Statistical framework for estimating GNSS bias
Vierinen, Juha; Rideout, William C; Erickson, Philip J; Norberg, Johannes
2015-01-01
We present a statistical framework for estimating global navigation satellite system (GNSS) non-ionospheric differential time delay bias. The biases are estimated by examining differences of measured line integrated electron densities (TEC) that are scaled to equivalent vertical integrated densities. The spatio-temporal variability, instrumentation dependent errors, and errors due to inaccurate ionospheric altitude profile assumptions are modeled as structure functions. These structure functions determine how the TEC differences are weighted in the linear least-squares minimization procedure, which is used to produce the bias estimates. A method for automatic detection and removal of outlier measurements that do not fit into a model of receiver bias is also described. The same statistical framework can be used for a single receiver station, but it also scales to a large global network of receivers. In addition to the Global Positioning System (GPS), the method is also applicable to other dual frequency GNSS s...
Quantum Statistical Calculation of Exchange Bias
Institute of Scientific and Technical Information of China (English)
WANG Huai-Yu; DAI Zhen-Hong
2004-01-01
The phenomenon of exchange bias of ferromagnetic (FM) films, which are coupled with an antiferromagnetic (AFM) film, is studied by Heisenberg model by use of the many-body Green's function method of quantum statistical theory for the uncompensated case. Exchange bias HE and coercivity Hc are calculated as functions of the FM film thickness L, temperature, the strength of the exchange interaction across the interface between FM and AFM and the anisotropy of the FM. Hc decreases with increasing L when the FM film is beyond some thickness. The dependence of the exchange bias HE on the FM film thickness and on temperature is also qualitatively in agreement with experiments.
Magnification Bias in Gravitational Arc Statistics
Energy Technology Data Exchange (ETDEWEB)
Caminha, G. B. [Rio de Janeiro, CBPF; Estrada, J. [Fermilab; Makler, M. [Rio de Janeiro, CBPF
2013-08-29
The statistics of gravitational arcs in galaxy clusters is a powerful probe of cluster structure and may provide complementary cosmological constraints. Despite recent progresses, discrepancies still remain among modelling and observations of arc abundance, specially regarding the redshift distribution of strong lensing clusters. Besides, fast "semi-analytic" methods still have to incorporate the success obtained with simulations. In this paper we discuss the contribution of the magnification in gravitational arc statistics. Although lensing conserves surface brightness, the magnification increases the signal-to-noise ratio of the arcs, enhancing their detectability. We present an approach to include this and other observational effects in semi-analytic calculations for arc statistics. The cross section for arc formation ({\\sigma}) is computed through a semi-analytic method based on the ratio of the eigenvalues of the magnification tensor. Using this approach we obtained the scaling of {\\sigma} with respect to the magnification, and other parameters, allowing for a fast computation of the cross section. We apply this method to evaluate the expected number of arcs per cluster using an elliptical Navarro--Frenk--White matter distribution. Our results show that the magnification has a strong effect on the arc abundance, enhancing the fraction of arcs, moving the peak of the arc fraction to higher redshifts, and softening its decrease at high redshifts. We argue that the effect of magnification should be included in arc statistics modelling and that it could help to reconcile arcs statistics predictions with the observational data.
Inferring Master Painters' Esthetic Biases from the Statistics of Portraits
Aleem, Hassan; Correa-Herran, Ivan; Grzywacz, Norberto M.
2017-01-01
The Processing Fluency Theory posits that the ease of sensory information processing in the brain facilitates esthetic pleasure. Accordingly, the theory would predict that master painters should display biases toward visual properties such as symmetry, balance, and moderate complexity. Have these biases been occurring and if so, have painters been optimizing these properties (fluency variables)? Here, we address these questions with statistics of portrait paintings from the Early Renaissance period. To do this, we first developed different computational measures for each of the aforementioned fluency variables. Then, we measured their statistics in 153 portraits from 26 master painters, in 27 photographs of people in three controlled poses, and in 38 quickly snapped photographs of individual persons. A statistical comparison between Early Renaissance portraits and quickly snapped photographs revealed that painters showed a bias toward balance, symmetry, and moderate complexity. However, a comparison between portraits and controlled-pose photographs showed that painters did not optimize each of these properties. Instead, different painters presented biases toward different, narrow ranges of fluency variables. Further analysis suggested that the painters' individuality stemmed in part from having to resolve the tension between complexity vs. symmetry and balance. We additionally found that constraints on the use of different painting materials by distinct painters modulated these fluency variables systematically. In conclusion, the Processing Fluency Theory of Esthetic Pleasure would need expansion if we were to apply it to the history of visual art since it cannot explain the lack of optimization of each fluency variables. To expand the theory, we propose the existence of a Neuroesthetic Space, which encompasses the possible values that each of the fluency variables can reach in any given art period. We discuss the neural mechanisms of this Space and propose that it
Konijn, Elly A.; van de Schoot, Rens; Winter, Sonja D.; Ferguson, Christopher J.
2015-01-01
The present paper argues that an important cause of publication bias resides in traditional frequentist statistics forcing binary decisions. An alternative approach through Bayesian statistics provides various degrees of support for any hypothesis allowing balanced decisions and proper null hypothes
Improving uncertainty estimation in urban hydrological modeling by statistically describing bias
Directory of Open Access Journals (Sweden)
D. Del Giudice
2013-10-01
Full Text Available Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible and relatively efficient methodology (i to obtain more reliable hydrological simulations in terms of coverage of validation data by the uncertainty bands and (ii to separate prediction uncertainty into its components. Our approach acknowledges that urban drainage predictions are biased. This is mostly due to input errors and structural deficits of the model. We address this issue by describing model bias in a Bayesian framework. The bias becomes an autoregressive term additional to white measurement noise, the only error type accounted for in traditional uncertainty analysis. To allow for bigger discrepancies during wet weather, we make the variance of bias dependent on the input (rainfall or/and output (runoff of the system. Specifically, we present a structured approach to select, among five variants, the optimal bias description for a given urban or natural case study. We tested the methodology in a small monitored stormwater system described with a parsimonious model. Our results clearly show that flow simulations are much more reliable when bias is accounted for than when it is neglected. Furthermore, our probabilistic predictions can discriminate between three uncertainty contributions: parametric uncertainty, bias, and measurement errors. In our case study, the best performing bias description is the output-dependent bias using a log-sinh transformation of data and model results. The limitations of the framework presented are some ambiguity due to the subjective choice of priors for bias parameters and its inability to address the causes of model discrepancies. Further research should focus on
Improving uncertainty estimation in urban hydrological modeling by statistically describing bias
Directory of Open Access Journals (Sweden)
D. Del Giudice
2013-04-01
Full Text Available Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible and computationally efficient methodology (i to obtain more reliable hydrological simulations in terms of coverage of validation data by the uncertainty bands and (ii to separate prediction uncertainty into its components. Our approach acknowledges that urban drainage predictions are biased. This is mostly due to input errors and structural deficits of the model. We address this issue by describing model bias in a Bayesian framework. The bias becomes an autoregressive term additional to white measurement noise, the only error type accounted for in traditional uncertainty analysis in urban hydrology. To allow for bigger discrepancies during wet weather, we make the variance of bias dependent on the input (rainfall or/and output (runoff of the system. Specifically, we present a structured approach to select, among five variants, the optimal bias description for a given urban or natural case study. We tested the methodology in a small monitored stormwater system described by means of a parsimonious model. Our results clearly show that flow simulations are much more reliable when bias is accounted for than when it is neglected. Furthermore, our probabilistic predictions can discriminate between three uncertainty contributions: parametric uncertainty, bias (due to input and structural errors, and measurement errors. In our case study, the best performing bias description was the output-dependent bias using a log-sinh transformation of data and model results. The limitations of the framework presented are some ambiguity due to the subjective choice of priors for bias parameters and its inability to directly
Statistical Characterization and Mitigation of NLOS Bias in UWB Localization Systems
Montorsi, Francesco; Vitetta, Giorgio M
2012-01-01
Propagation in non-line-of-sight (NLOS) conditions is one of the major impairments in ultrawideband (UWB) wireless localization systems based on time-of-arrival (TOA) measurements. In this paper the problem of the joint statistical characterization of the NLOS bias and of the most representative features of LOS/NLOS UWB waveforms is investigated. In addition, the performance of various maximum-likelihood (ML) estimators for joint localization and NLOS bias mitigation is assessed. Our numerical results evidence that the accuracy of all the considered estimators is appreciably influenced by the LOS/NLOS conditions of the propagation environment and that a statistical knowledge of multiple signal features can be exploited to mitigate the NLOS bias, reducing the overall localization error.
Beyond Kaiser bias: mildly non-linear two-point statistics of densities in distant spheres
Uhlemann, C; Kim, J; Pichon, C; Bernardeau, F; Pogosyan, D; Park, C; L'Huillier, B
2016-01-01
Simple parameter-free analytic bias functions for the two-point correlation of densities in spheres at large separation are presented. These bias functions generalize the so-called Kaiser bias to the mildly non-linear regime for arbitrary density contrasts. The derivation is carried out in the context of large deviation statistics while relying on the spherical collapse model. A logarithmic transformation provides a saddle approximation which is valid for the whole range of densities and shown to be accurate against the 30 Gpc cube state-of-the-art Horizon Run 4 simulation. Special configurations of two concentric spheres that allow to identify peaks are employed to obtain the conditional bias and a proxy to BBKS extrema correlation functions. These analytic bias functions should be used jointly with extended perturbation theory to predict two-point clustering statistics as they capture the non-linear regime of structure formation at the percent level down to scales of about 10 Mpc/h at redshift 0. Conversely...
Beyond Kaiser bias: mildly non-linear two-point statistics of densities in distant spheres
Uhlemann, C.; Codis, S.; Kim, J.; Pichon, C.; Bernardeau, F.; Pogosyan, D.; Park, C.; L'Huillier, B.
2017-04-01
We present simple parameter-free analytic bias functions for the two-point correlation of densities in spheres at large separation. These bias functions generalize the so-called Kaiser bias to the mildly non-linear regime for arbitrary density contrasts and grow as b(ρ) - b(1) ∝ (1 - ρ-13/21)ρ1 + n/3 with b(1) = -4/21 - n/3 for a power-law initial spectrum with index n. We carry out the derivation in the context of large-deviation statistics while relying on the spherical collapse model. We use a logarithmic transformation that provides a saddle-point approximation that is valid for the whole range of densities and show its accuracy against the 30 Gpc cube state-of-the-art Horizon Run 4 simulation. Special configurations of two concentric spheres that allow us to identify peaks are employed to obtain the conditional bias and a proxy for the BBKS extremum correlation functions. These analytic bias functions should be used jointly with extended perturbation theory to predict two-point clustering statistics as they capture the non-linear regime of structure formation at the per cent level down to scales of about 10 Mpc h-1 at redshift 0. Conversely, the joint statistics also provide us with optimal dark matter two-point correlation estimates that can be applied either universally to all spheres or to a restricted set of biased (over- or underdense) pairs. Based on a simple fiducial survey, we show that the variance of this estimator is reduced by five times relative to the traditional sample estimator for the two-point function. Extracting more information from correlations of different types of objects should prove essential in the context of upcoming surveys like Euclid, DESI and WFIRST.
