron reflectivity

    International Nuclear Information System (INIS)

    Velthuis, S. G. E. te

    2000-01-01

    The role of Polarized Neutron Reflectivity (PNR) for studying natural and synthetic exchange biased systems is illustrated. For a partially oxidized thin film of Co, cycling of the magnetic field causes a considerable reduction of the bias, which the onset of diffuse neutron scattering shows to be due to the loosening of the ferromagnetic domains. On the other hand, PNR measurements of a model exchange bias junction consisting of an n-layered Fe/Cr antiferromagnetic (AF) superlattice coupled with an m-layered Fe/Cr ferromagnetic (F) superlattice confirm the predicted collinear magnetization in the two superlattices. The two magnetized states of the F (along or opposite to the bias field) differ only in the relative orientation of the F and adjacent AF layer. The possibility of reading clearly the magnetic state at the interface pinpoints the commanding role that PNR is having in solving this intriguing problem

  3. Estimating the price elasticity of beer: meta-analysis of data with heterogeneity, dependence, and publication bias.

    Science.gov (United States)

    Nelson, Jon P

    2014-01-01

    Precise estimates of price elasticities are important for alcohol tax policy. Using meta-analysis, this paper corrects average beer elasticities for heterogeneity, dependence, and publication selection bias. A sample of 191 estimates is obtained from 114 primary studies. Simple and weighted means are reported. Dependence is addressed by restricting number of estimates per study, author-restricted samples, and author-specific variables. Publication bias is addressed using funnel graph, trim-and-fill, and Egger's intercept model. Heterogeneity and selection bias are examined jointly in meta-regressions containing moderator variables for econometric methodology, primary data, and precision of estimates. Results for fixed- and random-effects regressions are reported. Country-specific effects and sample time periods are unimportant, but several methodology variables help explain the dispersion of estimates. In models that correct for selection bias and heterogeneity, the average beer price elasticity is about -0.20, which is less elastic by 50% compared to values commonly used in alcohol tax policy simulations. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Reducing neutron multiplicity counting bias for plutonium warhead authentication

    Energy Technology Data Exchange (ETDEWEB)

    Goettsche, Malte

    2015-06-05

    Confidence in future nuclear arms control agreements could be enhanced by direct verification of warheads. It would include warhead authentication. This is the assessment based on measurements whether a declaration that a specific item is a nuclear warhead is true. An information barrier can be used to protect sensitive information during measurements. It could for example show whether attributes such as a fissile mass exceeding a threshold are met without indicating detailed measurement results. Neutron multiplicity measurements would be able to assess a plutonium fissile mass attribute if it were possible to show that their bias is low. Plutonium measurements have been conducted with the He-3 based Passive Scrap Multiplicity Counter. The measurement data has been used as a reference to test the capacity of the Monte Carlo code MCNPX-PoliMi to simulate neutron multiplicity measurements. The simulation results with their uncertainties are in agreement with the experimental results. It is essential to use cross-sections which include neutron scattering with the detector's polyethylene molecular structure. Further MCNPX-PoliMi simulations have been conducted in order to study bias that occurs when measuring samples with large plutonium masses such as warheads. Simulation results of solid and hollow metal spheres up to 6000 g show that the masses are underpredicted by as much as 20%. The main source of this bias has been identified in the false assumption that the neutron multiplication does not depend on the position where a spontaneous fission event occurred. The multiplication refers to the total number of neutrons leaking a sample after a primary spontaneous fission event, taking induced fission into consideration. The correction of the analysis has been derived and implemented in a MATLAB code. It depends on four geometry-dependent correction coefficients. When the sample configuration is fully known, these can be exactly determined and remove this type of

  5. Survey Response-Related Biases in Contingent Valuation: Concepts, Remedies, and Empirical Application to Valuing Aquatic Plant Management

    Science.gov (United States)

    Mark L. Messonnier; John C. Bergstrom; Chrisopher M. Cornwell; R. Jeff Teasley; H. Ken Cordell

    2000-01-01

    Simple nonresponse and selection biases that may occur in survey research such as contingent valuation applications are discussed and tested. Correction mechanisms for these types of biases are demonstrated. Results indicate the importance of testing and correcting for unit and item nonresponse bias in contingent valuation survey data. When sample nonresponse and...

  6. Genome-wide comparative analysis of codon usage bias and codon context patterns among cyanobacterial genomes.

    Science.gov (United States)

    Prabha, Ratna; Singh, Dhananjaya P; Sinha, Swati; Ahmad, Khurshid; Rai, Anil

    2017-04-01

    With the increasing accumulation of genomic sequence information of prokaryotes, the study of codon usage bias has gained renewed attention. The purpose of this study was to examine codon selection pattern within and across cyanobacterial species belonging to diverse taxonomic orders and habitats. We performed detailed comparative analysis of cyanobacterial genomes with respect to codon bias. Our analysis reflects that in cyanobacterial genomes, A- and/or T-ending codons were used predominantly in the genes whereas G- and/or C-ending codons were largely avoided. Variation in the codon context usage of cyanobacterial genes corresponded to the clustering of cyanobacteria as per their GC content. Analysis of codon adaptation index (CAI) and synonymous codon usage order (SCUO) revealed that majority of genes are associated with low codon bias. Codon selection pattern in cyanobacterial genomes reflected compositional constraints as major influencing factor. It is also identified that although, mutational constraint may play some role in affecting codon usage bias in cyanobacteria, compositional constraint in terms of genomic GC composition coupled with environmental factors affected codon selection pattern in cyanobacterial genomes. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Bias of genetic trend of genomic predictions based on both real dairy cattle and simulated data

    DEFF Research Database (Denmark)

    Ma, Peipei; Lund, Mogens Sandø; Nielsen, Ulrik Sander

    This study investigated the phenomenon of bias in the trend of genomic predictions and attempted to find the reason and solution for this bias. The data used in this study include Danish Jersey data and simulation data. In Jersey data, the bias was reduced when cows were included in the reference...... population. In simulated data, there was no bias when the test animals were unselected cows. When the G matrix was derived from genotypes of causal genes, the bias was reduced. The results suggest that the main reasons for causing the bias of the prediction trends are the selection of bulls and bull dams...

  8. Predicting Aggressive Tendencies by Visual Attention Bias Associated with Hostile Emotions.

    Science.gov (United States)

    Lin, Ping-I; Hsieh, Cheng-Da; Juan, Chi-Hung; Hossain, Md Monir; Erickson, Craig A; Lee, Yang-Han; Su, Mu-Chun

    2016-01-01

    The goal of the current study is to clarify the relationship between social information processing (e.g., visual attention to cues of hostility, hostility attribution bias, and facial expression emotion labeling) and aggressive tendencies. Thirty adults were recruited in the eye-tracking study that measured various components in social information processing. Baseline aggressive tendencies were measured using the Buss-Perry Aggression Questionnaire (AQ). Visual attention towards hostile objects was measured as the proportion of eye gaze fixation duration on cues of hostility. Hostility attribution bias was measured with the rating results for emotions of characters in the images. The results show that the eye gaze duration on hostile characters was significantly inversely correlated with the AQ score and less eye contact with an angry face. The eye gaze duration on hostile object was not significantly associated with hostility attribution bias, although hostility attribution bias was significantly positively associated with the AQ score. Our findings suggest that eye gaze fixation time towards non-hostile cues may predict aggressive tendencies.

  9. Selective attention supports working memory maintenance by modulating perceptual processing of distractors.

    Science.gov (United States)

    Sreenivasan, Kartik K; Jha, Amishi P

    2007-01-01

    Selective attention has been shown to bias sensory processing in favor of relevant stimuli and against irrelevant or distracting stimuli in perceptual tasks. Increasing evidence suggests that selective attention plays an important role during working memory maintenance, possibly by biasing sensory processing in favor of to-be-remembered items. In the current study, we investigated whether selective attention may also support working memory by biasing processing against irrelevant and potentially distracting information. Event-related potentials (ERPs) were recorded while subjects (n = 22) performed a delayed-recognition task for faces and shoes. The delay period was filled with face or shoe distractors. Behavioral performance was impaired when distractors were congruent with the working memory domain (e.g., face distractor during working memory for faces) relative to when distractors were incongruent with the working memory domain (e.g., face distractor during shoe working memory). If attentional biasing against distractor processing is indeed functionally relevant in supporting working memory maintenance, perceptual processing of distractors is predicted to be attenuated when distractors are more behaviorally intrusive relative to when they are nonintrusive. As such, we predicted that perceptual processing of distracting faces, as measured by the face-sensitive N170 ERP component, would be reduced in the context of congruent (face) working memory relative to incongruent (shoe) working memory. The N170 elicited by distracting faces demonstrated reduced amplitude during congruent versus incongruent working memory. These results suggest that perceptual processing of distracting faces may be attenuated due to attentional biasing against sensory processing of distractors that are most behaviorally intrusive during working memory maintenance.

  10. Bias correction method for climate change impact assessment at a basin scale

    Science.gov (United States)

    Nyunt, C.; Jaranilla-sanchez, P. A.; Yamamoto, A.; Nemoto, T.; Kitsuregawa, M.; Koike, T.

    2012-12-01

    Climate change impact studies are mainly based on the general circulation models GCM and these studies play an important role to define suitable adaptation strategies for resilient environment in a basin scale management. For this purpose, this study summarized how to select appropriate GCM to decrease the certain uncertainty amount in analysis. This was applied to the Pampanga, Angat and Kaliwa rivers in Luzon Island, the main island of Philippine and these three river basins play important roles in irrigation water supply, municipal water source for Metro Manila. According to the GCM scores of both seasonal evolution of Asia summer monsoon and spatial correlation and root mean squared error of atmospheric variables over the region, finally six GCM is chosen. Next, we develop a complete, efficient and comprehensive statistical bias correction scheme covering extremes events, normal rainfall and frequency of dry period. Due to the coarse resolution and parameterization scheme of GCM, extreme rainfall underestimation, too many rain days with low intensity and poor representation of local seasonality have been known as bias of GCM. Extreme rainfall has unusual characteristics and it should be focused specifically. Estimated maximum extreme rainfall is crucial for planning and design of infrastructures in river basin. Developing countries have limited technical, financial and management resources for implementing adaptation measures and they need detailed information of drought and flood for near future. Traditionally, the analysis of extreme has been examined using annual maximum series (AMS) adjusted to a Gumbel or Lognormal distribution. The drawback is the loss of the second, third etc, largest rainfall. Another approach is partial duration series (PDS) constructed using the values above a selected threshold and permit more than one event per year. The generalized Pareto distribution (GPD) has been used to model PDS and it is the series of excess over a threshold

  11. Long-term continuous acoustical suspended-sediment measurements in rivers - Theory, application, bias, and error

    Science.gov (United States)

    Topping, David J.; Wright, Scott A.