Bias Expansion of Spatial Statistics and Approximation of Differenced Lattice Point Counts
Indian Academy of Sciences (India)
Daniel J Nordman; Soumendra N Lahiri
2011-05-01
Investigations of spatial statistics, computed from lattice data in the plane, can lead to a special lattice point counting problem. The statistical goal is to expand the asymptotic expectation or large-sample bias of certain spatial covariance estimators, where this bias typically depends on the shape of a spatial sampling region. In particular, such bias expansions often require approximating a difference between two lattice point counts, where the counts correspond to a set of increasing domain (i.e., the sampling region) and an intersection of this set with a vector translate of itself. Non-trivially, the approximation error needs to be of smaller order than the spatial region’s perimeter length. For all convex regions in 2-dimensional Euclidean space and certain unions of convex sets, we show that a difference in areas can approximate a difference in lattice point counts to this required accuracy, even though area can poorly measure the lattice point count of any single set involved in the difference. When investigating large-sample properties of spatial estimators, this approximation result facilitates direct calculation of limiting bias, because, unlike counts, differences in areas are often tractable to compute even with non-rectangular regions. We illustrate the counting approximations with two statistical examples.
Ray, Robert L
2016-01-01
Two-particle correlation measurements and analysis are an important component of the relativistic heavy-ion physics program. In particular, particle pair-number correlations on two-dimensional transverse momentum ($p_t$) allow unique access to soft, semi-hard and hard-scattering processes in these collisions. Precise measurements of this type of correlation are essential for understanding the dynamics in heavy-ion collisions. However, transverse momentum correlation measurements are especially vulnerable to statistical and systematic biases. In this paper the origins of these large bias effects are explained and mathematical correlation forms are derived from mean-$p_t$ fluctuation quantities in the literature in an effort to minimize bias. Monte Carlo simulations are then used to test the degree to which each correlation definition leads to unbiased results in realistic applications. Several correlation forms are shown to be unacceptable for data analysis applications while several others are shown to reprod...
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.
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.
Ringard, Justine; Becker, Melanie; Seyler, Frederique; Linguet, Laurent
2016-04-01
Currently satellite-based precipitation estimates exhibit considerable biases, and there have been many efforts to reduce these biases by merging surface gauge measurements with satellite-based estimates. In Guiana Shield all products exhibited better performances during the dry season (August- December). All products greatly overestimate very low intensities (50 mm). Moreover the responses of each product are different according to hydro climatic regimes. The aim of this study is to correct spatially the bias of precipitation, and compare various correction methods to define the best methods depending on the rainfall characteristic correcting (intensity, frequency). Four satellites products are used: Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product (3B42V7) and real time product (3B42RT), the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network (PERSIANN) and the NOAA Climate Prediction Center (CPC) Morphing technique (CMORPH), for six hydro climatic regimes between 2001 and 2012. Several statistical transformations are used to correct the bias. Statistical transformations attempt to find a function h that maps a simulated variable Ps such that its new distribution equals the distribution of the observed variable Po. The first is the use of a distribution derived transformations which is a mixture of the Bernoulli and the Gamma distribution, where the Bernoulli distribution is used to model the probability of precipitation occurrence and the Gamma distribution used to model precipitation intensities. The second a quantile-quantile relation using parametric transformation, and the last one is a common approach using the empirical CDF of observed and modelled values instead of assuming parametric distributions. For each correction 30% of both, simulated and observed data sets, are used to calibrate and the other part used to validate. The validation are test with statistical
Statistical Bias Correction scheme for climate change impact assessment at a basin scale
Nyunt, C. T.
2013-12-01
Global climate models (GCMs) are the primary tool for understanding how the global climate may change in the future. GCM precipitation is characterized by underestimation of heavy precipitation, frequency errors by low intensity with long drizzle rain days and fail to catch the inter-seasonal change compared to the ground data. This study focus on the basin scale climate change impact study and we proposed the method for the multi model (GCMs) selection method together with the statistical bias correction method which cover the major deficiencies of GCM biases for climate change impact study at the basin level. The proposed method had been tested its applicability in the various river basin under different climate such as semiarid region in Tunisia, tropical monsoonal climate in Philippines and temperate humid region in Japan. It performed well enough for the climate change impact study in the basin scale and it can catch the point scale and basin scale climatology precipitation very well during the historical simulation. We found the GCM simulation during baiu season dissipate the baiu activity more earlier than the actual one when compared to the in-situ station data in Japan. For that case, the proposed bias correction performed in each season to reduce the bias of GCM for the impact study. The proposed bias correction method is still tested in different river basin in the world to check it applicability and now under developing as the web interface as the handy and efficient tool for the end users from the different parts of the world.
Bliefernicht, Jan; Laux, Patrick; Siegmund, Jonatan; Kunstmann, Harald
2013-04-01
The development and application of statistical techniques with a special focus on a recalibration of meteorological or hydrological forecasts to eliminate the bias between forecasts and observations has received a great deal of attention in recent years. One reason is that retrospective forecasts are nowadays available which allows for a proper training and validation of this kind of techniques. The objective of this presentation is to propose several statistical techniques with different degree of complexity and to evaluate and compare their performance for a recalibration of seasonal ensemble forecasts of monthly precipitation. The techniques selected in this study range from straightforward normal score and quantile-quantile transformation, local scaling, to more sophisticated and novel statistical techniques such as Copula-based methodology recently proposed by Laux et al. (2011). The seasonal forecasts are derived from the Climate Forecast System Version 2. This version is the current coupled ocean-atmosphere general circulation model of the U.S. National Centers for Environmental Prediction used to provide forecasts up to nine months. The CFS precipitation forecasts are compared to monthly precipitation observations from the Global Precipitation Climatology Centre. The statistical techniques are tested for semi-arid regions in West Africa and the Indian subcontinent focusing on large-scale river basins such as the Ganges and the Volta basin. In both regions seasonal precipitation forecasts are a crucial source of information for the prediction of hydro-meteorological extremes, in particular for droughts. The evaluation is done using retrospective CFS ensemble forecast from 1982 to 2009. The training of the statistical techniques is done in a cross-validation mode. The outcome of this investigation illustrates large systematic differences between forecasts and observations, in particular for the Volta basin in West Africa. The selection of straightforward
Ray, R. L.; Bhattarai, P.
2016-12-01
Two-particle correlation measurements and analysis are an important component of the relativistic heavy-ion physics program. In particular, particle pair-number correlations on two-dimensional transverse momentum (pt) allow unique access to soft, semihard, and hard scattering processes in these collisions. Precise measurements of this type of correlation are essential for understanding the dynamics in heavy-ion collisions. However, transverse momentum correlation measurements are especially vulnerable to statistical and systematic biases. In this paper the origins of these large bias effects are explained and mathematical correlation forms are derived from mean-pt fluctuation quantities in the literature. Monte Carlo simulations are then used to determine the conditions, e.g., multiplicity and collision centrality bin widths, where each correlation form is minimally biased. The ranges of applicability for each correlation quantity are compared. Several are found to reproduce the assumed input correlations with reasonable fidelity over a wide range of conditions encountered in practical analysis of data.
Duchesne, Thierry; Fortin, Daniel; Rivest, Louis-Paul
2015-01-01
Animal movement has a fundamental impact on population and community structure and dynamics. Biased correlated random walks (BCRW) and step selection functions (SSF) are commonly used to study movements. Because no studies have contrasted the parameters and the statistical properties of their estimators for models constructed under these two Lagrangian approaches, it remains unclear whether or not they allow for similar inference. First, we used the Weak Law of Large Numbers to demonstrate that the log-likelihood function for estimating the parameters of BCRW models can be approximated by the log-likelihood of SSFs. Second, we illustrated the link between the two approaches by fitting BCRW with maximum likelihood and with SSF to simulated movement data in virtual environments and to the trajectory of bison (Bison bison L.) trails in natural landscapes. Using simulated and empirical data, we found that the parameters of a BCRW estimated directly from maximum likelihood and by fitting an SSF were remarkably similar. Movement analysis is increasingly used as a tool for understanding the influence of landscape properties on animal distribution. In the rapidly developing field of movement ecology, management and conservation biologists must decide which method they should implement to accurately assess the determinants of animal movement. We showed that BCRW and SSF can provide similar insights into the environmental features influencing animal movements. Both techniques have advantages. BCRW has already been extended to allow for multi-state modeling. Unlike BCRW, however, SSF can be estimated using most statistical packages, it can simultaneously evaluate habitat selection and movement biases, and can easily integrate a large number of movement taxes at multiple scales. SSF thus offers a simple, yet effective, statistical technique to identify movement taxis.
Greenberg, Ariela Caren
Differential item functioning (DIF) and differential distractor functioning (DDF) are methods used to screen for item bias (Camilli & Shepard, 1994; Penfield, 2008). Using an applied empirical example, this mixed-methods study examined the congruency and relationship of DIF and DDF methods in screening multiple-choice items. Data for Study I were drawn from item responses of 271 female and 236 male low-income children on a preschool science assessment. Item analyses employed a common statistical approach of the Mantel-Haenszel log-odds ratio (MH-LOR) to detect DIF in dichotomously scored items (Holland & Thayer, 1988), and extended the approach to identify DDF (Penfield, 2008). Findings demonstrated that the using MH-LOR to detect DIF and DDF supported the theoretical relationship that the magnitude and form of DIF and are dependent on the DDF effects, and demonstrated the advantages of studying DIF and DDF in multiple-choice items. A total of 4 items with DIF and DDF and 5 items with only DDF were detected. Study II incorporated an item content review, an important but often overlooked and under-published step of DIF and DDF studies (Camilli & Shepard). Interviews with 25 female and 22 male low-income preschool children and an expert review helped to interpret the DIF and DDF results and their comparison, and determined that a content review process of studied items can reveal reasons for potential item bias that are often congruent with the statistical results. Patterns emerged and are discussed in detail. The quantitative and qualitative analyses were conducted in an applied framework of examining the validity of the preschool science assessment scores for evaluating science programs serving low-income children, however, the techniques can be generalized for use with measures across various disciplines of research.
Effects of drain bias on the statistical variation of double-gate tunnel field-effect transistors
Choi, Woo Young
2017-04-01
The effects of drain bias on the statistical variation of double-gate (DG) tunnel field-effect transistors (TFETs) are discussed in comparison with DG metal–oxide–semiconductor FETs (MOSFETs). Statistical variation corresponds to the variation of threshold voltage (V th), subthreshold swing (SS), and drain-induced barrier thinning (DIBT). The unique statistical variation characteristics of DG TFETs and DG MOSFETs with the variation of drain bias are analyzed by using full three-dimensional technology computer-aided design (TCAD) simulation in terms of the three dominant variation sources: line-edge roughness (LER), random dopant fluctuation (RDF) and workfunction variation (WFV). It is observed than DG TFETs suffer from less severe statistical variation as drain voltage increases unlike DG MOSFETs.
A statistical characterization of the Galileo-to-GPS inter-system bias
Gioia, Ciro; Borio, Daniele
2016-11-01
Global navigation satellite system operates using independent time scales and thus inter-system time offsets have to be determined to enable multi-constellation navigation solutions. GPS/Galileo inter-system bias and drift are evaluated here using different types of receivers: two mass market and two professional receivers. Moreover, three different approaches are considered for the inter-system bias determination: in the first one, the broadcast Galileo to GPS time offset is used to align GPS and Galileo time scales. In the second, the inter-system bias is included in the multi-constellation navigation solution and is estimated using the measurements available. Finally, an enhanced algorithm using constraints on the inter-system bias time evolution is proposed. The inter-system bias estimates obtained with the different approaches are analysed and their stability is experimentally evaluated using the Allan deviation. The impact of the inter-system bias on the position velocity time solution is also considered and the performance of the approaches analysed is evaluated in terms of standard deviation and mean errors for both horizontal and vertical components. From the experiments, it emerges that the inter-system bias is very stable and that the use of constraints, modelling the GPS/Galileo inter-system bias behaviour, significantly improves the performance of multi-constellation navigation.
Modular reweighting software for statistical mechanical analysis of biased equilibrium data
Sindhikara, Daniel J.