    2016-05-04

    these sites. In addition, detailed, step-by-step procedures are presented for the general river application of the method.Quantification of errors in sediment-transport measurements made using this acoustical method is essential if the measurements are to be used effectively, for example, to evaluate uncertainty in long-term sediment loads and budgets. Several types of error analyses are presented to evaluate (1) the stability of acoustical calibrations over time, (2) the effect of neglecting backscatter from silt and clay, (3) the bias arising from changes in sand grain size, (4) the time-varying error in the method, and (5) the influence of nonrandom processes on error. Results indicate that (1) acoustical calibrations can be stable for long durations (multiple years), (2) neglecting backscatter from silt and clay can result in unacceptably high bias, (3) two frequencies are likely required to obtain sand-concentration measurements that are unbiased by changes in grain size, depending on site-specific conditions and acoustic frequency, (4) relative errors in silt-and-clay- and sand-concentration measurements decrease substantially as concentration increases, and (5) nonrandom errors may arise from slow changes in the spatial structure of suspended sediment that affect the relations between concentration in the acoustically ensonified part of the cross section and concentration in the entire river cross section. Taken together, the error analyses indicate that the two-frequency method produces unbiased measurements of suspended-silt-and-clay and sand concentration, with errors that are similar to, or larger than, those associated with conventional sampling methods.

  12. Method for exploiting bias in factor analysis using constrained alternating least squares algorithms

    Science.gov (United States)

    Keenan, Michael R.

    2008-12-30

    Bias plays an important role in factor analysis and is often implicitly made use of, for example, to constrain solutions to factors that conform to physical reality. However, when components are collinear, a large range of solutions may exist that satisfy the basic constraints and fit the data equally well. In such cases, the introduction of mathematical bias through the application of constraints may select solutions that are less than optimal. The biased alternating least squares algorithm of the present invention can offset mathematical bias introduced by constraints in the standard alternating least squares analysis to achieve factor solutions that are most consistent with physical reality. In addition, these methods can be used to explicitly exploit bias to provide alternative views and provide additional insights into spectral data sets.

  13. Quantifying the clear-sky bias of satellite-derived infrared LST

    Science.gov (United States)

    Ermida, S. L.; Trigo, I. F.; DaCamara, C.

    2017-12-01

    Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

  14. Averaging Bias Correction for Future IPDA Lidar Mission MERLIN

    Directory of Open Access Journals (Sweden)

    Tellier Yoann

    2018-01-01

    Full Text Available The CNES/DLR MERLIN satellite mission aims at measuring methane dry-air mixing ratio column (XCH4 and thus improving surface flux estimates. In order to get a 1% precision on XCH4 measurements, MERLIN signal processing assumes an averaging of data over 50 km. The induced biases due to the non-linear IPDA lidar equation are not compliant with accuracy requirements. This paper analyzes averaging biases issues and suggests correction algorithms tested on realistic simulated scenes.

  15. Estimation of satellite position, clock and phase bias corrections

    Science.gov (United States)

    Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs

    2018-05-01

    Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.

  16. The relationship between attentional bias toward safety and driving behavior.

    Science.gov (United States)

    Zheng, Tingting; Qu, Weina; Zhang, Kan; Ge, Yan

    2016-11-01

    As implicit cognitive processes garner more and more importance, studies in the fields of healthy psychology and organizational safety research have focused on attentional bias, a kind of selective allocation of attentional resources in the early stage of cognitive processing. However, few studies have explored the role of attentional bias on driving behavior. This study assessed drivers' attentional bias towards safety-related words (ABS) using the dot-probe paradigm and self-reported daily driving behaviors. The results revealed significant negative correlations between attentional bias scores and several indicators of dangerous driving. Drivers with fewer dangerous driving behaviors showed greater ABS. We also built a significant linear regression model between ABS and the total DDDI score, as well as ABS and the number of accidents. Finally, we discussed the possible mechanism underlying these associations and several limitations of our study. This study opens up a new topic for the exploration of implicit processes in driving safety research. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. On the Importance of Reliable Covariate Measurement in Selection Bias Adjustments Using Propensity Scores

    Science.gov (United States)

    Steiner, Peter M.; Cook, Thomas D.; Shadish, William R.

    2011-01-01

    The effect of unreliability of measurement on propensity score (PS) adjusted treatment effects has not been previously studied. The authors report on a study simulating different degrees of unreliability in the multiple covariates that were used to estimate the PS. The simulation uses the same data as two prior studies. Shadish, Clark, and Steiner…

  18. Journal bias or author bias?

    Science.gov (United States)

    Harris, Ian

    2016-01-01

    I read with interest the comment by Mark Wilson in the Indian Journal of Medical Ethics regarding bias and conflicts of interest in medical journals. Wilson targets one journal (the New England Journal of Medicine: NEJM) and one particular "scandal" to make his point that journals' decisions on publication are biased by commercial conflicts of interest (CoIs). It is interesting that he chooses the NEJM which, by his own admission, had one of the strictest CoI policies and had published widely on this topic. The feeling is that if the NEJM can be guilty, they can all be guilty.

  19. Sensitivity analysis for publication bias in meta-analysis of diagnostic studies for a continuous biomarker.

    Science.gov (United States)

    Hattori, Satoshi; Zhou, Xiao-Hua

    2018-02-10

    Publication bias is one of the most important issues in meta-analysis. For standard meta-analyses to examine intervention effects, the funnel plot and the trim-and-fill method are simple and widely used techniques for assessing and adjusting for the influence of publication bias, respectively. However, their use may be subjective and can then produce misleading insights. To make a more objective inference for publication bias, various sensitivity analysis methods have been proposed, including the Copas selection model. For meta-analysis of diagnostic studies evaluating a continuous biomarker, the summary receiver operating characteristic (sROC) curve is a very useful method in the presence of heterogeneous cutoff values. To our best knowledge, no methods are available for evaluation of influence of publication bias on estimation of the sROC curve. In this paper, we introduce a Copas-type selection model for meta-analysis of diagnostic studies and propose a sensitivity analysis method for publication bias. Our method enables us to assess the influence of publication bias on the estimation of the sROC curve and then judge whether the result of the meta-analysis is sufficiently confident or should be interpreted with much caution. We illustrate our proposed method with real data. Copyright © 2017 John Wiley & Sons, Ltd.

  20. Front-side biasing of n-in-p silicon strip detectors

    CERN Document Server

    Baselga Bacardit, Marta; Dierlamm, Alexander Hermann; Dragicevic, Marko Gerhart; Konig, Axel; Pree, Elias; Metzler, Marius

    2018-01-01

    Front-side biasing is an alternative method to bias a silicon sensor. Instead of directly applying high voltage to the back-side, one can exploit the conductive properties of the edge region to bias a detector exclusively via top-side connections. This option can be beneficial for the detector design and might help to facilitate the assembly process of modules. The effective bias voltage is affected by the resistance of the edge region and the sensor current. The measurements of n-in-p sensors performed to qualify this concept have shown that the voltage drop emerging from this resistance is negligible before irradiation. After irradiation, however, the resistivity of the edge region increases with fluence and saturates in the region of 10$^{7}\\,\\Omega$ at a fluence of 1$\\,\\cdot\\,10^{15}\\,$n$_{\\textrm{eq}}$cm$^{-2}$. The measurements are complemented by TCAD simulations and interpretations of the observed effects.

  1. "Unreliability as a threat to understanding psychopathology: The cautionary tale of attentional bias": Correction to Rodebaugh et al. (2016).

    Science.gov (United States)

    2016-10-01

    Reports an error in "Unreliability as a threat to understanding psychopathology: The cautionary tale of attentional bias" by Thomas L. Rodebaugh, Rachel B. Scullin, Julia K. Langer, David J. Dixon, Jonathan D. Huppert, Amit Bernstein, Ariel Zvielli and Eric J. Lenze ( Journal of Abnormal Psychology , 2016[Aug], Vol 125[6], 840-851). There was an error in the Author Note concerning the support of the MacBrain Face Stimulus Set. The correct statement is provided. (The following abstract of the original article appeared in record 2016-30117-001.) The use of unreliable measures constitutes a threat to our understanding of psychopathology, because advancement of science using both behavioral and biologically oriented measures can only be certain if such measurements are reliable. Two pillars of the National Institute of Mental Health's portfolio-the Research Domain Criteria (RDoC) initiative for psychopathology and the target engagement initiative in clinical trials-cannot succeed without measures that possess the high reliability necessary for tests involving mediation and selection based on individual differences. We focus on the historical lack of reliability of attentional bias measures as an illustration of how reliability can pose a threat to our understanding. Our own data replicate previous findings of poor reliability for traditionally used scores, which suggests a serious problem with the ability to test theories regarding attentional bias. This lack of reliability may also suggest problems with the assumption (in both theory and the formula for the scores) that attentional bias is consistent and stable across time. In contrast, measures accounting for attention as a dynamic process in time show good reliability in our data. The field is sorely in need of research reporting findings and reliability for attentional bias scores using multiple methods, including those focusing on dynamic processes over time. We urge researchers to test and report reliability of

  2. Preference Bias of Head Orientation in Choosing between Two Non-durables

    Directory of Open Access Journals (Sweden)

    Hiroyuki eFunaya

    2015-06-01

    Full Text Available The goal of this study is to investigate how customers’ gaze, head and body orientations reflect their choices. Although the relationship between human choice and gaze behavior has been well studied, other behaviors such as head and body are unknown. We conducted a two-alternatives-forced-choice task to examine (1 whether preference bias, i.e. a positional bias in gaze, head and body toward the item that was later chosen, exists in choice, (2 when preference bias is observed and when prediction of the resulting choice becomes possible (3 whether human choice is affected when the body orientations are manipulated. We used real non-durable products (cheap snacks and clothing on a shopping shelf. The results showed that there was a significant preference bias in head orientation at the beginning one second when the subjects stood straight toward the shelf, and that the head orientation was more biased toward the selected item than the gaze and the center of pressure at the ending one second. Manipulating body orientation did not affect the result of choice. The preference bias detected by observing the head orientation would be useful in marketing science for predicting customers’ choice.