2012-07-01
Here a simple, useful, modular approach and software suite designed for statistical reweighting and analysis of equilibrium ensembles is presented. Statistical reweighting is useful and sometimes necessary for analysis of equilibrium enhanced sampling methods, such as umbrella sampling or replica exchange, and also in experimental cases where biasing factors are explicitly known. Essentially, statistical reweighting allows extrapolation of data from one or more equilibrium ensembles to another. Here, the fundamental separable steps of statistical reweighting are broken up into modules - allowing for application to the general case and avoiding the black-box nature of some “all-inclusive” reweighting programs. Additionally, the programs included are, by-design, written with little dependencies. The compilers required are either pre-installed on most systems, or freely available for download with minimal trouble. Examples of the use of this suite applied to umbrella sampling and replica exchange molecular dynamics simulations will be shown along with advice on how to apply it in the general case. New version program summaryProgram title: Modular reweighting version 2 Catalogue identifier: AEJH_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJH_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 179 118 No. of bytes in distributed program, including test data, etc.: 8 518 178 Distribution format: tar.gz Programming language: C++, Python 2.6+, Perl 5+ Computer: Any Operating system: Any RAM: 50-500 MB Supplementary material: An updated version of the original manuscript (Comput. Phys. Commun. 182 (2011) 2227) is available Classification: 4.13 Catalogue identifier of previous version: AEJH_v1_0 Journal reference of previous version: Comput. Phys. Commun. 182 (2011) 2227 Does the new
Directory of Open Access Journals (Sweden)
R. Rojas
2011-04-01
Full Text Available In this work we asses the benefits of removing bias in climate forcing data used for hydrological climate change impact assessment at pan-European scale, with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 model driven by the SRES-A1B emission scenario are corrected for bias using a histogram equalization method. As predictand for the bias correction we employ gridded interpolated observations of precipitation, average, minimum, and maximum temperature from the E-OBS data set. Bias removal transfer functions are derived for the control period 1961–1990. These are subsequently used to correct the climate simulations for the control period, and, under the assumption of a stationary error model, for the future time window 2071–2100. Validation against E-OBS climatology in the control period shows that the correction method performs successfully in removing bias in average and extreme statistics relevant for flood simulation over the majority of the European domain in all seasons. This translates into considerably improved simulations with the hydrological model of observed average and extreme river discharges at a majority of 554 validation river stations across Europe. Probabilities of extreme events derived employing extreme value techniques are also more closely reproduced. Results indicate that projections of future flood hazard in Europe based on uncorrected climate simulations, both in terms of their magnitude and recurrence interval, are likely subject to large errors. Notwithstanding the inherent limitations of the large-scale approach used herein, this study strongly advocates the removal of bias in climate simulations prior to their use in hydrological impact assessment.
Directory of Open Access Journals (Sweden)
R. Rojas
2011-08-01
Full Text Available In this work we asses the benefits of removing bias in climate forcing data used for hydrological climate change impact assessment at pan-European scale, with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 model driven by the SRES-A1B emission scenario are corrected for bias using a histogram equalization method. As target for the bias correction we employ gridded interpolated observations of precipitation, average, minimum, and maximum temperature from the E-OBS data set. Bias removal transfer functions are derived for the control period 1961–1990. These are subsequently used to correct the climate simulations for the control period, and, under the assumption of a stationary error model, for the future time window 2071–2100. Validation against E-OBS climatology in the control period shows that the correction method performs successfully in removing bias in average and extreme statistics relevant for flood simulation over the majority of the European domain in all seasons. This translates into considerably improved simulations with the hydrological model of observed average and extreme river discharges at a majority of 554 validation river stations across Europe. Probabilities of extreme events derived employing extreme value techniques are also more closely reproduced. Results indicate that projections of future flood hazard in Europe based on uncorrected climate simulations, both in terms of their magnitude and recurrence interval, are likely subject to large errors. Notwithstanding the inherent limitations of the large-scale approach used herein, this study strongly advocates the removal of bias in climate simulations prior to their use in hydrological impact assessment.
A combined statistical bias correction and stochastic downscaling method for precipitation
Volosciuk, Claudia; Maraun, Douglas; Vrac, Mathieu; Widmann, Martin
2017-03-01
Much of our knowledge about future changes in precipitation relies on global (GCMs) and/or regional climate models (RCMs) that have resolutions which are much coarser than typical spatial scales of precipitation, particularly extremes. The major problems with these projections are both climate model biases and the gap between gridbox and point scale. Wong et al. (2014) developed a model to jointly bias correct and downscale precipitation at daily scales. This approach, however, relied on pairwise correspondence between predictor and predictand for calibration, and, thus, on nudged simulations which are rarely available. Here we present an extension of this approach that separates the downscaling from the bias correction and in principle is applicable to free-running GCMs/RCMs. In a first step, we bias correct RCM-simulated precipitation against gridded observations at the same scale using a parametric quantile mapping (QMgrid) approach. In a second step, we bridge the scale gap: we predict local variance employing a regression-based model with coarse-scale precipitation as a predictor. The regression model is calibrated between gridded and point-scale (station) observations. For this concept we present one specific implementation, although the optimal model may differ for each studied location. To correct the whole distribution including extreme tails we apply a mixture distribution of a gamma distribution for the precipitation mass and a generalized Pareto distribution for the extreme tail in the first step. For the second step a vector generalized linear gamma model is employed. For evaluation we adopt the perfect predictor experimental setup of VALUE. We also compare our method to the classical QM as it is usually applied, i.e., between RCM and point scale (QMpoint). Precipitation is in most cases improved by (parts of) our method across different European climates. The method generally performs better in summer than in winter and in winter best in the
How cognitive biases can distort environmental statistics: introducing the rough estimation task.
Wilcockson, Thomas D W; Pothos, Emmanuel M
2016-04-01
The purpose of this study was to develop a novel behavioural method to explore cognitive biases. The task, called the Rough Estimation Task, simply involves presenting participants with a list of words that can be in one of three categories: appetitive words (e.g. alcohol, food, etc.), neutral related words (e.g. musical instruments) and neutral unrelated words. Participants read the words and are then asked to state estimates for the percentage of words in each category. Individual differences in the propensity to overestimate the proportion of appetitive stimuli (alcohol-related or food-related words) in a word list were associated with behavioural measures (i.e. alcohol consumption, hazardous drinking, BMI, external eating and restrained eating, respectively), thereby providing evidence for the validity of the task. The task was also found to be associated with an eye-tracking attentional bias measure. The Rough Estimation Task is motivated in relation to intuitions with regard to both the behaviour of interest and the theory of cognitive biases in substance use.
Vickers Andrew J; Cronin Angel M
2008-01-01
Abstract Background A common feature of diagnostic research is that results for a diagnostic gold standard are available primarily for patients who are positive for the test under investigation. Data from such studies are subject to what has been termed "verification bias". We evaluated statistical methods for verification bias correction when there are few false negatives. Methods A simulation study was conducted of a screening study subject to verification bias. We compared estimates of the...
Not a Copernican observer: biased peculiar velocity statistics in the local Universe
Hellwing, Wojciech A; Feix, Martin; Bilicki, Maciej
2016-01-01
We assess the effect of the local large scale structure on the estimation of two-point statistics of the observed radial peculiar velocities of galaxies. A large N-body simulation is used to examine these statistics from the perspective of random observers as well as "Local Group (LG)-like" observers conditioned to reside in an environment resembling the observed universe within 20 Mpc. The local environment systematically distorts the shape and amplitude of velocity statistics with respect to ensemble-averaged measurements made by a Copernican (random) observer. The Virgo cluster has the most significant impact, introducing large systematic deviations in all the statistics. For a simple "top-hat" selection function, an idealized survey extending to $\\sim 160h^{-1}\\,{\\rm Mpc}$ or deeper is needed to completely mitigate the effects of the local environment. Using shallower catalogues leads to systematic deviations of the order of $50$ to $200\\%$ depending on the scale considered. For a flat redshift distributi...
Not a Copernican observer: biased peculiar velocity statistics in the local Universe
Hellwing, Wojciech A.; Nusser, Adi; Feix, Martin; Bilicki, Maciej
2017-01-01
We assess the effect of the local large scale structure on the estimation of two-point statistics of the observed radial peculiar velocities of galaxies. A large N-body simulation is used to examine these statistics from the perspective of random observers as well as "Local Group (LG)-like" observers conditioned to reside in an environment resembling the observed universe within 20 Mpc. The local environment systematically distorts the shape and amplitude of velocity statistics with respect to ensemble-averaged measurements made by a Copernican (random) observer. The Virgo cluster has the most significant impact, introducing large systematic deviations in all the statistics. For a simple "top-hat" selection function, an idealized survey extending to ˜160h-1 Mpc or deeper is needed to completely mitigate the effects of the local environment. Using shallower catalogues leads to systematic deviations of the order of 50 to 200% depending on the scale considered. For a flat redshift distribution similar to the one of the CosmicFlows-3 survey, the deviations are even more prominent in both the shape and amplitude at all separations considered (≲100h^{-1} Mpc). Conclusions based on statistics calculated without taking into account the impact of the local environment should be revisited.
Dagnall, Neil; Denovan, Andrew; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter
2016-01-01
The present paper examined relationships between schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experience; O-LIFE scale brief), belief in the paranormal (assessed via the Revised Paranormal Belief Scale; RPBS) and proneness to statistical bias (i.e., perception of randomness and susceptibility to conjunction fallacy). Participants were 254 volunteers recruited via convenience sampling. Probabilistic reasoning problems appeared framed within both standard and paranormal contexts. Analysis revealed positive correlations between the Unusual Experience (UnExp) subscale of O-LIFE and paranormal belief measures [RPBS full scale, traditional paranormal beliefs (TPB) and new age philosophy]. Performance on standard problems correlated negatively with UnExp and belief in the paranormal (particularly the TPB dimension of the RPBS). Consideration of specific problem types revealed that perception of randomness associated more strongly with belief in the paranormal than conjunction; both problem types related similarly to UnExp. Structural equation modeling specified that belief in the paranormal mediated the indirect relationship between UnExp and statistical bias. For problems presented in a paranormal context a framing effect occurred. Whilst UnExp correlated positively with conjunction proneness (controlling for perception of randomness), there was no association between UnExp and perception of randomness (controlling for conjunction).
Directory of Open Access Journals (Sweden)
Neil Dagnall
2016-07-01
Full Text Available The present paper examined relationships between schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experience; O-LIFE scale brief, belief in the paranormal (assessed via the Revised Paranormal Belief Scale; RPBS and proneness to statistical bias (i.e., perception of randomness and susceptibility to conjunction fallacy. Participants were 254 volunteers recruited via convenience sampling. Probabilistic reasoning problems appeared framed within both standard and paranormal contexts. Analysis revealed positive correlations between the Unusual Experience subscale of O-LIFE and paranormal belief measures (RPBS full scale, traditional paranormal beliefs and new age philosophy. Performance on standard problems correlated negatively with Unusual Experience and belief in the paranormal (particularly the traditional paranormal belief dimension of the RPBS. Consideration of specific problem types revealed that perception of randomness associated more strongly with belief in the paranormal than conjunction; both problem types related similarly to Unusual Experience. Structural equation modelling specified that belief in the paranormal mediated the indirect relationship between Unusual Experience and statistical bias. For problems presented in a paranormal context a framing effect occurred. Whilst Unusual Experience correlated positively with conjunction proneness (controlling for perception of randomness, there was no association between Unusual Experience and perception of randomness (controlling for conjunction.
Statistical inference for nanopore sequencing with a biased random walk model.
Emmett, Kevin J; Rosenstein, Jacob K; van de Meent, Jan-Willem; Shepard, Ken L; Wiggins, Chris H
2015-04-21
Nanopore sequencing promises long read-lengths and single-molecule resolution, but the stochastic motion of the DNA molecule inside the pore is, as of this writing, a barrier to high accuracy reads. We develop a method of statistical inference that explicitly accounts for this error, and demonstrate that high accuracy (>99%) sequence inference is feasible even under highly diffusive motion by using a hidden Markov model to jointly analyze multiple stochastic reads. Using this model, we place bounds on achievable inference accuracy under a range of experimental parameters.