  3. Preference bias of head orientation in choosing between two non-durables.

    Science.gov (United States)

    Funaya, Hiroyuki; Shibata, Tomohiro

    2015-01-01

    The goal of this study is to investigate how customers' gaze, head and body orientations reflect their choices. Although the relationship between human choice and gaze behavior has been well-studied, other behaviors such as head and body are unknown. We conducted a two-alternatives-forced-choice task to examine (1) whether preference bias, i.e., a positional bias in gaze, head and body toward the item that was later chosen, exists in choice, (2) when preference bias is observed and when prediction of the resulting choice becomes possible (3) whether human choice is affected when the body orientations are manipulated. We used real non-durable products (cheap snacks and clothing) on a shopping shelf. The results showed that there was a significant preference bias in head orientation at the beginning 1 s when the subjects stood straight toward the shelf, and that the head orientation was more biased toward the selected item than the gaze and the center of pressure at the ending 1 s. Manipulating body orientation did not affect the result of choice. The preference bias detected by observing the head orientation would be useful in marketing science for predicting customers' choice.

  4. The role of cognitive biases in short-term psychodynamic psychotherapy.

    Science.gov (United States)

    Kramer, Ueli; Ortega, Diana; Ambresin, Gilles; Despland, Jean-Nicolas; de Roten, Yves

    2018-06-01

    The concept of biased thinking - or cognitive biases - is relevant to psychotherapy research and clinical conceptualization, beyond cognitive theories. The present naturalistic study aimed to examine the changes in biased thinking over the course of a short-term dynamic psychotherapy (STDP) and to discover potential links between these changes and symptomatic improvement. This study focuses on 32 self-referred patients consulting for Adjustment Disorder according to DSM-IV-TR. The therapists were experienced psychodynamically oriented psychiatrists and psychotherapists. Coding of cognitive biases (using the Cognitive Errors Rating Scale; CERS) was made by external raters based on transcripts of interviews of psychotherapy; the reliability of these ratings on a randomly chosen 24% of all sessions was established. Based on the Symptom Check List SCL-90-R given before and after, the Reliable Change Index (RCI) was used. The assessment of cognitive errors was done at three time points: early (session 4-7), mid-treatment (session 12-17), and close to the end (after session 20) of the treatment. The results showed that the total frequency of cognitive biases was stable over time (p = .20), which was true both for positive and for negative cognitive biases. In exploring the three main subscales of the CERS, we found a decrease in selective abstraction (p = .02) and an increase in personalization (p = .05). A significant link between RCI scores (outcome) and frequency of positive cognitive biases was found, suggesting that biases towards the positive might have a protective function in psychotherapy. Therapists may be attentive to changes in biased thinking across short-term dynamic psychotherapy for adjustment disorder. Therapists may foster the emergence of positive cognitive biases at mid-treatment for adjustment disorder. © 2017 The British Psychological Society.

  5. Automated detection of heuristics and biases among pathologists in a computer-based system.

    Science.gov (United States)

    Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia

    2013-08-01

    The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.

  6. Fat fraction bias correction using T1 estimates and flip angle mapping.

    Science.gov (United States)

    Yang, Issac Y; Cui, Yifan; Wiens, Curtis N; Wade, Trevor P; Friesen-Waldner, Lanette J; McKenzie, Charles A

    2014-01-01

    To develop a new method of reducing T1 bias in proton density fat fraction (PDFF) measured with iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL). PDFF maps reconstructed from high flip angle IDEAL measurements were simulated and acquired from phantoms and volunteer L4 vertebrae. T1 bias was corrected using a priori T1 values for water and fat, both with and without flip angle correction. Signal-to-noise ratio (SNR) maps were used to measure precision of the reconstructed PDFF maps. PDFF measurements acquired using small flip angles were then compared to both sets of corrected large flip angle measurements for accuracy and precision. Simulations show similar results in PDFF error between small flip angle measurements and corrected large flip angle measurements as long as T1 estimates were within one standard deviation from the true value. Compared to low flip angle measurements, phantom and in vivo measurements demonstrate better precision and accuracy in PDFF measurements if images were acquired at a high flip angle, with T1 bias corrected using T1 estimates and flip angle mapping. T1 bias correction of large flip angle acquisitions using estimated T1 values with flip angle mapping yields fat fraction measurements of similar accuracy and superior precision compared to low flip angle acquisitions. Copyright © 2013 Wiley Periodicals, Inc.

  7. Genome-wide analysis of codon usage bias in four sequenced cotton species.

    Science.gov (United States)

    Wang, Liyuan; Xing, Huixian; Yuan, Yanchao; Wang, Xianlin; Saeed, Muhammad; Tao, Jincai; Feng, Wei; Zhang, Guihua; Song, Xianliang; Sun, Xuezhen

    2018-01-01

    Codon usage bias (CUB) is an important evolutionary feature in a genome which provides important information for studying organism evolution, gene function and exogenous gene expression. The CUB and its shaping factors in the nuclear genomes of four sequenced cotton species, G. arboreum (A2), G. raimondii (D5), G. hirsutum (AD1) and G. barbadense (AD2) were analyzed in the present study. The effective number of codons (ENC) analysis showed the CUB was weak in these four species and the four subgenomes of the two tetraploids. Codon composition analysis revealed these four species preferred to use pyrimidine-rich codons more frequently than purine-rich codons. Correlation analysis indicated that the base content at the third position of codons affect the degree of codon preference. PR2-bias plot and ENC-plot analyses revealed that the CUB patterns in these genomes and subgenomes were influenced by combined effects of translational selection, directional mutation and other factors. The translational selection (P2) analysis results, together with the non-significant correlation between GC12 and GC3, further revealed that translational selection played the dominant role over mutation pressure in the codon usage bias. Through relative synonymous codon usage (RSCU) analysis, we detected 25 high frequency codons preferred to end with T or A, and 31 low frequency codons inclined to end with C or G in these four species and four subgenomes. Finally, 19 to 26 optimal codons with 19 common ones were determined for each species and subgenomes, which preferred to end with A or T. We concluded that the codon usage bias was weak and the translation selection was the main shaping factor in nuclear genes of these four cotton genomes and four subgenomes.

  8. A new method for mapping perceptual biases across visual space.

    Science.gov (United States)

    Finlayson, Nonie J; Papageorgiou, Andriani; Schwarzkopf, D Samuel

    2017-08-01

    How we perceive the environment is not stable and seamless. Recent studies found that how a person qualitatively experiences even simple visual stimuli varies dramatically across different locations in the visual field. Here we use a method we developed recently that we call multiple alternatives perceptual search (MAPS) for efficiently mapping such perceptual biases across several locations. This procedure reliably quantifies the spatial pattern of perceptual biases and also of uncertainty and choice. We show that these measurements are strongly correlated with those from traditional psychophysical methods and that exogenous attention can skew biases without affecting overall task performance. Taken together, MAPS is an efficient method to measure how an individual's perceptual experience varies across space.

  9. Picomolar detection limits with current-polarized Pb2+ ion-selective membranes.

    Science.gov (United States)

    Pergel, E; Gyurcsányi, R E; Tóth, K; Lindner, E

    2001-09-01

    Minor ion fluxes across ion-selective membranes bias submicromolar activity measurements with conventional ion-selective electrodes. When ion fluxes are balanced, the lower limit of detection is expected to be dramatically improved. As proof of principle, the flux of lead ions across an ETH 5435 ionophore-based lead-selective membrane was gradually compensated by applying a few nanoamperes of galvanostatic current. When the opposite ion fluxes were matched, and the undesirable leaching of primary ions was eliminated, Nernstian response down to 3 x 10(-12) M was achieved.

  10. Operator Bias in the Estimation of Arc Efficiency in Gas Tungsten Arc Welding

    Directory of Open Access Journals (Sweden)

    Fredrik Sikström

    2015-03-01

    Full Text Available In this paper the operator bias in the measurement process of arc efficiency in stationary direct current electrode negative gas tungsten arc welding is discussed. An experimental study involving 15 operators (enough to reach statistical significance has been carried out with the purpose to estimate the arc efficiency from a specific procedure for calorimetric experiments. The measurement procedure consists of three manual operations which introduces operator bias in the measurement process. An additional relevant experiment highlights the consequences of estimating the arc voltage by measuring the potential between the terminals of the welding power source instead of measuring the potential between the electrode contact tube and the workpiece. The result of the study is a statistical evaluation of the operator bias influence on the estimate, showing that operator bias is negligible in the estimate considered here. On the contrary the consequences of neglecting welding leads voltage drop results in a significant under estimation of the arc efficiency.

  11. Job strain and the risk of depression: is reporting biased?

    DEFF Research Database (Denmark)

    Kolstad, Henrik; Hansen, Åse Marie; Kærgaard, Anette

    2011-01-01

    It is unknown whether the relation between job strain and depression reflects causal characteristics of the working environment or reporting bias. The authors investigated reporting bias by analyzing individual versus work-unit measures of job strain and the risk of depressive symptoms (n = 287) ...

  12. Sources of method bias in social science research and recommendations on how to control it.

    Science.gov (United States)

    Podsakoff, Philip M; MacKenzie, Scott B; Podsakoff, Nathan P

    2012-01-01

    Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms "method" and "method bias" and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

  13. Biasing vector network analyzers using variable frequency and amplitude signals

    Science.gov (United States)

    Nobles, J. E.; Zagorodnii, V.; Hutchison, A.; Celinski, Z.

    2016-08-01

    We report the development of a test setup designed to provide a variable frequency biasing signal to a vector network analyzer (VNA). The test setup is currently used for the testing of liquid crystal (LC) based devices in the microwave region. The use of an AC bias for LC based devices minimizes the negative effects associated with ionic impurities in the media encountered with DC biasing. The test setup utilizes bias tees on the VNA test station to inject the bias signal. The square wave biasing signal is variable from 0.5 to 36.0 V peak-to-peak (VPP) with a frequency range of DC to 10 kHz. The test setup protects the VNA from transient processes, voltage spikes, and high-frequency leakage. Additionally, the signals to the VNA are fused to ½ amp and clipped to a maximum of 36 VPP based on bias tee limitations. This setup allows us to measure S-parameters as a function of both the voltage and the frequency of the applied bias signal.

  14. Measuring individual work performance: identifying and selecting indicators.

    Science.gov (United States)

    Koopmans, Linda; Bernaards, Claire M; Hildebrandt, Vincent H; de Vet, Henrica C W; van der Beek, Allard J

    2014-01-01

    Theoretically, individual work performance (IWP) can be divided into four dimensions: task performance, contextual performance, adaptive performance, and counterproductive work behavior. However, there is no consensus on the indicators used to measure these dimensions. This study was designed to (1) identify indicators for each dimension, (2) select the most relevant indicators, and (3) determine the relative weight of each dimension in ratings of work performance. IWP indicators were identified from multiple research disciplines, via literature, existing questionnaires, and expert interviews. Subsequently, experts selected the most relevant indicators per dimension and scored the relative weight of each dimension in ratings of IWP. In total, 128 unique indicators were identified. Twenty-three of these indicators were selected by experts as most relevant for measuring IWP. Task performance determined 36% of the work performance rating, while the other three dimensions respectively determined 22%, 20% and 21% of the rating. Notable consensus was found on relevant indicators of IWP, reducing the number from 128 to 23 relevant indicators. This provides an important step towards the development of a standardized, generic and short measurement instrument for assessing IWP.

  15. Best Practices in Hiring: Addressing Unconscious Bias

    Science.gov (United States)

    Simpson, Caroline E.

    2012-01-01

    Research has shown that implementing certain hiring practices will increase diversity in the workplace while enhancing academic quality. All of these practices rely on addressing the issue of 'unconscious bias.' A brief overview of unconscious bias--what it is, how it works, and simple measures to counter it--will be presented. Successful strategies, actions, and recommendations for implementing best recruiting and hiring practices, which have been proven to enhance academic excellence by ensuring a deep and diverse applicant pool, will also be presented.

  16. Is perception of gender biased by a context prime?

    DEFF Research Database (Denmark)

    Skewes, Lea; Mørch Zederkof, Julie; Skewes, Joshua Charles

    2016-01-01

    It is well-documented on both explicit and implicit measures that men are associated with agential traits, while women are associated with communal traits, and that these explicit and implicit attitudes and cognitions lead to biases in behaviour. However, little is known about whether information...... about gender is already biased when it enters the cognitive system. We explored whether the same kinds of biases, which pervade implicit attitudes and cognition also pervade peoples’ perception of gender. Using a Bayesian signal detection model, we provide strong evidence that gender stereotypical...

  17. Spatial Bias in Field-Estimated Unsaturated Hydraulic Properties

    Energy Technology Data Exchange (ETDEWEB)

    HOLT,ROBERT M.; WILSON,JOHN L.; GLASS JR.,ROBERT J.

    2000-12-21

    Hydraulic property measurements often rely on non-linear inversion models whose errors vary between samples. In non-linear physical measurement systems, bias can be directly quantified and removed using calibration standards. In hydrologic systems, field calibration is often infeasible and bias must be quantified indirectly. We use a Monte Carlo error analysis to indirectly quantify spatial bias in the saturated hydraulic conductivity, K{sub s}, and the exponential relative permeability parameter, {alpha}, estimated using a tension infiltrometer. Two types of observation error are considered, along with one inversion-model error resulting from poor contact between the instrument and the medium. Estimates of spatial statistics, including the mean, variance, and variogram-model parameters, show significant bias across a parameter space representative of poorly- to well-sorted silty sand to very coarse sand. When only observation errors are present, spatial statistics for both parameters are best estimated in materials with high hydraulic conductivity, like very coarse sand. When simple contact errors are included, the nature of the bias changes dramatically. Spatial statistics are poorly estimated, even in highly conductive materials. Conditions that permit accurate estimation of the statistics for one of the parameters prevent accurate estimation for the other; accurate regions for the two parameters do not overlap in parameter space. False cross-correlation between estimated parameters is created because estimates of K{sub s} also depend on estimates of {alpha} and both parameters are estimated from the same data.

  18. A test of the critical assumption of the sensory bias model for the evolution of female mating preference using neural networks.

    Science.gov (United States)

    Fuller, Rebecca C

    2009-07-01

    The sensory bias model for the evolution of mating preferences states that mating preferences evolve as correlated responses to selection on nonmating behaviors sharing a common sensory system. The critical assumption is that pleiotropy creates genetic correlations that affect the response to selection. I simulated selection on populations of neural networks to test this. First, I selected for various combinations of foraging and mating preferences. Sensory bias predicts that populations with preferences for like-colored objects (red food and red mates) should evolve more readily than preferences for differently colored objects (red food and blue mates). Here, I found no evidence for sensory bias. The responses to selection on foraging and mating preferences were independent of one another. Second, I selected on foraging preferences alone and asked whether there were correlated responses for increased mating preferences for like-colored mates. Here, I found modest evidence for sensory bias. Selection for a particular foraging preference resulted in increased mating preference for similarly colored mates. However, the correlated responses were small and inconsistent. Selection on foraging preferences alone may affect initial levels of mating preferences, but these correlations did not constrain the joint evolution of foraging and mating preferences in these simulations.

  19. A biased activation theory of the cognitive and attentional modulation of emotion.

    Science.gov (United States)

    Rolls, Edmund T

    2013-01-01

    Cognition can influence emotion by biasing neural activity in the first cortical region in which the reward value and subjective pleasantness of stimuli is made explicit in the representation, the orbitofrontal cortex (OFC). The same effect occurs in a second cortical tier for emotion, the anterior cingulate cortex (ACC). Similar effects are found for selective attention, to for example the pleasantness vs. the intensity of stimuli, which modulates representations of reward value and affect in the orbitofrontal and anterior cingulate cortices. The mechanisms for the effects of cognition and attention on emotion are top-down biased competition and top-down biased activation. Affective and mood states can in turn influence memory and perception, by backprojected biasing influences. Emotion-related decision systems operate to choose between gene-specified rewards such as taste, touch, and beauty. Reasoning processes capable of planning ahead with multiple steps held in working memory in the explicit system can allow the gene-specified rewards not to be selected, or to be deferred. The stochastic, noisy, dynamics of decision-making systems in the brain may influence whether decisions are made by the selfish-gene-specified reward emotion system, or by the cognitive reasoning system that explicitly calculates reward values that are in the interests of the individual, the phenotype.

  20. A biased activation theory of the cognitive and attentional modulation of emotion

    Directory of Open Access Journals (Sweden)

    Edmund eRolls

    2013-03-01

    Full Text Available Cognition can influence emotion by biasing neural activity in the first cortical region in which the reward value and subjective pleasantness of stimuli is made explicit in the representation, the orbitofrontal cortex. The same effect occurs in a second cortical tier for emotion, the anterior cingulate cortex. Similar effects are found for selective attention, to for example the pleasantness vs the intensity of stimuli, which modulates representations of reward value and affect in the orbitofrontal and anterior cingulate cortices. The mechanisms for the effects of cognition and attention on emotion are top-down biased competition and top-down biased activation. Affective and mood states can in turn influence memory and perception, by backprojected biasing influences. Emotion-related decision systems operate to choose between gene-specified rewards such as taste, touch, and beauty. Reasoning processes capable of planning ahead with multiple steps held in working memory in the explicit system can allow the gene-specified rewards not to be selected, or to be deferred. The stochastic, noisy, dynamics of decision-making systems in the brain may influence whether decisions are made by the selfish-gene-specified reward emotion system, or by the cognitive reasoning system that explicitly calculates reward values that are in the interests of the individual, the phenotype.

  1. Body image related negative interpretation bias in anorexia nervosa.

    Science.gov (United States)

    Brockmeyer, Timo; Anderle, Alisa; Schmidt, Hagen; Febry, Stephanie; Wünsch-Leiteritz, Wally; Leiteritz, Andreas; Friederich, Hans-Christoph

    2018-05-01

    A distorted body image and pronounced body dissatisfaction are hallmarks of anorexia nervosa (AN) that typically result in dietary restraint and compensatory behaviours. Cognitive biases such as negative interpretation bias are considered key maintaining factors of these maladaptive cognitions and behaviours. However, little attention has been paid to empirical tests whether negative interpretation bias exists in AN and to what degree it is associated with symptom severity. Participants in the present study were 40 women with AN and 40 healthy women with no history of an eating disorder. Body-related negative interpretation bias (i.e., a tendency to interpret ambiguous information about the own body in a negative way) was measured by a Scrambled Sentences Task. Patients with AN showed a stronger body-related negative interpretation bias than healthy controls. Within both groups, negative interpretation bias correlated strongly and positively with AN symptom severity and these effects were not moderated by levels of depressive symptoms. The findings support the idea that biased interpretation of body-related information is associated with the specific psychopathology of AN. Targeted, computerised interventions (e.g. interpretation bias modification) may help to alter these dysfunctional cognitive schemas that lie at the heart of AN. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. New Trends in Magnetic Exchange Bias

    Science.gov (United States)

    Mougin, Alexandra; Mangin, Stéphane; Bobo, Jean-Francois; Loidl, Alois

    2005-05-01

    The study of layered magnetic structures is one of the hottest topics in magnetism due to the growing attraction of applications in magnetic sensors and magnetic storage media, such as random access memory. For almost half a century, new discoveries have driven researchers to re-investigate magnetism in thin film structures. Phenomena such as giant magnetoresistance, tunneling magnetoresistance, exchange bias and interlayer exchange coupling led to new ideas to construct devices, based not only on semiconductors but on a variety of magnetic materials Upon cooling fine cobalt particles in a magnetic field through the Néel temperature of their outer antiferromagnetic oxide layer, Meiklejohn and Bean discovered exchange bias in 1956. The exchange bias effect through which an antiferromagnetic AF layer can cause an adjacent ferromagnetic F layer to develop a preferred direction of magnetization, is widely used in magnetoelectronics technology to pin the magnetization of a device reference layer in a desired direction. However, the origin and effects due to exchange interaction across the interface between antiferromagneic and ferromagnetic layers are still debated after about fifty years of research, due to the extreme difficulty associated with the determination of the magnetic interfacial structure in F/AF bilayers. Indeed, in an AF/F bilayer system, the AF layer acts as “the invisible man” during conventional magnetic measurements and the presence of the exchange coupling is evidenced indirectly through the unusual behavior of the adjacent F layer. Basically, the coercive field of the F layer increases in contact with the AF and, in some cases, its hysteresis loop is shifted by an amount called exchange bias field. Thus, AF/F exchange coupling generates a new source of anisotropy in the F layer. This induced anisotropy strongly depends on basic features such as the magnetocrystalline anisotropy, crystallographic and spin structures, defects, domain patterns etc

  3. Measuring online interpretations and attributions of social situations: Links with adolescent social anxiety.

    Science.gov (United States)

    Haller, Simone P W; Raeder, Sophie M; Scerif, Gaia; Cohen Kadosh, Kathrin; Lau, Jennifer Y F

    2016-03-01

    We evaluated the utility of a novel, picture-based tool to measure how adolescents interpret and attribute cause to social exchanges and whether biases in these processes relate to social anxiety. Briefly presented ambiguous visual social scenes, each containing a photograph of the adolescent as the protagonist, were followed by three possible interpretations (positive, negative, neutral/unrelated) and two possible causal attributions (internal, external) to which participants responded. Ninety-five adolescents aged 14 to 17 recruited from mainstream schools, with varying levels of social anxiety rated the likelihood of positive, negative and unrelated interpretations before selecting the single interpretation they deemed as most likely. This was followed by a question prompting them to decide between an internal or external causal attribution for the interpreted event. Across scenarios, adolescents with higher levels of social anxiety rated negative interpretations as more likely and positive interpretations as less likely compared to lower socially anxious adolescents. Higher socially anxious adolescents were also more likely to select internal attributions to negative and less likely to select internal attributions for positive events than adolescents with lower levels of social anxiety. Adolescents with higher social anxiety display cognitive biases in interpretation and attribution. This tool is suitable for measuring cognitive biases of complex visual-social cues in youth populations with social anxiety and simulates the demands of daily social experiences more closely. As we did not measure depressive symptoms, we cannot be sure that biases linked to social anxiety are not due to concurrent low mood. Copyright © 2015. Published by Elsevier Ltd.