Kuusela, Mikael
2015-01-01
We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse problem arising in data analysis at the Large Hadron Collider at CERN consists in estimating the intensity function of an indirectly observed Poisson point process. Unfolding typically proceeds in two steps: one first produces a regularized point estimate of the unknown intensity and then uses the variability of this estimator to form frequentist confidence intervals that quantify the uncertainty of the solution. In this paper, we propose forming the point estimate using empirical Bayes estimation which enables a data-driven choice of the regularization strength through marginal maximum likelihood estimation. Observing that neither Bayesian credible intervals nor standard bootstrap confidence intervals succeed in achieving good frequentist coverage in this problem due to the inh...
Directory of Open Access Journals (Sweden)
Vickers Andrew J
2008-11-01
Full Text Available Abstract Background A common feature of diagnostic research is that results for a diagnostic gold standard are available primarily for patients who are positive for the test under investigation. Data from such studies are subject to what has been termed "verification bias". We evaluated statistical methods for verification bias correction when there are few false negatives. Methods A simulation study was conducted of a screening study subject to verification bias. We compared estimates of the area-under-the-curve (AUC corrected for verification bias varying both the rate and mechanism of verification. Results In a single simulated data set, varying false negatives from 0 to 4 led to verification bias corrected AUCs ranging from 0.550 to 0.852. Excess variation associated with low numbers of false negatives was confirmed in simulation studies and by analyses of published studies that incorporated verification bias correction. The 2.5th – 97.5th centile range constituted as much as 60% of the possible range of AUCs for some simulations. Conclusion Screening programs are designed such that there are few false negatives. Standard statistical methods for verification bias correction are inadequate in this circumstance.
Li, R.; Wang, S.-Y.; Gillies, R. R.
2016-04-01
Large biases associated with climate projections are problematic when it comes to their regional application in the assessment of water resources and ecosystems. Here, we demonstrate a method that can reduce systematic biases in regional climate projections. The global and regional climate models employed to demonstrate the technique are the Community Climate System Model (CCSM) and the Weather Research and Forecasting (WRF) model. The method first utilized a statistical regression technique and a global reanalysis dataset to correct biases in the CCSM-simulated variables (e.g., temperature, geopotential height, specific humidity, and winds) that are subsequently used to drive the WRF model. The WRF simulations were conducted for the western United States and were driven with (a) global reanalysis, (b) original CCSM, and (c) bias-corrected CCSM data. The bias-corrected CCSM data led to a more realistic regional climate simulation of precipitation and associated atmospheric dynamics, as well as snow water equivalent (SWE), in comparison to the original CCSM-driven WRF simulation. Since most climate applications rely on existing global model output as the forcing data (i.e., they cannot re-run or change the global model), which often contain large biases, this method provides an effective and economical tool to reduce biases in regional climate downscaling simulations of water resource variables.
DEFF Research Database (Denmark)
Thorson, James T.; Kristensen, Kasper
2016-01-01
configurations of an age-structured population dynamics model. This simulation experiment shows that the epsilon-method and the existing bias-correction method perform equally well in data-rich contexts, but the epsilon-method is slightly less biased in data-poor contexts. We then apply the epsilon....... Quantities of biological or management interest ("derived quantities") are then often calculated as nonlinear functions of fixed and random effect estimates. However, the conventional "plug-in" estimator for a derived quantity in a maximum likelihood mixed-effects model will be biased whenever the estimator...... is calculated as a nonlinear function of random effects. We therefore describe and evaluate a new "epsilon" estimator as a generic bias-correction estimator for derived quantities. We use simulated data to compare the epsilon-method with an existing bias-correction algorithm for estimating recruitment in four...
Indian Academy of Sciences (India)
V R Durai; Rashmi Bhardwaj
2014-07-01
The output from Global Forecasting System (GFS) T574L64 operational at India Meteorological Department (IMD), New Delhi is used for obtaining location specific quantitative forecast of maximum and minimum temperatures over India in the medium range time scale. In this study, a statistical bias correction algorithm has been introduced to reduce the systematic bias in the 24–120 hour GFS model location specific forecast of maximum and minimum temperatures for 98 selected synoptic stations, representing different geographical regions of India. The statistical bias correction algorithm used for minimizing the bias of the next forecast is Decaying Weighted Mean (DWM), as it is suitable for small samples. The main objective of this study is to evaluate the skill of Direct Model Output (DMO) and Bias Corrected (BC) GFS for location specific forecast of maximum and minimum temperatures over India. The performance skill of 24–120 hour DMO and BC forecast of GFS model is evaluated for all the 98 synoptic stations during summer (May–August 2012) and winter (November 2012–February 2013) seasons using different statistical evaluation skill measures. The magnitude of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for BC GFS forecast is lower than DMO during both summer and winter seasons. The BC GFS forecasts have higher skill score as compared to GFS DMO over most of the stations in all day-1 to day-5 forecasts during both summer and winter seasons. It is concluded from the study that the skill of GFS statistical BC forecast improves over the GFS DMO remarkably and hence can be used as an operational weather forecasting system for location specific forecast over India.
Prasanna, V.
2016-11-01
This study makes use of temperature and precipitation from CMIP5 climate model output for climate change application studies over the Indian region during the summer monsoon season (JJAS). Bias correction of temperature and precipitation from CMIP5 GCM simulation results with respect to observation is discussed in detail. The non-linear statistical bias correction is a suitable bias correction method for climate change data because it is simple and does not add up artificial uncertainties to the impact assessment of climate change scenarios for climate change application studies (agricultural production changes) in the future. The simple statistical bias correction uses observational constraints on the GCM baseline, and the projected results are scaled with respect to the changing magnitude in future scenarios, varying from one model to the other. Two types of bias correction techniques are shown here: (1) a simple bias correction using a percentile-based quantile-mapping algorithm and (2) a simple but improved bias correction method, a cumulative distribution function (CDF; Weibull distribution function)-based quantile-mapping algorithm. This study shows that the percentile-based quantile mapping method gives results similar to the CDF (Weibull)-based quantile mapping method, and both the methods are comparable. The bias correction is applied on temperature and precipitation variables for present climate and future projected data to make use of it in a simple statistical model to understand the future changes in crop production over the Indian region during the summer monsoon season. In total, 12 CMIP5 models are used for Historical (1901-2005), RCP4.5 (2005-2100), and RCP8.5 (2005-2100) scenarios. The climate index from each CMIP5 model and the observed agricultural yield index over the Indian region are used in a regression model to project the changes in the agricultural yield over India from RCP4.5 and RCP8.5 scenarios. The results revealed a better
Baronchelli, Andrea; Loreto, Vittorio; Puglisi, Andrea
2015-01-01
Language universals have long been attributed to an innate Universal Grammar. An alternative explanation states that linguistic universals emerged independently in every language in response to shared cognitive or perceptual biases. A computational model has recently shown how this could be the case, focusing on the paradigmatic example of the universal properties of colour naming patterns, and producing results in quantitative agreement with the experimental data. Here we investigate the role of an individual perceptual bias in the framework of the model. We study how, and to what extent, the structure of the bias influences the corresponding linguistic universal patterns. We show that the cultural history of a group of speakers introduces population-specific constraints that act against the pressure for uniformity arising from the individual bias, and we clarify the interplay between these two forces.
Hayslett, H T
1991-01-01
Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the
Rosenbaum, Paul R
2016-03-01
A common practice with ordered doses of treatment and ordered responses, perhaps recorded in a contingency table with ordered rows and columns, is to cut or remove a cross from the table, leaving the outer corners--that is, the high-versus-low dose, high-versus-low response corners--and from these corners to compute a risk or odds ratio. This little remarked but common practice seems to be motivated by the oldest and most familiar method of sensitivity analysis in observational studies, proposed by Cornfield et al. (1959), which says that to explain a population risk ratio purely as bias from an unobserved binary covariate, the prevalence ratio of the covariate must exceed the risk ratio. Quite often, the largest risk ratio, hence the one least sensitive to bias by this standard, is derived from the corners of the ordered table with the central cross removed. Obviously, the corners use only a portion of the data, so a focus on the corners has consequences for the standard error as well as for bias, but sampling variability was not a consideration in this early and familiar form of sensitivity analysis, where point estimates replaced population parameters. Here, this cross-cut analysis is examined with the aid of design sensitivity and the power of a sensitivity analysis.
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
Valle, G.; Dell'Omodarme, M.; Prada Moroni, P. G.; Degl'Innocenti, S.
2017-03-01
larger than approximately 1% lead to estimates that are not only less precise but also biased. Moreover, we show that a fit obtained with a grid of models computed at a fixed ΔY/ ΔZ - thus neglecting the current uncertainty in the initial helium content of the system - can provide severely biased age and overshooting estimates. The possibility of independent overshooting efficiencies for the two stars of the system is also explored. Conclusions: The present analysis confirms that to constrain the core overshooting parameter by means of binary systems is a very difficult task that requires an observational precision still rarely achieved and a robust statistical treatment of the error sources.
Sendhil Mullainathan; Andrei Shleifer
2002-01-01
There are two different types of media bias. One bias, which we refer to as ideology, reflects a news outlet's desire to affect reader opinions in a particular direction. The second bias, which we refer to as spin, reflects the outlet's attempt to simply create a memorable story. We examine competition among media outlets in the presence of these biases. Whereas competition can eliminate the effect of ideological bias, it actually exaggerates the incentive to spin stories.
Distinguishing Selection Bias and Confounding Bias in Comparative Effectiveness Research.
Haneuse, Sebastien
2016-04-01
Comparative effectiveness research (CER) aims to provide patients and physicians with evidence-based guidance on treatment decisions. As researchers conduct CER they face myriad challenges. Although inadequate control of confounding is the most-often cited source of potential bias, selection bias that arises when patients are differentially excluded from analyses is a distinct phenomenon with distinct consequences: confounding bias compromises internal validity, whereas selection bias compromises external validity. Despite this distinction, however, the label "treatment-selection bias" is being used in the CER literature to denote the phenomenon of confounding bias. Motivated by an ongoing study of treatment choice for depression on weight change over time, this paper formally distinguishes selection and confounding bias in CER. By formally distinguishing selection and confounding bias, this paper clarifies important scientific, design, and analysis issues relevant to ensuring validity. First is that the 2 types of biases may arise simultaneously in any given study; even if confounding bias is completely controlled, a study may nevertheless suffer from selection bias so that the results are not generalizable to the patient population of interest. Second is that the statistical methods used to mitigate the 2 biases are themselves distinct; methods developed to control one type of bias should not be expected to address the other. Finally, the control of selection and confounding bias will often require distinct covariate information. Consequently, as researchers plan future studies of comparative effectiveness, care must be taken to ensure that all data elements relevant to both confounding and selection bias are collected.
Hewstone, Miles; Rubin, Mark; Willis, Hazel
2002-01-01
This chapter reviews the extensive literature on bias in favor of in-groups at the expense of out-groups. We focus on five issues and identify areas for future research: (a) measurement and conceptual issues (especially in-group favoritism vs. out-group derogation, and explicit vs. implicit measures of bias); (b) modern theories of bias highlighting motivational explanations (social identity, optimal distinctiveness, uncertainty reduction, social dominance, terror management); (c) key moderators of bias, especially those that exacerbate bias (identification, group size, status and power, threat, positive-negative asymmetry, personality and individual differences); (d) reduction of bias (individual vs. intergroup approaches, especially models of social categorization); and (e) the link between intergroup bias and more corrosive forms of social hostility.