  4. Higher cortisol levels at diurnal trough predict greater attentional bias towards threat in healthy young adults.

    Science.gov (United States)

    Hakamata, Yuko; Izawa, Shuhei; Sato, Eisuke; Komi, Shotaro; Murayama, Norio; Moriguchi, Yoshiya; Hanakawa, Takashi; Inoue, Yusuke; Tagaya, Hirokuni

    2013-11-01

    Attentional bias (AB), selective information processing towards threat, can exacerbate anxiety and depression. Despite growing interest, physiological determinants of AB are yet to be understood. We examined whether stress hormone cortisol and its diurnal variation pattern contribute to AB. Eighty-seven healthy young adults underwent assessments for AB, anxious personality traits, depressive symptoms, and attentional function. Salivary cortisol was collected at three time points daily (at awakening, 30 min after awakening, and bedtime) for 2 consecutive days. We performed: (1) multiple regression analysis to examine the relationships between AB and the other measures and (2) analysis of variance (ANOVA) between groups with different cortisol variation patterns for the other measures. Multiple regression analysis revealed that higher cortisol levels at bedtime (pattention and cortisol measurement at three time points daily. We showed that higher cortisol levels at bedtime and blunted cortisol variation are associated with greater AB. Individuals who have higher cortisol levels at diurnal trough might be at risk of clinical anxiety or depression but could also derive more benefits from the attentional-bias-modification program. © 2013 Elsevier B.V. All rights reserved.

  5. Quantification of intervertebral displacement with a novel MRI-based modeling technique: Assessing measurement bias and reliability with a porcine spine model.

    Science.gov (United States)

    Mahato, Niladri K; Montuelle, Stephane; Goubeaux, Craig; Cotton, John; Williams, Susan; Thomas, James; Clark, Brian C

    2017-05-01

    The purpose of this study was to develop a novel magnetic resonance imaging (MRI)-based modeling technique for measuring intervertebral displacements. Here, we present the measurement bias and reliability of the developmental work using a porcine spine model. Porcine lumbar vertebral segments were fitted in a custom-built apparatus placed within an externally calibrated imaging volume of an open-MRI scanner. The apparatus allowed movement of the vertebrae through pre-assigned magnitudes of sagittal and coronal translation and rotation. The induced displacements were imaged with static (T 1 ) and fast dynamic (2D HYCE S) pulse sequences. These images were imported into animation software, in which these images formed a background 'scene'. Three-dimensional models of vertebrae were created using static axial scans from the specimen and then transferred into the animation environment. In the animation environment, the user manually moved the models (rotoscoping) to perform model-to-'scene' matching to fit the models to their image silhouettes and assigned anatomical joint axes to the motion-segments. The animation protocol quantified the experimental translation and rotation displacements between the vertebral models. Accuracy of the technique was calculated as 'bias' using a linear mixed effects model, average percentage error and root mean square errors. Between-session reliability was examined by computing intra-class correlation coefficients (ICC) and the coefficient of variations (CV). For translation trials, a constant bias (β 0 ) of 0.35 (±0.11) mm was detected for the 2D HYCE S sequence (p=0.01). The model did not demonstrate significant additional bias with each mm increase in experimental translation (β 1 Displacement=0.01mm; p=0.69). Using the T 1 sequence for the same assessments did not significantly change the bias (p>0.05). ICC values for the T 1 and 2D HYCE S pulse sequences were 0.98 and 0.97, respectively. For rotation trials, a constant bias (

  6. Simultaneous perceptual and response biases on sequential face attractiveness judgments

    Science.gov (United States)

    Pegors, Teresa K.; Mattar, Marcelo G.; Bryan, Peter B.; Epstein, Russell A.

    2015-01-01

    Face attractiveness is a social characteristic that we often use to make first-pass judgments about the people around us. However, these judgments are highly influenced by our surrounding social world, and researchers still understand little about the mechanisms underlying these influences. In a series of three experiments, we used a novel sequential rating paradigm that enabled us to measure biases on attractiveness judgments from the previous face and the previous rating. Our results revealed two simultaneous and opposing influences on face attractiveness judgments that arise from our past experience of faces: a response bias in which attractiveness ratings shift towards a previously given rating, and a stimulus bias in which attractiveness ratings shift away from the mean attractiveness of the previous face. Furthermore, we provide evidence that the contrastive stimulus bias (but not the assimilative response bias) is strengthened by increasing the duration of the previous stimulus, suggesting an underlying perceptual mechanism. These results demonstrate that judgments of face attractiveness are influenced by information from our evaluative and perceptual history and that these influences have measurable behavioral effects over the course of just a few seconds. PMID:25867223

  7. Overweight people have low levels of implicit weight bias, but overweight nations have high levels of implicit weight bias.

    Directory of Open Access Journals (Sweden)

    Maddalena Marini

    Full Text Available Although a greater degree of personal obesity is associated with weaker negativity toward overweight people on both explicit (i.e., self-report and implicit (i.e., indirect behavioral measures, overweight people still prefer thin people on average. We investigated whether the national and cultural context - particularly the national prevalence of obesity - predicts attitudes toward overweight people independent of personal identity and weight status. Data were collected from a total sample of 338,121 citizens from 71 nations in 22 different languages on the Project Implicit website (https://implicit.harvard.edu/ between May 2006 and October 2010. We investigated the relationship of the explicit and implicit weight bias with the obesity both at the individual (i.e., across individuals and national (i.e., across nations level. Explicit weight bias was assessed with self-reported preference between overweight and thin people; implicit weight bias was measured with the Implicit Association Test (IAT. The national estimates of explicit and implicit weight bias were obtained by averaging the individual scores for each nation. Obesity at the individual level was defined as Body Mass Index (BMI scores, whereas obesity at the national level was defined as three national weight indicators (national BMI, national percentage of overweight and underweight people obtained from publicly available databases. Across individuals, greater degree of obesity was associated with weaker implicit negativity toward overweight people compared to thin people. Across nations, in contrast, a greater degree of national obesity was associated with stronger implicit negativity toward overweight people compared to thin people. This result indicates a different relationship between obesity and implicit weight bias at the individual and national levels.

  8. Parallel bias vs perpendicular bias of a ferrite tuned cavity for the TRIUMF KAON Factory booster ring

    International Nuclear Information System (INIS)

    Poirier, R.L.; Enegren, T.A.

    1988-06-01

    The RF cavity reference design for the KAON Factory booster ring is a double gap drift-tube cavity with parallel biased ferrite tuners to vary the frequency from 46 MHz to 62 MHz. LAMPF has developed a single gap cavity with perpendicularly biased ferrite to vary the frequency from 50 MHz to 60 MHz. Measurements on the LAMPF cavity have indicated that their frequency range could be extended to cover our requirements while still maintaining a reasonable magnetic Q. The analysis and comparison of the RF circuit and the AC magnetizing circuit for both designs are reported. (Author) (14 refs., 6 figs.)

  9. Global-local visual biases correspond with visual-spatial orientation.

    Science.gov (United States)

    Basso, Michael R; Lowery, Natasha

    2004-02-01

    Within the past decade, numerous investigations have demonstrated reliable associations of global-local visual processing biases with right and left hemisphere function, respectively (cf. Van Kleeck, 1989). Yet the relevance of these biases to other cognitive functions is not well understood. Towards this end, the present research examined the relationship between global-local visual biases and perception of visual-spatial orientation. Twenty-six women and 23 men completed a global-local judgment task (Kimchi and Palmer, 1982) and the Judgment of Line Orientation Test (JLO; Benton, Sivan, Hamsher, Varney, and Spreen, 1994), a measure of visual-spatial orientation. As expected, men had better performance on JLO. Extending previous findings, global biases were related to better visual-spatial acuity on JLO. The findings suggest that global-local biases and visual-spatial orientation may share underlying cerebral mechanisms. Implications of these findings for other visually mediated cognitive outcomes are discussed.

  10. Mutation-selection models of codon substitution and their use to estimate selective strengths on codon usage

    DEFF Research Database (Denmark)

    Yang, Ziheng; Nielsen, Rasmus

    2008-01-01

    Current models of codon substitution are formulated at the levels of nucleotide substitution and do not explicitly consider the separate effects of mutation and selection. They are thus incapable of inferring whether mutation or selection is responsible for evolution at silent sites. Here we impl...... codon usage in mammals. Estimates of selection coefficients nevertheless suggest that selection on codon usage is weak and most mutations are nearly neutral. The sensitivity of the analysis on the assumed mutation model is discussed.......Current models of codon substitution are formulated at the levels of nucleotide substitution and do not explicitly consider the separate effects of mutation and selection. They are thus incapable of inferring whether mutation or selection is responsible for evolution at silent sites. Here we...... implement a few population genetics models of codon substitution that explicitly consider mutation bias and natural selection at the DNA level. Selection on codon usage is modeled by introducing codon-fitness parameters, which together with mutation-bias parameters, predict optimal codon frequencies...

  11. Determinants of Colour Constancy and the Blue Bias

    Science.gov (United States)

    Gegenfurtner, Karl

    2017-01-01

    We investigated several sensory and cognitive determinants of colour constancy across 40 illumination hues. In the first experiment, we measured colour naming for the illumination and for the colour induced by the illumination on the colorimetric grey. Results confirmed that the induced colours are approximately complementary to the colour of the illumination. In the second experiment, we measured colour constancy using achromatic adjustments. Average colour constancy was perfect under the blue daylight illumination and decreased in colour directions away from the blue daylight illumination due to undershooting and a strong blue bias. Apart from this blue bias, colour constancy was not related to illumination discrimination and to chromatic detection measured previously with the same setup and stimuli. We also observed a strong negative relationship between the degree of colour constancy and the consensus of naming the illumination colour. Constancy coincided with a low naming consensus, in particular because bluish illumination colours were sometimes seen as achromatic. Blue bias and category consensus alone explained >68%, and all determinants together explained >94% of the variance of achromatic adjustments. These findings suggest that colour constancy is optimised for blue daylight. PMID:29348910

  12. Accounting for response misclassification and covariate measurement error improves power and reduces bias in epidemiologic studies.

    Science.gov (United States)

    Cheng, Dunlei; Branscum, Adam J; Stamey, James D

    2010-07-01

    To quantify the impact of ignoring misclassification of a response variable and measurement error in a covariate on statistical power, and to develop software for sample size and power analysis that accounts for these flaws in epidemiologic data. A Monte Carlo simulation-based procedure is developed to illustrate the differences in design requirements and inferences between analytic methods that properly account for misclassification and measurement error to those that do not in regression models for cross-sectional and cohort data. We found that failure to account for these flaws in epidemiologic data can lead to a substantial reduction in statistical power, over 25% in some cases. The proposed method substantially reduced bias by up to a ten-fold margin compared to naive estimates obtained by ignoring misclassification and mismeasurement. We recommend as routine practice that researchers account for errors in measurement of both response and covariate data when determining sample size, performing power calculations, or analyzing data from epidemiological studies. 2010 Elsevier Inc. All rights reserved.

  13. Opportunity to Learn, Test Bias, and School Effects.

    Science.gov (United States)

    Anderson, Lorin W.

    The purpose of the study was to examine test bias and the "non-effects" of schooling. Teachers were given a list of words selected from standardized vocabulary tests and asked to indicate the words they had taught. The words were classified by the grade level at which they were first introduced. Ninety-five third-grade students in four schools…

  14. Nonperturbative theory of weak pre- and post-selected measurements

    Energy Technology Data Exchange (ETDEWEB)

    Kofman, Abraham G., E-mail: kofmana@gmail.com; Ashhab, Sahel; Nori, Franco

    2012-11-01

    This paper starts with a brief review of the topic of strong and weak pre- and post-selected (PPS) quantum measurements, as well as weak values, and afterwards presents original work. In particular, we develop a nonperturbative theory of weak PPS measurements of an arbitrary system with an arbitrary meter, for arbitrary initial states of the system and the meter. New and simple analytical formulas are obtained for the average and the distribution of the meter pointer variable. These formulas hold to all orders in the weak value. In the case of a mixed preselected state, in addition to the standard weak value, an associated weak value is required to describe weak PPS measurements. In the linear regime, the theory provides the generalized Aharonov–Albert–Vaidman formula. Moreover, we reveal two new regimes of weak PPS measurements: the strongly-nonlinear regime and the inverted region (the regime with a very large weak value), where the system-dependent contribution to the pointer deflection decreases with increasing the measurement strength. The optimal conditions for weak PPS measurements are obtained in the strongly-nonlinear regime, where the magnitude of the average pointer deflection is equal or close to the maximum. This maximum is independent of the measurement strength, being typically of the order of the pointer uncertainty. In the optimal regime, the small parameter of the theory is comparable to the overlap of the pre- and post-selected states. We show that the amplification coefficient in the weak PPS measurements is generally a product of two qualitatively different factors. The effects of the free system and meter Hamiltonians are discussed. We also estimate the size of the ensemble required for a measurement and identify optimal and efficient meters for weak measurements. Exact solutions are obtained for a certain class of the measured observables. These solutions are used for numerical calculations, the results of which agree with the theory

  15. Nonperturbative theory of weak pre- and post-selected measurements

    International Nuclear Information System (INIS)

    Kofman, Abraham G.; Ashhab, Sahel; Nori, Franco

    2012-01-01

    This paper starts with a brief review of the topic of strong and weak pre- and post-selected (PPS) quantum measurements, as well as weak values, and afterwards presents original work. In particular, we develop a nonperturbative theory of weak PPS measurements of an arbitrary system with an arbitrary meter, for arbitrary initial states of the system and the meter. New and simple analytical formulas are obtained for the average and the distribution of the meter pointer variable. These formulas hold to all orders in the weak value. In the case of a mixed preselected state, in addition to the standard weak value, an associated weak value is required to describe weak PPS measurements. In the linear regime, the theory provides the generalized Aharonov–Albert–Vaidman formula. Moreover, we reveal two new regimes of weak PPS measurements: the strongly-nonlinear regime and the inverted region (the regime with a very large weak value), where the system-dependent contribution to the pointer deflection decreases with increasing the measurement strength. The optimal conditions for weak PPS measurements are obtained in the strongly-nonlinear regime, where the magnitude of the average pointer deflection is equal or close to the maximum. This maximum is independent of the measurement strength, being typically of the order of the pointer uncertainty. In the optimal regime, the small parameter of the theory is comparable to the overlap of the pre- and post-selected states. We show that the amplification coefficient in the weak PPS measurements is generally a product of two qualitatively different factors. The effects of the free system and meter Hamiltonians are discussed. We also estimate the size of the ensemble required for a measurement and identify optimal and efficient meters for weak measurements. Exact solutions are obtained for a certain class of the measured observables. These solutions are used for numerical calculations, the results of which agree with the theory

  16. Nucleotide composition bias and codon usage trends of gene ...

    Indian Academy of Sciences (India)

    2015-06-10

    Jun 10, 2015 ... In a wide variety of organisms, synonymous codons are selected with different ... In addition, a series of GC skew and AT skew data was calculated for codon positions 1, ..... bias from different perspectives. Interestingly .... This study was supported by programme for Changjiang Scholars and Innovative ...

  17. CPI Bias in Korea

    Directory of Open Access Journals (Sweden)

    Chul Chung

    2007-12-01

    Full Text Available We estimate the CPI bias in Korea by employing the approach of Engel’s Law as suggested by Hamilton (2001. This paper is the first attempt to estimate the bias using Korean panel data, Korean Labor and Income Panel Study(KLIPS. Following Hamilton’s model with non­linear specification correction, our estimation result shows that the cumulative CPI bias over the sample period (2000-2005 was 0.7 percent annually. This CPI bias implies that about 21 percent of the inflation rate during the period can be attributed to the bias. In light of purchasing power parity, we provide an interpretation of the estimated bias.

  18. TCABR Tokamak scrape-off layer turbulence with DC biasing

    International Nuclear Information System (INIS)

    Heller, M.V.A.P.; Ferreira, A.A.; Caldas, I.L.; Nascimento, I.C.

    2004-01-01

    Turbulence and particle transport in plasma scrape-off layer have been controlled by external electric fields. This control can be achieved by a biasing electrode located inside the plasma. We investigate plasma turbulence changes in the scrape-off layer of TCABR tokamak introduced by DC biasing an electrode inside the plasma. Our investigation is based on the alterations observed on the wavelet power spectra and on the intermittent burst sequences of plasma potential and density fluctuations measured by a set of Langmuir probes. Biasing the electrode changes the turbulence statistics and the bursts intermittence. With the imposed external electric field, fluctuation amplitudes, phase velocities, and anomalous particle transport are modified. Transport reduction for higher frequencies induced by the biasing could be due to the strong de-phasing between density and potential fluctuations. The mode coupling increases with the perturbation for the high frequency broadband fluctuations. The total (laminar and bursting) radial particle transport is reduced by about 25% by DC biasing. Bursts contribution to total transport is 15% and for the studied conditions this contribution does not change much with the bias perturbation

  19. Ensemble stacking mitigates biases in inference of synaptic connectivity

    Directory of Open Access Journals (Sweden)

    Brendan Chambers

    2018-03-01

    Full Text Available A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches. Mapping the routing of spikes through local circuitry is crucial for understanding neocortical computation. Under appropriate experimental conditions, these maps can be used to infer likely patterns of synaptic recruitment, linking activity to underlying anatomical connections. Such inferences help to reveal the synaptic implementation of population dynamics and computation. We compare a number of standard functional measures to infer underlying connectivity. We find that regularization impacts measures

  20. Children do not exhibit ambiguity aversion despite intact familiarity bias.

    Science.gov (United States)

    Li, Rosa; Brannon, Elizabeth M; Huettel, Scott A

    2014-01-01

    The phenomenon of ambiguity aversion, in which risky gambles with known probabilities are preferred over ambiguous gambles with unknown probabilities, has been thoroughly documented in adults but never measured in children. Here, we use two distinct tasks to investigate ambiguity preferences of children (8- to 9-year-olds) and a comparison group of adults (19- to 27-year-olds). Across three separate measures, we found evidence for significant ambiguity aversion in adults but not in children and for greater ambiguity aversion in adults compared to children. As ambiguity aversion in adults has been theorized to result from a preference to bet on the known and avoid the unfamiliar, we separately measured familiarity bias and found that children, like adults, are biased towards the familiar. Our findings indicate that ambiguity aversion emerges across the course of development between childhood and adolescence, while a familiarity bias is already present in childhood.

  1. Adaptive measurement selection for progressive damage estimation

    Science.gov (United States)

    Zhou, Wenfan; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Chattopadhyay, Aditi; Peralta, Pedro

    2011-04-01

    Noise and interference in sensor measurements degrade the quality of data and have a negative impact on the performance of structural damage diagnosis systems. In this paper, a novel adaptive measurement screening approach is presented to automatically select the most informative measurements and use them intelligently for structural damage estimation. The method is implemented efficiently in a sequential Monte Carlo (SMC) setting using particle filtering. The noise suppression and improved damage estimation capability of the proposed method is demonstrated by an application to the problem of estimating progressive fatigue damage in an aluminum compact-tension (CT) sample using noisy PZT sensor measurements.