D'Aloisio, Anson; Jeong, Donghui; Shapiro, Paul R
2012-01-01
Characterizing the level of primordial non-Gaussianity (PNG) in the initial conditions for structure formation is one of the most promising ways to test inflation and differentiate among different scenarios. The scale-dependent imprint of PNG on the large-scale clustering of galaxies and quasars has already been used to place significant constraints on the level of PNG in our observed Universe. Such measurements depend upon an accurate and robust theory for how PNG affects the bias of galactic halos relative to the underlying matter density field. We improve upon previous work by employing a more general analytical method - the path-integral extension of the excursion set formalism - which is able to account for the non-Markovianity caused by PNG in the random-walk model used to identify halos in the initial density field. This non-Markovianity encodes information about environmental effects on halo formation which have so far not been taken into account in analytical bias calculations. We compute both scale-...
The Probability Distribution for a Biased Spinner
Foster, Colin
2012-01-01
This article advocates biased spinners as an engaging context for statistics students. Calculating the probability of a biased spinner landing on a particular side makes valuable connections between probability and other areas of mathematics. (Contains 2 figures and 1 table.)
Theoretical investigation of exchange bias
Institute of Scientific and Technical Information of China (English)
Xiong Zhi-Jie; Wang Huai-Yu; Ding Ze-Jun
2007-01-01
The exchange bias of bilayer magnetic films consisting of ferromagnetic (FM) and antiferromagnetic (AFM) layers in an uncompensated case is studied by use of the many-body Green's function method of quantum statistical theory.The effects of the layer thickness and temperature and the interfacial coupling strength on the exchange bias HE are investigated. The dependence of the exchange bias HE on the FM layer thickness and temperature is qualitatively in agreement with experimental results. When temperature varies, both the coercivity HC and HE decrease with the temperature increasing. For each FM thickness, there exists a least AFM thickness in which the exchange bias occurs,which is called pinning thickness.
Desjacques, Vincent; Schmidt, Fabian
2016-01-01
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 pedagogical proof 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 includes 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 i...
Numeracy and framing bias in epilepsy.
Choi, Hyunmi; Wong, John B; Mendiratta, Anil; Heiman, Gary A; Hamberger, Marla J
2011-01-01
Patients with epilepsy are frequently confronted with complex treatment decisions. Communicating treatment risks is often difficult because patients may have difficulty with basic statistical concepts (i.e., low numeracy) or might misconceive the statistical information based on the way information is presented, a phenomenon known as "framing bias." We assessed numeracy and framing bias in 95 adults with chronic epilepsy and explored cognitive correlates of framing bias. Compared with normal controls, patients with epilepsy had significantly poorer performance on the Numeracy scale (P=0.02), despite a higher level of education than normal controls (Pframing bias. Abstract problem solving performance correlated with the degree of framing bias (r=0.631, Pframing bias. Poor numeracy and susceptibility framing bias place patients with epilepsy at risk for uninformed decisions.
Institute of Scientific and Technical Information of China (English)
汤洁; 巴金
2013-01-01
Precipitation pH and conductivity are measured routinely in the nation-wide network with more than 300 stations, known as the Acid Rain Monitoring Network (ARMN), under the infrastructure of China Meteorological Administration (CMA) since early 1990s. Previous studies indicate that a systematic negative bias in the pH measurement, caused by the aging of pH electrode, which has weakened the data quality obviously. Characteristics of the bias are investigated to describe the temporal and spatial features of the negative pH measurement bias (NBpH) and to estimate its magnitude with meticulous statistical approaches, based on the monitoring dataset obtained from CMA-ARMN during 1992—2011. The result indicates that 40% stations of CMA-ARMN suffers from NBpH problem in the early 1990s, while this ratio decreases to 25% during 2010—2011. The proportion of data infected with NBpH problem during 2010— 2011 reduces to 2% from 10% in the early 1990s. This improvement of pH measurement mentioned above can be attributed to the renewal of pH meter for all CMA-ARMN stations in 2000, the re-approval of Standard Operation Manual of CMA-ARMN in 2005, and the recent trail measures on the pH electrode aging. Also, statistics shows that NBpH problem seldom occurs in the stations over the Northwest China and Qinghai-Tibet Plateau, but frequently occurs in the stations of other regions over China. On the whole, NBpH problem in southern part of China is more serious than those in the northern part of China. This geographical feature of NBpH is related with the behavior of aged pH electrode which shows bigger negative bias when measuring the solution of low pH and low conductivity. Quasi-quantitative estimation of NBpH based on the K-pH inequality principle shows that the magnitude of NBpH for about 80% data ranges from —0. 6 to 0, with a few of extremes lower than —3. 0. The lower pH is, the larger NBpH tends to be. To avoid NBpH problem in future, substitution of the now
Venema, Victor; Lindau, Ralf
2016-04-01
In an accompanying talk we show that well-homogenized national dataset warm more than temperatures from global collections averaged over the region of common coverage. In this poster we want to present auxiliary work about possible biases in the raw observations and on how well relative statistical homogenization can remove trend biases. There are several possible causes of cooling biases, which have not been studied much. Siting could be an important factor. Urban stations tend to move away from the centre to better locations. Many stations started inside of urban areas and are nowadays more outside. Even for villages the temperature difference between the centre and edge can be 0.5°C. When a city station moves to an airport, which often happened around WWII, this takes the station (largely) out of the urban heat island. During the 20th century the Stevenson screen was established as the dominant thermometer screen. This screen protected the thermometer much better against radiation than earlier designs. Deficits of earlier measurement methods have artificially warmed the temperatures in the 19th century. Newer studies suggest we may have underestimated the size of this bias. Currently we are in a transition to Automatic Weather Stations. The net global effect of this transition is not clear at this moment. Irrigation on average decreases the 2m-temperature by about 1 degree centigrade. At the same time, irrigation has increased significantly during the last century. People preferentially live in irrigated areas and weather stations serve agriculture. Thus it is possible that there is a higher likelihood that weather stations are erected in irrigated areas than elsewhere. In this case irrigation could lead to a spurious cooling trend. In the Parallel Observations Science Team of the International Surface Temperature Initiative (ISTI-POST) we are studying influence of the introduction of Stevenson screens and Automatic Weather Stations using parallel measurements
Length-biased Weighted Maxwell Distribution
Directory of Open Access Journals (Sweden)
Kanak Modi
2015-12-01
Full Text Available The concept of length-biased distribution can be employed in development of proper models for life-time data. In this paper, we develop the length-biased form of Weighted Maxwell distribution (WMD. We study the statistical properties of the derived distribution including moments, moment generating function, hazard rate, reverse hazard rate, Shannon entropy and estimation of parameters
Climate model bias correction and the role of timescales
Directory of Open Access Journals (Sweden)
J. O. Haerter
2010-10-01
Full Text Available It is well known that output from climate models cannot be used to force hydrological simulations without some form of preprocessing to remove the existing biases. In principle, statistical bias correction methodologies act on model output so the statistical properties of the corrected data match those of the observations. However the improvements to the statistical properties of the data are limited to the specific time scale of the fluctuations that are considered. For example, a statistical bias correction methodology for mean daily values might be detrimental to monthly statistics. Also, in applying bias corrections derived from present day to scenario simulations, an assumption is made of persistence of the bias over the largest timescales. We examine the effects of mixing fluctuations on different time scales and suggest an improved statistical methodology, referred to here as a cascade bias correction method, that eliminates, or greatly reduces, the negative effects.
2014-01-01
Can raising awareness of racial bias subsequently reduce that bias? We address this question by exploiting the widespread media attention highlighting racial bias among professional basketball referees that occurred in May 2007 following the release of an academic study. Using new data, we confirm that racial bias persisted in the years after the study's original sample, but prior to the media coverage. Subsequent to the media coverage though, the bias completely disappeared. We examine poten...
Eulerian bias and the galaxy density field
Mann, B M; Heavens, A F; Mann, Bob; Peacock, John; Heavens, Alan
1997-01-01
We investigate the effects on cosmological clustering statistics of empirical biasing, where the galaxy distribution is a local transformation of the present-day Eulerian density field. The effects of the suppression of galaxy numbers in voids, and their enhancement in regions of high density, are considered, independently and in combination. We compare results from numerical simulations with the predictions of simple analytic models. We find that the bias is generally scale-dependent, so that the shape of the galaxy power spectrum differs from that of the underlying mass distribution. The degree of bias is always a monotonic function of scale, tending to an asymptotic value on scales where the density fluctuations are linear. The scale dependence is often rather weak, with many reasonable prescriptions giving a bias which is nearly independent of scale. We have investigated whether such an Eulerian bias can reconcile a range of theoretical power spectra with the twin requirements of fitting the galaxy power ...
Statistical electromagnetics: Complex cavities
Naus, H.W.L.
2008-01-01
A selection of the literature on the statistical description of electromagnetic fields and complex cavities is concisely reviewed. Some essential concepts, for example, the application of the central limit theorem and the maximum entropy principle, are scrutinized. Implicit assumptions, biased choic
Publication Bias The "File-Drawer Problem" in Scientific Inference
Scargle, J D
1999-01-01
Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always misestimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical c...
Simundić, Ana-Maria
2013-01-01
By writing scientific articles we communicate science among colleagues and peers. By doing this, it is our responsibility to adhere to some basic principles like transparency and accuracy. Authors, journal editors and reviewers need to be concerned about the quality of the work submitted for publication and ensure that only studies which have been designed, conducted and reported in a transparent way, honestly and without any deviation from the truth get to be published. Any such trend or deviation from the truth in data collection, analysis, interpretation and publication is called bias. Bias in research can occur either intentionally or unintentionally. Bias causes false conclusions and is potentially misleading. Therefore, it is immoral and unethical to conduct biased research. Every scientist should thus be aware of all potential sources of bias and undertake all possible actions to reduce or minimize the deviation from the truth. This article describes some basic issues related to bias in research.
Recursive bias estimation and L2 boosting
Energy Technology Data Exchange (ETDEWEB)
Hengartner, Nicolas W [Los Alamos National Laboratory; Cornillon, Pierre - Andre [INRA, FRANCE; Matzner - Lober, Eric [RENNE, FRANCE
2009-01-01
This paper presents a general iterative bias correction procedure for regression smoothers. This bias reduction schema is shown to correspond operationally to the L{sub 2} Boosting algorithm and provides a new statistical interpretation for L{sub 2} Boosting. We analyze the behavior of the Boosting algorithm applied to common smoothers S which we show depend on the spectrum of I - S. We present examples of common smoother for which Boosting generates a divergent sequence. The statistical interpretation suggest combining algorithm with an appropriate stopping rule for the iterative procedure. Finally we illustrate the practical finite sample performances of the iterative smoother via a simulation study.
Germano, Fabrizio
2008-01-01
Within the spokes model of Chen and Riordan (2007) that allows for non-localized competition among arbitrary numbers of media outlets, we quantify the effect of concentration of ownership on quality and bias of media content. A main result shows that too few commercial outlets, or better, too few separate owners of commercial outlets can lead to substantial bias in equilibrium. Increasing the number of outlets (commercial and non-commercial) tends to bring down this bias; but the strongest ef...
Interpretation biases in paranoia.
Savulich, George; Freeman, Daniel; Shergill, Sukhi; Yiend, Jenny
2015-01-01
Information in the environment is frequently ambiguous in meaning. Emotional ambiguity, such as the stare of a stranger, or the scream of a child, encompasses possible good or bad emotional consequences. Those with elevated vulnerability to affective disorders tend to interpret such material more negatively than those without, a phenomenon known as "negative interpretation bias." In this study we examined the relationship between vulnerability to psychosis, measured by trait paranoia, and interpretation bias. One set of material permitted broadly positive/negative (valenced) interpretations, while another allowed more or less paranoid interpretations, allowing us to also investigate the content specificity of interpretation biases associated with paranoia. Regression analyses (n=70) revealed that trait paranoia, trait anxiety, and cognitive inflexibility predicted paranoid interpretation bias, whereas trait anxiety and cognitive inflexibility predicted negative interpretation bias. In a group comparison those with high levels of trait paranoia were negatively biased in their interpretations of ambiguous information relative to those with low trait paranoia, and this effect was most pronounced for material directly related to paranoid concerns. Together these data suggest that a negative interpretation bias occurs in those with elevated vulnerability to paranoia, and that this bias may be strongest for material matching paranoid beliefs. We conclude that content-specific biases may be important in the cause and maintenance of paranoid symptoms.