  2. A scanning tunneling microscope break junction method with continuous bias modulation.

    Science.gov (United States)

    Beall, Edward; Yin, Xing; Waldeck, David H; Wierzbinski, Emil

    2015-09-28

    Single molecule conductance measurements on 1,8-octanedithiol were performed using the scanning tunneling microscope break junction method with an externally controlled modulation of the bias voltage. Application of an AC voltage is shown to improve the signal to noise ratio of low current (low conductance) measurements as compared to the DC bias method. The experimental results show that the current response of the molecule(s) trapped in the junction and the solvent media to the bias modulation can be qualitatively different. A model RC circuit which accommodates both the molecule and the solvent is proposed to analyze the data and extract a conductance for the molecule.

  3. The relationships between common measures of glucose meter performance.

    Science.gov (United States)

    Wilmoth, Daniel R

    2012-09-01

    Glucose meter performance is commonly measured in several different ways, including the relative bias and coefficient of variation (CV), the total error, the mean absolute relative deviation (MARD), and the size of the interval around the reference value that would be necessary to contain a meter measurement at a specified probability. This fourth measure is commonly expressed as a proportion of the reference value and will be referred to as the necessary relative deviation. A deeper understanding of the relationships between these measures may aid health care providers, patients, and regulators in comparing meter performances when different measures are used. The relationships between common measures of glucose meter performance were derived mathematically. Equations are presented for calculating the total error, MARD, and necessary relative deviation using the reference value, relative bias, and CV when glucose meter measurements are normally distributed. When measurements are also unbiased, the CV, total error, MARD, and necessary relative deviation are linearly related and are therefore equivalent measures of meter performance. The relative bias and CV provide more information about meter performance than the other measures considered but may be difficult for some audiences to interpret. Reporting meter performance in multiple ways may facilitate the informed selection of blood glucose meters. © 2012 Diabetes Technology Society.

  4. Using Machine Learning to Predict MCNP Bias

    Energy Technology Data Exchange (ETDEWEB)

    Grechanuk, Pavel Aleksandrovi [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-01-09

    For many real-world applications in radiation transport where simulations are compared to experimental measurements, like in nuclear criticality safety, the bias (simulated - experimental keff) in the calculation is an extremely important quantity used for code validation. The objective of this project is to accurately predict the bias of MCNP6 [1] criticality calculations using machine learning (ML) algorithms, with the intention of creating a tool that can complement the current nuclear criticality safety methods. In the latest release of MCNP6, the Whisper tool is available for criticality safety analysts and includes a large catalogue of experimental benchmarks, sensitivity profiles, and nuclear data covariance matrices. This data, coming from 1100+ benchmark cases, is used in this study of ML algorithms for criticality safety bias predictions.

  5. Virtual tape measure for the operating microscope: system specifications and performance evaluation.

    Science.gov (United States)

    Kim, M Y; Drake, J M; Milgram, P

    2000-01-01

    The Virtual Tape Measure for the Operating Microscope (VTMOM) was created to assist surgeons in making accurate 3D measurements of anatomical structures seen in the surgical field under the operating microscope. The VTMOM employs augmented reality techniques by combining stereoscopic video images with stereoscopic computer graphics, and functions by relying on an operator's ability to align a 3D graphic pointer, which serves as the end-point of the virtual tape measure, with designated locations on the anatomical structure being measured. The VTMOM was evaluated for its baseline and application performances as well as its application efficacy. Baseline performance was determined by measuring the mean error (bias) and standard deviation of error (imprecision) in measurements of non-anatomical objects. Application performance was determined by comparing the error in measuring the dimensions of aneurysm models with and without the VTMOM. Application efficacy was determined by comparing the error in selecting the appropriate aneurysm clip size with and without the VTMOM. Baseline performance indicated a bias of 0.3 mm and an imprecision of 0.6 mm. Application bias was 3.8 mm and imprecision was 2.8 mm for aneurysm diameter. The VTMOM did not improve aneurysm clip size selection accuracy. The VTMOM is a potentially accurate tool for use under the operating microscope. However, its performance when measuring anatomical objects is highly dependent on complex visual features of the object surfaces. Copyright 2000 Wiley-Liss, Inc.

  6. Normalization Approaches for Removing Systematic Biases Associated with Mass Spectrometry and Label-Free Proteomics

    Energy Technology Data Exchange (ETDEWEB)

    Callister, Stephen J.; Barry, Richard C.; Adkins, Joshua N.; Johnson, Ethan T.; Qian, Weijun; Webb-Robertson, Bobbie-Jo M.; Smith, Richard D.; Lipton, Mary S.

    2006-02-01

    Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS). Arbitrary abundances of peptides were obtained from three sample sets, including a standard protein sample, two Deinococcus radiodurans samples taken from different growth phases, and two mouse striatum samples from control and methamphetamine-stressed mice (strain C57BL/6). The selected normalization techniques were evaluated in both the absence and presence of biological variability by estimating extraneous variability prior to and following normalization. Prior to normalization, replicate runs from each sample set were observed to be statistically different, while following normalization replicate runs were no longer statistically different. Although all techniques reduced systematic bias, assigned ranks among the techniques revealed significant trends. For most LC-FTICR MS analyses, linear regression normalization ranked either first or second among the four techniques, suggesting that this technique was more generally suitable for reducing systematic biases.

  7. Measurement of quasi-static and low frequency electric fields on the Viking satellite

    International Nuclear Information System (INIS)

    Block, L.P.; Faelthammar, C.G.; Lindqvist, P.A.; Marklund, G.T.; Mozer, F.S.; Pedersen, A.

    1987-03-01

    The instrument for measurement of quasi-static and low frequency (dc and slow varying) electric fields on the Viking satellite is described. The instrument uses three spherical probe pairs to measure the full three-dimensional electric field vector with 18.75 ms time resolution. The probes are kept near plasma potential by means of a controllable bias current. A guard covering part of the booms is biased to a negative voltage to prevent photoelectrons escaping from the probes from reaching the satellite body. Current-voltage sweeps are performed to determine the plasma density and temperature and to select the optimal bias current. The bias currents to the probes and the voltage offset on the guards as well as the current-voltage sweeps are controlled by an on-board microprocessor which can be programmed from the ground and allows great flexibility. (authors)

  8. Measuring implicit attitudes: A positive framing bias flaw in the Implicit Relational Assessment Procedure (IRAP).

    Science.gov (United States)

    O'Shea, Brian; Watson, Derrick G; Brown, Gordon D A

    2016-02-01

    How can implicit attitudes best be measured? The Implicit Relational Assessment Procedure (IRAP), unlike the Implicit Association Test (IAT), claims to measure absolute, not just relative, implicit attitudes. In the IRAP, participants make congruent (Fat Person-Active: false; Fat Person-Unhealthy: true) or incongruent (Fat Person-Active: true; Fat Person-Unhealthy: false) responses in different blocks of trials. IRAP experiments have reported positive or neutral implicit attitudes (e.g., neutral attitudes toward fat people) in cases in which negative attitudes are normally found on explicit or other implicit measures. It was hypothesized that these results might reflect a positive framing bias (PFB) that occurs when participants complete the IRAP. Implicit attitudes toward categories with varying prior associations (nonwords, social systems, flowers and insects, thin and fat people) were measured. Three conditions (standard, positive framing, and negative framing) were used to measure whether framing influenced estimates of implicit attitudes. It was found that IRAP scores were influenced by how the task was framed to the participants, that the framing effect was modulated by the strength of prior stimulus associations, and that a default PFB led to an overestimation of positive implicit attitudes when measured by the IRAP. Overall, the findings question the validity of the IRAP as a tool for the measurement of absolute implicit attitudes. A new tool (Simple Implicit Procedure:SIP) for measuring absolute, not just relative, implicit attitudes is proposed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  9. Think leader, think White? Capturing and weakening an implicit pro-White leadership bias.

    Science.gov (United States)

    Gündemir, Seval; Homan, Astrid C; de Dreu, Carsten K W; van Vugt, Mark

    2014-01-01

    Across four studies, we found evidence for an implicit pro-White leadership bias that helps explain the underrepresentation of ethnic minorities in leadership positions. Both White-majority and ethnic minority participants reacted significantly faster when ethnically White names and leadership roles (e.g., manager; Study 1) or leadership traits (e.g., decisiveness; Study 2 & 3) were paired in an Implicit Association Test (IAT) rather than when ethnic minority names and leadership traits were paired. Moreover, the implicit pro-White leadership bias showed discriminant validity with the conventional implicit bias measures (Study 3). Importantly, results showed that the pro-White leadership bias can be weakened when situational cues increase the salience of a dual identity (Study 4). This, in turn, can diminish the explicit pro-White bias in promotion related decision making processes (Study 4). This research offers a new tool to measure the implicit psychological processes underlying the underrepresentation of ethnic minorities in leadership positions and proposes interventions to weaken such biases.

  10. Think Leader, Think White? Capturing and Weakening an Implicit Pro-White Leadership Bias

    Science.gov (United States)

    Gündemir, Seval; Homan, Astrid C.; de Dreu, Carsten K. W.; van Vugt, Mark

    2014-01-01

    Across four studies, we found evidence for an implicit pro-White leadership bias that helps explain the underrepresentation of ethnic minorities in leadership positions. Both White-majority and ethnic minority participants reacted significantly faster when ethnically White names and leadership roles (e.g., manager; Study 1) or leadership traits (e.g., decisiveness; Study 2 & 3) were paired in an Implicit Association Test (IAT) rather than when ethnic minority names and leadership traits were paired. Moreover, the implicit pro-White leadership bias showed discriminant validity with the conventional implicit bias measures (Study 3). Importantly, results showed that the pro-White leadership bias can be weakened when situational cues increase the salience of a dual identity (Study 4). This, in turn, can diminish the explicit pro-White bias in promotion related decision making processes (Study 4). This research offers a new tool to measure the implicit psychological processes underlying the underrepresentation of ethnic minorities in leadership positions and proposes interventions to weaken such biases. PMID:24416181

  11. Think leader, think White? Capturing and weakening an implicit pro-White leadership bias.

    Directory of Open Access Journals (Sweden)

    Seval Gündemir

    Full Text Available Across four studies, we found evidence for an implicit pro-White leadership bias that helps explain the underrepresentation of ethnic minorities in leadership positions. Both White-majority and ethnic minority participants reacted significantly faster when ethnically White names and leadership roles (e.g., manager; Study 1 or leadership traits (e.g., decisiveness; Study 2 & 3 were paired in an Implicit Association Test (IAT rather than when ethnic minority names and leadership traits were paired. Moreover, the implicit pro-White leadership bias showed discriminant validity with the conventional implicit bias measures (Study 3. Importantly, results showed that the pro-White leadership bias can be weakened when situational cues increase the salience of a dual identity (Study 4. This, in turn, can diminish the explicit pro-White bias in promotion related decision making processes (Study 4. This research offers a new tool to measure the implicit psychological processes underlying the underrepresentation of ethnic minorities in leadership positions and proposes interventions to weaken such biases.