Directory of Open Access Journals (Sweden)
Mahmoud Moradi
2013-04-01
Full Text Available Most economic and finance theories are based on the assumption that during economic decision making, people would act totally rational and consider all available information. Nevertheless, behavioral finance focuses on studying of the role of psychological factors on economic participants’ behavior. The study shows that in real-world environment, people are influenced by emotional and cognitive errors and may make irrational financial decisions. In many cases, the participants of financial markets are not aware of their talents for error in decision making, so they are dissatisfied with their investments by considering some behavioral biases decisions. These decisions may often yield undesirable outcomes, which could influence economy, significantly. This paper presents a survey on the relationship between personality dimensions with behavioral biases and availability bias among investment managers in the Tehran Stock Exchange using SPSS software, descriptive and inferential statistics. The necessary data are collected through questionnaire and they are analyzed using some statistical tests. The preliminary results indicate that there is a relationship between personality dimensions and behavioral biases like conservatism bias and availability bias among the investors in the Tehran Stock Exchange.
... Certification Import Safety International Recall Guidance Civil and Criminal Penalties Federal Court Orders & Decisions Research & Statistics Research & Statistics Technical Reports Injury Statistics NEISS Injury ...
Transformationally decoupling clustering and tracer bias
Neyrinck, Mark C
2014-01-01
Gaussianizing transformations are used statistically in many non-cosmological fields, but in cosmology, we are only starting to apply them. Here I explain a strategy of analyzing the 1-point function (PDF) of a spatial field, together with the 'essential' clustering statistics of the Gaussianized field, which are invariant to a local transformation. In cosmology, if the tracer sampling is sufficient, this achieves two important goals. First, it can greatly multiply the Fisher information, which is negligible on nonlinear scales in the usual $\\delta$ statistics. Second, it decouples clustering statistics from a local bias description for tracers such as galaxies.
Das-Smaal, E.A.
1990-01-01
On what grounds can we conclude that an act of categorization is biased? In this chapter, it is contended that in the absence of objective norms of what categories actually are, biases in categorization can only be specified in relation to theoretical understandings of categorization. Therefore, the
Ditto, Peter H; Wojcik, Sean P; Chen, Eric Evan; Grady, Rebecca Hofstein; Ringel, Megan M
2015-01-01
Duarte et al. are right to worry about political bias in social psychology but they underestimate the ease of correcting it. Both liberals and conservatives show partisan bias that often worsens with cognitive sophistication. More non-liberals in social psychology is unlikely to speed our convergence upon the truth, although it may broaden the questions we ask and the data we collect.
Cosmic Statistics of Statistics
Szapudi, I.; Colombi, S.; Bernardeau, F.
1999-01-01
The errors on statistics measured in finite galaxy catalogs are exhaustively investigated. The theory of errors on factorial moments by Szapudi & Colombi (1996) is applied to cumulants via a series expansion method. All results are subsequently extended to the weakly non-linear regime. Together with previous investigations this yields an analytic theory of the errors for moments and connected moments of counts in cells from highly nonlinear to weakly nonlinear scales. The final analytic formu...
Systematic review of the empirical evidence of study publication bias and outcome reporting bias.
Directory of Open Access Journals (Sweden)
Kerry Dwan
Full Text Available BACKGROUND: The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias has been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Until recently, outcome reporting bias has received less attention. METHODOLOGY/PRINCIPAL FINDINGS: We review and summarise the evidence from a series of cohort studies that have assessed study publication bias and outcome reporting bias in randomised controlled trials. Sixteen studies were eligible of which only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Eleven of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7. In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. CONCLUSIONS: Recent work provides direct empirical evidence for the existence of study publication bias and outcome reporting bias. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.
Matthew Gentzkow; Jesse M. Shapiro
2005-01-01
A Bayesian consumer who is uncertain about the quality of an information source will infer that the source is of higher quality when its reports conform to the consumer's prior expectations. We use this fact to build a model of media bias in which firms slant their reports toward the prior beliefs of their customers in order to build a reputation for quality. Bias emerges in our model even though it can make all market participants worse off. The model predicts that bias will be less severe w...
Biased predecision processing.
Brownstein, Aaron L
2003-07-01
Decision makers conduct biased predecision processing when they restructure their mental representation of the decision environment to favor one alternative before making their choice. The question of whether biased predecision processing occurs has been controversial since L. Festinger (1957) maintained that it does not occur. The author reviews relevant research in sections on theories of cognitive dissonance, decision conflict, choice certainty, action control, action phases, dominance structuring, differentiation and consolidation, constructive processing, motivated reasoning, and groupthink. Some studies did not find evidence of biased predecision processing, but many did. In the Discussion section, the moderators are summarized and used to assess the theories.
Berkson’s bias, selection bias, and missing data
Westreich, Daniel
2012-01-01
While Berkson’s bias is widely recognized in the epidemiologic literature, it remains underappreciated as a model of both selection bias and bias due to missing data. Simple causal diagrams and 2×2 tables illustrate how Berkson’s bias connects to collider bias and selection bias more generally, and show the strong analogies between Berksonian selection bias and bias due to missing data. In some situations, considerations of whether data are missing at random or missing not at random is less i...
DEFF Research Database (Denmark)
Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan
2006-01-01
This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved........ The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...
Introduction to Unconscious Bias
Schmelz, Joan T.
2010-05-01
We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.
Increasingly minimal bias routing
Energy Technology Data Exchange (ETDEWEB)
Bataineh, Abdulla; Court, Thomas; Roweth, Duncan
2017-02-21
A system and algorithm configured to generate diversity at the traffic source so that packets are uniformly distributed over all of the available paths, but to increase the likelihood of taking a minimal path with each hop the packet takes. This is achieved by configuring routing biases so as to prefer non-minimal paths at the injection point, but increasingly prefer minimal paths as the packet proceeds, referred to herein as Increasing Minimal Bias (IMB).
Measuring agricultural policy bias
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
2010-01-01
that the agricultural price incentive bias generally perceived to exist during the 1980s was largely eliminated during the 1990s. Results also demonstrate that general equilibrium effects and country-specific characteristics are crucial for determining the sign and magnitude of agricultural bias. Our comprehensive...... protection measure is therefore uniquely suited to capture the full impact of trade policies on relative agricultural price incentives....
Probability and (Braiding) Statistics
2016-01-01
Given recent progress in the realization of Majorana zero modes in semiconducting nanowires with proximity-induced superconductivity, a crucial next step is to attempt an experimental demonstration of the predicted braiding statistics associated with the Majorana mode. Such a demonstration should, in principle, confirm that observed zero-bias anomalies are indeed indicative of the presence of anyonic Majorana zero modes. Moreover, such a demonstration would be a breakthrough at the level of f...
Biased causal inseparable game
Bhattacharya, Some Sankar
2015-01-01
Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...
... with Alzheimer’s CCAN Peer Network COPD Caregiving Caregiver Statistics Statistics on Family Caregivers and Family Caregiving Caregiving Population ... Health Care Caregiver Self-Awareness State by State Statistics Caregiving Population The value of the services family ...
Discrete angle biasing in Monte Carlo radiation transport
Energy Technology Data Exchange (ETDEWEB)
Cramer, S.N.
1988-05-01
An angular biasing procedure is presented for use in Monte Carlo radiation transport with discretized scattering angle data. As in more general studies, the method is shown to reduce statistical weight fluctuations when it is combined with the exponential transformation. This discrete data application has a simple analytic form which is problem independent. The results from a sample problem illustrate the variance reduction and efficiency characteristics of the combined biasing procedures, and a large neutron and gamma ray integral experiment is also calculated. A proposal is given for the possible code generation of the biasing parameter p and the preferential direction /ovr/Omega///sub 0/ used in the combined biasing schemes.
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
. 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...... 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...
Norén, Patrik
2013-01-01
Algebraic statistics brings together ideas from algebraic geometry, commutative algebra, and combinatorics to address problems in statistics and its applications. Computer algebra provides powerful tools for the study of algorithms and software. However, these tools are rarely prepared to address statistical challenges and therefore new algebraic results need often be developed. This way of interplay between algebra and statistics fertilizes both disciplines. Algebraic statistics is a relativ...
Artificial bias typically neglected in comparisons of uncertain atmospheric data
Pitkänen, Mikko R. A.; Mikkonen, Santtu; Lehtinen, Kari E. J.; Lipponen, Antti; Arola, Antti
2016-09-01
Publications in atmospheric sciences typically neglect biases caused by regression dilution (bias of the ordinary least squares line fitting) and regression to the mean (RTM) in comparisons of uncertain data. We use synthetic observations mimicking real atmospheric data to demonstrate how the biases arise from random data uncertainties of measurements, model output, or satellite retrieval products. Further, we provide examples of typical methods of data comparisons that have a tendency to pronounce the biases. The results show, that data uncertainties can significantly bias data comparisons due to regression dilution and RTM, a fact that is known in statistics but disregarded in atmospheric sciences. Thus, we argue that often these biases are widely regarded as measurement or modeling errors, for instance, while they in fact are artificial. It is essential that atmospheric and geoscience communities become aware of and consider these features in research.
Simulating currency substitution bias
M. Boon (Martin); C.J.M. Kool (Clemens); C.G. de Vries (Casper)
1989-01-01
textabstractThe sign and size of estimates of the elasticity of currency substitution critically depend on the definition of the oppurtunity costs of holding money. We investigate possible biases by means of Monte Carlo experiments, as sufficient real data are not available.
Zalk, Sue Rosenberg; And Others
This study investigated children's sex biased attitudes as a function of the sex, age, and race of the child as well as a geographical-SES factor. Two attitudes were measured on a 55-item questionnaire: Sex Pride (attributing positive characteristics to a child of the same sex) and Sex Prejudice (attributing negative characteristics to a child of…
Forster, Malcolm R
2011-01-01
Statisticians and philosophers of science have many common interests but restricted communication with each other. This volume aims to remedy these shortcomings. It provides state-of-the-art research in the area of philosophy of statistics by encouraging numerous experts to communicate with one another without feeling "restricted” by their disciplines or thinking "piecemeal” in their treatment of issues. A second goal of this book is to present work in the field without bias toward any particular statistical paradigm. Broadly speaking, the essays in this Handbook are concerned with problems of induction, statistics and probability. For centuries, foundational problems like induction have been among philosophers' favorite topics; recently, however, non-philosophers have increasingly taken a keen interest in these issues. This volume accordingly contains papers by both philosophers and non-philosophers, including scholars from nine academic disciplines.
新家, 健精
2013-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
Pestman, Wiebe R
2009-01-01
This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.
Bayesian Methods for Statistical Analysis
Puza, Borek
2015-01-01
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete c...
Olowofoyeku, AA
2016-01-01
This article addresses the issues attending common law collegiate courts’ engagements with allegations of bias within their own ranks. It will be argued that, in such cases, it would be inappropriate to involve the collegiate panel or any member thereof in the decision, since such involvement inevitably encounters difficulties. The common law’s dilemmas require drastic solutions, but the common law arguably is illequipped to implement the required change. The answer, it will be argued, is ...