  12. Exploring the function of selective attention and hypervigilance for threat in anxiety.

    Science.gov (United States)

    Richards, Helen J; Benson, Valerie; Donnelly, Nick; Hadwin, Julie A

    2014-02-01

    Theoretical frameworks of anxiety propose that attentional biases to threat-related stimuli cause or maintain anxious states. The current paper draws on theoretical frameworks and key empirical studies to outline the distinctive attentional processes highlighted as being important in understanding anxiety. We develop a conceptual framework to make a distinction between two attentional biases: selective attention to threat and hypervigilance for threat. We suggest that these biases each have a different purpose and can account for the typical patterns of facilitated and impaired attention evident in anxious individuals. The framework is novel in its specification of the eye movement behavior associated with these attentional biases. We highlight that selective attention involves narrowing overt attention onto threat to ensure that these stimuli receive processing priority, leading to rapid engagement with task-relevant threat and delayed disengagement from task-irrelevant threat. We show that hypervigilance operates in the presence and absence of threat and involves monitoring for potential dangers via attentional broadening or excessive scanning of the environment with numerous eye movements, leading to improved threat detection and increased distraction from task-irrelevant threat. We conclude that future research could usefully employ eye movement measures to more clearly understand the diverse roles of attention in anxiety. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Measuring redshift-space distortions using photometric surveys

    OpenAIRE

    Ross, Ashley; Percival, Will; Crocce, M.; Cabre, A.; Gaztanaga, E.

    2011-01-01

    We outline how redshift-space distortions (RSD) can be measured from the angular correlation function w({\\theta}), of galaxies selected from photometric surveys. The natural degeneracy between RSD and galaxy bias can be minimized by comparing results from bins with top-hat galaxy selection in redshift, and bins based on the radial position of galaxy pair centres. This comparison can also be used to test the accuracy of the photometric redshifts. The presence of RSD will be clearly detectable ...

  14. Affective bias as a rational response to the statistics of rewards and punishments.

    Science.gov (United States)

    Pulcu, Erdem; Browning, Michael

    2017-10-04

    Affective bias, the tendency to differentially prioritise the processing of negative relative to positive events, is commonly observed in clinical and non-clinical populations. However, why such biases develop is not known. Using a computational framework, we investigated whether affective biases may reflect individuals' estimates of the information content of negative relative to positive events. During a reinforcement learning task, the information content of positive and negative outcomes was manipulated independently by varying the volatility of their occurrence. Human participants altered the learning rates used for the outcomes selectively, preferentially learning from the most informative. This behaviour was associated with activity of the central norepinephrine system, estimated using pupilometry, for loss outcomes. Humans maintain independent estimates of the information content of distinct positive and negative outcomes which may bias their processing of affective events. Normalising affective biases using computationally inspired interventions may represent a novel approach to treatment development.

  15. A theoretical model for analysing gender bias in medicine.

    Science.gov (United States)

    Risberg, Gunilla; Johansson, Eva E; Hamberg, Katarina

    2009-08-03

    During the last decades research has reported unmotivated differences in the treatment of women and men in various areas of clinical and academic medicine. There is an ongoing discussion on how to avoid such gender bias. We developed a three-step-theoretical model to understand how gender bias in medicine can occur and be understood. In this paper we present the model and discuss its usefulness in the efforts to avoid gender bias. In the model gender bias is analysed in relation to assumptions concerning difference/sameness and equity/inequity between women and men. Our model illustrates that gender bias in medicine can arise from assuming sameness and/or equity between women and men when there are genuine differences to consider in biology and disease, as well as in life conditions and experiences. However, gender bias can also arise from assuming differences when there are none, when and if dichotomous stereotypes about women and men are understood as valid. This conceptual thinking can be useful for discussing and avoiding gender bias in clinical work, medical education, career opportunities and documents such as research programs and health care policies. Too meet the various forms of gender bias, different facts and measures are needed. Knowledge about biological differences between women and men will not reduce bias caused by gendered stereotypes or by unawareness of health problems and discrimination associated with gender inequity. Such bias reflects unawareness of gendered attitudes and will not change by facts only. We suggest consciousness-rising activities and continuous reflections on gender attitudes among students, teachers, researchers and decision-makers.

  16. Attentional bias for positive emotional stimuli: A meta-analytic investigation.

    Science.gov (United States)

    Pool, Eva; Brosch, Tobias; Delplanque, Sylvain; Sander, David

    2016-01-01

    Despite an initial focus on negative threatening stimuli, researchers have more recently expanded the investigation of attentional biases toward positive rewarding stimuli. The present meta-analysis systematically compared attentional bias for positive compared with neutral visual stimuli across 243 studies (N = 9,120 healthy participants) that used different types of attentional paradigms and positive stimuli. Factors were tested that, as postulated by several attentional models derived from theories of emotion, might modulate this bias. Overall, results showed a significant, albeit modest (Hedges' g = .258), attentional bias for positive as compared with neutral stimuli. Moderator analyses revealed that the magnitude of this attentional bias varied as a function of arousal and that this bias was significantly larger when the emotional stimulus was relevant to specific concerns (e.g., hunger) of the participants compared with other positive stimuli that were less relevant to the participants' concerns. Moreover, the moderator analyses showed that attentional bias for positive stimuli was larger in paradigms that measure early, rather than late, attentional processing, suggesting that attentional bias for positive stimuli occurs rapidly and involuntarily. Implications for theories of emotion and attention are discussed. (c) 2015 APA, all rights reserved).

  17. Recent advances in precipitation-bias correction and application

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Significant progresses have been made in recent years in precipitation data analyses at regional to global scales. This paper re-views and synthesizes recent advances in precipitation-bias corrections and applications in many countries and over the cold re-gions. The main objective of this review is to identify and examine gaps in regional and national precipitation-error analyses. This paper also discusses and recommends future research needs and directions. More effort and coordination are necessary in the determinations of precipitation biases on large regions across national borders. It is important to emphasize that bias cor-rections of precipitation measurements affect both water budget and energy balance calculations, particularly over the cold regions.

  18. Exchange bias mediated by interfacial nanoparticles (invited)

    Energy Technology Data Exchange (ETDEWEB)

    Berkowitz, A. E., E-mail: aberk@ucsd.edu [Department of Physics, University of California, San Diego, La Jolla, California 92093 (United States); Center for Magnetic Recording Research, University of California, California 92093 (United States); Sinha, S. K. [Department of Physics, University of California, San Diego, La Jolla, California 92093 (United States); Fullerton, E. E. [Center for Magnetic Recording Research, University of California, California 92093 (United States); Smith, D. J. [Department of Physics, Arizona State University, Tempe, Arizona 85287 (United States)

    2015-05-07

    The objective of this study on the iconic exchange-bias bilayer Permalloy/CoO has been to identify those elements of the interfacial microstructure and accompanying magnetic properties that are responsible for the exchange-bias and hysteretic properties of this bilayer. Both epitaxial and polycrystalline samples were examined. X-ray and neutron reflectometry established that there existed an interfacial region, of width ∼1 nm, whose magnetic properties differed from those of Py or CoO. A model was developed for the interfacial microstructure that predicts all the relevant properties of this system; namely; the temperature and Permalloy thickness dependence of the exchange-bias, H{sub EX}, and coercivity, H{sub C}; the much smaller measured values of H{sub EX} from what was nominally expected; the different behavior of H{sub EX} and H{sub C} in epitaxial and polycrystalline bilayers. A surprising result is that the exchange-bias does not involve direct exchange-coupling between Permalloy and CoO, but rather is mediated by CoFe{sub 2}O{sub 4} nanoparticles in the interfacial region.

  19. Caste-biased gene expression in a facultatively eusocial bee suggests a role for genetic accommodation in the evolution of eusociality.

    Science.gov (United States)

    Jones, Beryl M; Kingwell, Callum J; Wcislo, William T; Robinson, Gene E

    2017-01-11

    Developmental plasticity may accelerate the evolution of phenotypic novelty through genetic accommodation, but studies of genetic accommodation often lack knowledge of the ancestral state to place selected traits in an evolutionary context. A promising approach for assessing genetic accommodation involves using a comparative framework to ask whether ancestral plasticity is related to the evolution of a particular trait. Bees are an excellent group for such comparisons because caste-based societies (eusociality) have evolved multiple times independently and extant species exhibit different modes of eusociality. We measured brain and abdominal gene expression in a facultatively eusocial bee, Megalopta genalis, and assessed whether plasticity in this species is functionally linked to eusocial traits in other bee lineages. Caste-biased abdominal genes in M. genalis overlapped significantly with caste-biased genes in obligately eusocial bees. Moreover, caste-biased genes in M. genalis overlapped significantly with genes shown to be rapidly evolving in multiple studies of 10 bee species, particularly for genes in the glycolysis pathway and other genes involved in metabolism. These results provide support for the idea that eusociality can evolve via genetic accommodation, with plasticity in facultatively eusocial species like M. genalis providing a substrate for selection during the evolution of caste in obligately eusocial lineages. © 2017 The Author(s).

  20. Large biases in regression-based constituent flux estimates: causes and diagnostic tools

    Science.gov (United States)

    Hirsch, Robert M.

    2014-01-01

    It has been documented in the literature that, in some cases, widely used regression-based models can produce severely biased estimates of long-term mean river fluxes of various constituents. These models, estimated using sample values of concentration, discharge, and date, are used to compute estimated fluxes for a multiyear period at a daily time step. This study compares results of the LOADEST seven-parameter model, LOADEST five-parameter model, and the Weighted Regressions on Time, Discharge, and Season (WRTDS) model using subsampling of six very large datasets to better understand this bias problem. This analysis considers sample datasets for dissolved nitrate and total phosphorus. The results show that LOADEST-7 and LOADEST-5, although they often produce very nearly unbiased results, can produce highly biased results. This study identifies three conditions that can give rise to these severe biases: (1) lack of fit of the log of concentration vs. log discharge relationship, (2) substantial differences in the shape of this relationship across seasons, and (3) severely heteroscedastic residuals. The WRTDS model is more resistant to the bias problem than the LOADEST models but is not immune to them. Understanding the causes of the bias problem is crucial to selecting an appropriate method for flux computations. Diagnostic tools for identifying the potential for bias problems are introduced, and strategies for resolving bias problems are described.