Behavioral Biases in Interpersonal Contexts
N. Liu (Ning)
2017-01-01
markdownabstractThis thesis presents evidence suggesting that the same types of biases in individual decision making under uncertainty pertain in interpersonal contexts. The chapters above demonstrate in specific contexts how specific interpersonal factors attenuate, amplify, or replicate these bias
Publication bias and the failure of replication in experimental psychology.
Francis, Gregory
2012-12-01
Replication of empirical findings plays a fundamental role in science. Among experimental psychologists, successful replication enhances belief in a finding, while a failure to replicate is often interpreted to mean that one of the experiments is flawed. This view is wrong. Because experimental psychology uses statistics, empirical findings should appear with predictable probabilities. In a misguided effort to demonstrate successful replication of empirical findings and avoid failures to replicate, experimental psychologists sometimes report too many positive results. Rather than strengthen confidence in an effect, too much successful replication actually indicates publication bias, which invalidates entire sets of experimental findings. Researchers cannot judge the validity of a set of biased experiments because the experiment set may consist entirely of type I errors. This article shows how an investigation of the effect sizes from reported experiments can test for publication bias by looking for too much successful replication. Simulated experiments demonstrate that the publication bias test is able to discriminate biased experiment sets from unbiased experiment sets, but it is conservative about reporting bias. The test is then applied to several studies of prominent phenomena that highlight how publication bias contaminates some findings in experimental psychology. Additional simulated experiments demonstrate that using Bayesian methods of data analysis can reduce (and in some cases, eliminate) the occurrence of publication bias. Such methods should be part of a systematic process to remove publication bias from experimental psychology and reinstate the important role of replication as a final arbiter of scientific findings.
Assessing Bias in Search Engines.
Mowshowitz, Abbe; Kawaguchi, Akira
2002-01-01
Addresses the measurement of bias in search engines on the Web, defining bias as the balance and representation of items in a collection retrieved from a database for a set of queries. Assesses bias by measuring the deviation from the ideal of the distribution produced by a particular search engine. (Author/LRW)
Sadovskii, Michael V
2012-01-01
This volume provides a compact presentation of modern statistical physics at an advanced level. Beginning with questions on the foundations of statistical mechanics all important aspects of statistical physics are included, such as applications to ideal gases, the theory of quantum liquids and superconductivity and the modern theory of critical phenomena. Beyond that attention is given to new approaches, such as quantum field theory methods and non-equilibrium problems.
... Foodborne, Waterborne, and Environmental Diseases Mycotic Diseases Branch Histoplasmosis Statistics Recommend on Facebook Tweet Share Compartir How common is histoplasmosis? In the United States, an estimated 60% to ...
Szulc, Stefan
1965-01-01
Statistical Methods provides a discussion of the principles of the organization and technique of research, with emphasis on its application to the problems in social statistics. This book discusses branch statistics, which aims to develop practical ways of collecting and processing numerical data and to adapt general statistical methods to the objectives in a given field.Organized into five parts encompassing 22 chapters, this book begins with an overview of how to organize the collection of such information on individual units, primarily as accomplished by government agencies. This text then
Goodman, Joseph W
2015-01-01
This book discusses statistical methods that are useful for treating problems in modern optics, and the application of these methods to solving a variety of such problems This book covers a variety of statistical problems in optics, including both theory and applications. The text covers the necessary background in statistics, statistical properties of light waves of various types, the theory of partial coherence and its applications, imaging with partially coherent light, atmospheric degradations of images, and noise limitations in the detection of light. New topics have been introduced i
Forbes, Catherine; Hastings, Nicholas; Peacock, Brian J.
2010-01-01
A new edition of the trusted guide on commonly used statistical distributions Fully updated to reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues to serve as an authoritative guide on the application of statistical methods to research across various disciplines. The book provides a concise presentation of popular statistical distributions along with the necessary knowledge for their successful use in data modeling and analysis. Following a basic introduction, forty popular distributions are outlined in individual chapters that are complete with re
Statistical theory and inference
Olive, David J
2014-01-01
This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families. Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name" distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.
Excess success for three related papers on racial bias
2015-01-01
Three related articles reported that racial bias altered perceptual experience and influenced decision-making. These findings have been applied to training programs for law enforcement, and elsewhere, to mitigate racial bias. However, a statistical analysis of each of the three articles finds that the reported experimental results should be rare, even if the theoretical ideas were correct. The analysis estimates that the probability of the reported experimental success for the articles is 0.0...
Lyons, L
2016-01-01
Accelerators and detectors are expensive, both in terms of money and human effort. It is thus important to invest effort in performing a good statistical anal- ysis of the data, in order to extract the best information from it. This series of five lectures deals with practical aspects of statistical issues that arise in typical High Energy Physics analyses.
Glaz, Joseph
2009-01-01
Suitable for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science and medicine, this title brings together a collection of chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.
Bias and Causation Models and Judgment for Valid Comparisons
Weisberg, Herbert I
2010-01-01
A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects. Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation pre
On the dynamical origin of bias in clusters of galaxies
Colafrancesco, Sergio; Del Popolo, A; Colafrancesco, S; Del Popolo, A
1994-01-01
We study the effect of the dynamical friction induced by the presence of substructure on the statistics of the collapse of density peaks. Applying the results of a former paper we show that within high density environments, like rich clusters of galaxies, the collapse of smaller peaks is strongly delayed until very late epochs. A bias of dynamical nature thus naturally arises because high density peaks preferentially collapse For a standard CDM model we find that this dynamical bias can account for a substantial part of the total bias required by observations on cluster scales.
Publication Bias ( The "File-Drawer Problem") in Scientific Inference
Scargle, Jeffrey D.; DeVincenzi, Donald (Technical Monitor)
1999-01-01
Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always miss-estimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical combination can be trusted only if it is known with certainty that all studies that have been carried out are included. Such certainty is virtually impossible to achieve in literature surveys.
Wannier, Gregory H
2010-01-01
Until recently, the field of statistical physics was traditionally taught as three separate subjects: thermodynamics, statistical mechanics, and kinetic theory. This text, a forerunner in its field and now a classic, was the first to recognize the outdated reasons for their separation and to combine the essentials of the three subjects into one unified presentation of thermal physics. It has been widely adopted in graduate and advanced undergraduate courses, and is recommended throughout the field as an indispensable aid to the independent study and research of statistical physics.Designed for
Blakemore, J S
1962-01-01
Semiconductor Statistics presents statistics aimed at complementing existing books on the relationships between carrier densities and transport effects. The book is divided into two parts. Part I provides introductory material on the electron theory of solids, and then discusses carrier statistics for semiconductors in thermal equilibrium. Of course a solid cannot be in true thermodynamic equilibrium if any electrical current is passed; but when currents are reasonably small the distribution function is but little perturbed, and the carrier distribution for such a """"quasi-equilibrium"""" co
Ross, Sheldon M
2005-01-01
In this revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. To quote from the preface, ""It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."" Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.* Ross's clear writin
Ross, Sheldon M
2010-01-01
In this 3rd edition revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. Concepts are motivated, illustrated and explained in a way that attempts to increase one's intuition. To quote from the preface, ""It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."" Ross achieves this
Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James
2014-01-01
Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.
Model selection bias and Freedman's paradox
Lukacs, P.M.; Burnham, K.P.; Anderson, D.R.
2010-01-01
In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly "significant" when the number of data points is similar in magnitude to the number of variables. A new type of model averaging estimator based on model selection with Akaike's AIC is used with linear regression to investigate the problems of likely inclusion of spurious effects and model selection bias, the bias introduced while using the data to select a single seemingly "best" model from a (often large) set of models employing many predictor variables. The new model averaging estimator helps reduce these problems and provides confidence interval coverage at the nominal level while traditional stepwise selection has poor inferential properties. ?? The Institute of Statistical Mathematics, Tokyo 2009.
Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...
DEFF Research Database (Denmark)
Tryggestad, Kjell
2004-01-01
The study aims is to describe how the inclusion and exclusion of materials and calculative devices construct the boundaries and distinctions between statistical facts and artifacts in economics. My methodological approach is inspired by John Graunt's (1667) Political arithmetic and more recent work...... within constructivism and the field of Science and Technology Studies (STS). The result of this approach is here termed reversible statistics, reconstructing the findings of a statistical study within economics in three different ways. It is argued that all three accounts are quite normal, albeit...... in different ways. The presence and absence of diverse materials, both natural and political, is what distinguishes them from each other. Arguments are presented for a more symmetric relation between the scientific statistical text and the reader. I will argue that a more symmetric relation can be achieved...
... Resources Conducting Clinical Trials Statistical Tools and Data Terminology Resources NCI Data Catalog Cryo-EM NCI's Role ... Contacts Other Funding Find NCI funding for small business innovation, technology transfer, and contracts Training Cancer Training ...
The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute works to provide information on cancer statistics in an effort to reduce the burden of cancer among the U.S. population.
U.S. Department of Health & Human Services — The CMS Center for Strategic Planning produces an annual CMS Statistics reference booklet that provides a quick reference for summary information about health...
Serdobolskii, Vadim Ivanovich
2007-01-01
This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters.This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution.Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. ...
Radar error statistics for the space shuttle
Lear, W. M.
1979-01-01
Radar error statistics of C-band and S-band that are recommended for use with the groundtracking programs to process space shuttle tracking data are presented. The statistics are divided into two parts: bias error statistics, using the subscript B, and high frequency error statistics, using the subscript q. Bias errors may be slowly varying to constant. High frequency random errors (noise) are rapidly varying and may or may not be correlated from sample to sample. Bias errors were mainly due to hardware defects and to errors in correction for atmospheric refraction effects. High frequency noise was mainly due to hardware and due to atmospheric scintillation. Three types of atmospheric scintillation were identified: horizontal, vertical, and line of sight. This was the first time that horizontal and line of sight scintillations were identified.
Outcome predictability biases learning.
Griffiths, Oren; Mitchell, Chris J; Bethmont, Anna; Lovibond, Peter F
2015-01-01
Much of contemporary associative learning research is focused on understanding how and when the associative history of cues affects later learning about those cues. Very little work has investigated the effects of the associative history of outcomes on human learning. Three experiments extended the "learned irrelevance" paradigm from the animal conditioning literature to examine the influence of an outcome's prior predictability on subsequent learning of relationships between cues and that outcome. All 3 experiments found evidence for the idea that learning is biased by the prior predictability of the outcome. Previously predictable outcomes were readily associated with novel predictive cues, whereas previously unpredictable outcomes were more readily associated with novel nonpredictive cues. This finding highlights the importance of considering the associative history of outcomes, as well as cues, when interpreting multistage designs. Associative and cognitive explanations of this certainty matching effect are discussed.
Improved analysis of bias in Monte Carlo criticality safety
Haley, Thomas C.
2000-08-01
Criticality safety, the prevention of nuclear chain reactions, depends on Monte Carlo computer codes for most commercial applications. One major shortcoming of these codes is the limited accuracy of the atomic and nuclear data files they depend on. In order to apply a code and its data files to a given criticality safety problem, the code must first be benchmarked against similar problems for which the answer is known. The difference between a code prediction and the known solution is termed the "bias" of the code. Traditional calculations of the bias for application to commercial criticality problems are generally full of assumptions and lead to large uncertainties which must be conservatively factored into the bias as statistical tolerances. Recent trends in storing commercial nuclear fuel---narrowed regulatory margins of safety, degradation of neutron absorbers, the desire to use higher enrichment fuel, etc.---push the envelope of criticality safety. They make it desirable to minimize uncertainty in the bias to accommodate these changes, and they make it vital to understand what assumptions are safe to make under what conditions. A set of improved procedures is proposed for (1) developing multivariate regression bias models, and (2) applying multivariate regression bias models. These improved procedures lead to more accurate estimates of the bias and much smaller uncertainties about this estimate, while also generally providing more conservative results. The drawback is that the procedures are not trivial and are highly labor intensive to implement. The payback in savings in margin to criticality and conservatism for calculations near regulatory and safety limits may be worth this cost. To develop these procedures, a bias model using the statistical technique of weighted least squares multivariate regression is developed in detail. Problems that can occur from a weak statistical analysis are highlighted, and a solid statistical method for developing the bias
Jana, Madhusudan
2015-01-01
Statistical mechanics is self sufficient, written in a lucid manner, keeping in mind the exam system of the universities. Need of study this subject and its relation to Thermodynamics is discussed in detail. Starting from Liouville theorem gradually, the Statistical Mechanics is developed thoroughly. All three types of Statistical distribution functions are derived separately with their periphery of applications and limitations. Non-interacting ideal Bose gas and Fermi gas are discussed thoroughly. Properties of Liquid He-II and the corresponding models have been depicted. White dwarfs and condensed matter physics, transport phenomenon - thermal and electrical conductivity, Hall effect, Magneto resistance, viscosity, diffusion, etc. are discussed. Basic understanding of Ising model is given to explain the phase transition. The book ends with a detailed coverage to the method of ensembles (namely Microcanonical, canonical and grand canonical) and their applications. Various numerical and conceptual problems ar...
Schwabl, Franz
2006-01-01
The completely revised new edition of the classical book on Statistical Mechanics covers the basic concepts of equilibrium and non-equilibrium statistical physics. In addition to a deductive approach to equilibrium statistics and thermodynamics based on a single hypothesis - the form of the microcanonical density matrix - this book treats the most important elements of non-equilibrium phenomena. Intermediate calculations are presented in complete detail. Problems at the end of each chapter help students to consolidate their understanding of the material. Beyond the fundamentals, this text demonstrates the breadth of the field and its great variety of applications. Modern areas such as renormalization group theory, percolation, stochastic equations of motion and their applications to critical dynamics, kinetic theories, as well as fundamental considerations of irreversibility, are discussed. The text will be useful for advanced students of physics and other natural sciences; a basic knowledge of quantum mechan...
Error covariance calculation for forecast bias estimation in hydrologic data assimilation
Pauwels, Valentijn R. N.; De Lannoy, Gabriëlle J. M.
2015-12-01
To date, an outstanding issue in hydrologic data assimilation is a proper way of dealing with forecast bias. A frequently used method to bypass this problem is to rescale the observations to the model climatology. While this approach improves the variability in the modeled soil wetness and discharge, it is not designed to correct the results for any bias. Alternatively, attempts have been made towards incorporating dynamic bias estimates into the assimilation algorithm. Persistent bias models are most often used to propagate the bias estimate, where the a priori forecast bias error covariance is calculated as a constant fraction of the unbiased a priori state error covariance. The latter approach is a simplification to the explicit propagation of the bias error covariance. The objective of this paper is to examine to which extent the choice for the propagation of the bias estimate and its error covariance influence the filter performance. An Observation System Simulation Experiment (OSSE) has been performed, in which ground water storage observations are assimilated into a biased conceptual hydrologic model. The magnitudes of the forecast bias and state error covariances are calibrated by optimizing the innovation statistics of groundwater storage. The obtained bias propagation models are found to be identical to persistent bias models. After calibration, both approaches for the estimation of the forecast bias error covariance lead to similar results, with a realistic attribution of error variances to the bias and state estimate, and significant reductions of the bias in both the estimates of groundwater storage and discharge. Overall, the results in this paper justify the use of the traditional approach for online bias estimation with a persistent bias model and a simplified forecast bias error covariance estimation.
Freund, Rudolf J; Wilson, William J
2010-01-01
Statistical Methods, 3e provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach emphasizing concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples and data exercises organized by level of difficulty. This text requires that a student be familiar with algebra. New to this edition: NEW expansion of exercises a
Levine-Wissing, Robin
2012-01-01
All Access for the AP® Statistics Exam Book + Web + Mobile Everything you need to prepare for the Advanced Placement® exam, in a study system built around you! There are many different ways to prepare for an Advanced Placement® exam. What's best for you depends on how much time you have to study and how comfortable you are with the subject matter. To score your highest, you need a system that can be customized to fit you: your schedule, your learning style, and your current level of knowledge. This book, and the online tools that come with it, will help you personalize your AP® Statistics prep
Mandl, Franz
1988-01-01
The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition E. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A. C. Phillips Computing for Scient
Rohatgi, Vijay K
2003-01-01
Unified treatment of probability and statistics examines and analyzes the relationship between the two fields, exploring inferential issues. Numerous problems, examples, and diagrams--some with solutions--plus clear-cut, highlighted summaries of results. Advanced undergraduate to graduate level. Contents: 1. Introduction. 2. Probability Model. 3. Probability Distributions. 4. Introduction to Statistical Inference. 5. More on Mathematical Expectation. 6. Some Discrete Models. 7. Some Continuous Models. 8. Functions of Random Variables and Random Vectors. 9. Large-Sample Theory. 10. General Meth
Davidson, Norman
2003-01-01
Clear and readable, this fine text assists students in achieving a grasp of the techniques and limitations of statistical mechanics. The treatment follows a logical progression from elementary to advanced theories, with careful attention to detail and mathematical development, and is sufficiently rigorous for introductory or intermediate graduate courses.Beginning with a study of the statistical mechanics of ideal gases and other systems of non-interacting particles, the text develops the theory in detail and applies it to the study of chemical equilibrium and the calculation of the thermody
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-12-31
For the year 1997 and 1998, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually includes also historical time series over a longer period (see e.g. Energiatilastot 1997, Statistics Finland, Helsinki 1998, ISSN 0784-3165). The inside of the Review`s back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO{sub 2}-emissions, Electricity supply, Energy imports by country of origin in January-September 1998, Energy exports by recipient country in January-September 1998, Consumer prices of liquid fuels, Consumer prices of hard coal, Natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, Value added taxes and fiscal charges and fees included in consumer prices of some energy sources, Energy taxes and precautionary stock fees, pollution fees on oil products
Energy Technology Data Exchange (ETDEWEB)
NONE
1998-12-31
For the year 1997 and 1998, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually includes also historical time series over a longer period (see e.g. Energiatilastot 1996, Statistics Finland, Helsinki 1997, ISSN 0784-3165). The inside of the Review`s back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO{sub 2}-emissions, Electricity supply, Energy imports by country of origin in January-June 1998, Energy exports by recipient country in January-June 1998, Consumer prices of liquid fuels, Consumer prices of hard coal, Natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, Value added taxes and fiscal charges and fees included in consumer prices of some energy sources, Energy taxes and precautionary stock fees, pollution fees on oil products
Gallavotti, Giovanni
2011-01-01
C. Cercignani: A sketch of the theory of the Boltzmann equation.- O.E. Lanford: Qualitative and statistical theory of dissipative systems.- E.H. Lieb: many particle Coulomb systems.- B. Tirozzi: Report on renormalization group.- A. Wehrl: Basic properties of entropy in quantum mechanics.
Cirino, Robert
Non-language elements of bias in mass media--such as images, sounds, tones of voices, inflection, and facial expressions--are invariably integrated with the choice of language. Further, they have an emotional impact that is often greater than that of language. It is essential that the teacher of English deal with this non-language bias since it is…
Observable Priors: Limiting Biases in Estimated Parameters for Incomplete Orbits
Kosmo, Kelly; Martinez, Gregory; Hees, Aurelien; Witzel, Gunther; Ghez, Andrea M.; Do, Tuan; Sitarski, Breann; Chu, Devin; Dehghanfar, Arezu
2017-01-01
Over twenty years of monitoring stellar orbits at the Galactic center has provided an unprecedented opportunity to study the physics and astrophysics of the supermassive black hole (SMBH) at the center of the Milky Way Galaxy. In order to constrain the mass of and distance to the black hole, and to evaluate its gravitational influence on orbiting bodies, we use Bayesian statistics to infer black hole and stellar orbital parameters from astrometric and radial velocity measurements of stars orbiting the central SMBH. Unfortunately, most of the short period stars in the Galactic center have periods much longer than our twenty year time baseline of observations, resulting in incomplete orbital phase coverage--potentially biasing fitted parameters. Using the Bayesian statistical framework, we evaluate biases in the black hole and orbital parameters of stars with varying phase coverage, using various prior models to fit the data. We present evidence that incomplete phase coverage of an orbit causes prior assumptions to bias statistical quantities, and propose a solution to reduce these biases for orbits with low phase coverage. The explored solution assumes uniformity in the observables rather than in the inferred model parameters, as is the current standard method of orbit fitting. Of the cases tested, priors that assume uniform astrometric and radial velocity observables reduce the biases in the estimated parameters. The proposed method will not only improve orbital estimates of stars orbiting the central SMBH, but can also be extended to other orbiting bodies with low phase coverage such as visual binaries and exoplanets.
Publication bias in dermatology systematic reviews and meta-analyses.
Atakpo, Paul; Vassar, Matt
2016-05-01
Systematic reviews and meta-analyses in dermatology provide high-level evidence for clinicians and policy makers that influence clinical decision making and treatment guidelines. One methodological problem with systematic reviews is the under representation of unpublished studies. This problem is due in part to publication bias. Omission of statistically non-significant data from meta-analyses may result in overestimation of treatment effect sizes which may lead to clinical consequences. Our goal was to assess whether systematic reviewers in dermatology evaluate and report publication bias. Further, we wanted to conduct our own evaluation of publication bias on meta-analyses that failed to do so. Our study considered systematic reviews and meta-analyses from ten dermatology journals from 2006 to 2016. A PubMed search was conducted, and all full-text articles that met our inclusion criteria were retrieved and coded by the primary author. 293 articles were included in our analysis. Additionally, we formally evaluated publication bias in meta-analyses that failed to do so using trim and fill and cumulative meta-analysis by precision methods. Publication bias was mentioned in 107 articles (36.5%) and was formally evaluated in 64 articles (21.8%). Visual inspection of a funnel plot was the most common method of evaluating publication bias. Publication bias was present in 45 articles (15.3%), not present in 57 articles (19.5%) and not determined in 191 articles (65.2%). Using the trim and fill method, 7 meta-analyses (33.33%) showed evidence of publication bias. Although the trim and fill method only found evidence of publication bias in 7 meta-analyses, the cumulative meta-analysis by precision method found evidence of publication bias in 15 meta-analyses (71.4%). Many of the reviews in our study did not mention or evaluate publication bias. Further, of the 42 articles that stated following PRISMA reporting guidelines, 19 (45.2%) evaluated for publication bias. In
Anandamide mediates cognitive judgement bias in rats.
Kregiel, J; Malek, N; Popik, P; Starowicz, K; Rygula, R
2016-02-01
In the present study, we investigated the effects of acute pharmacological manipulation of the endocannabinoid (EC) system on the valence of cognitive judgement bias of rats in the ambiguous-cue interpretation (ACI) paradigm. To accomplish this goal, after initial behavioural training, different groups of rats received single, systemic injections of the irreversible anandamide (AEA) hydrolysis inhibitor URB597, the cannabinoid receptor type 1 (CB1) inverse agonist AM251, the cannabinoid receptor type 2 (CB2) inverse agonist AM630, the combination of URB597 and AM251, and a combination of URB597 and AM630 and were subsequently tested with the ACI paradigm. We report that URB597 at a dose of 1 mg/kg significantly biased animals towards positive interpretation of the ambiguous cue and that this effect was abolished by pre-treatment with AM251 (1 mg/kg) or AM630 (1 mg/kg). The CB1 and CB2 inverse agonists administered alone (1 mg/kg) had no statistically significant effects on the interpretation of the ambiguous cue by rats. Our findings suggest involvement of the endocannabinoid system in the mediation of optimistic judgement bias.
Challenges of guarantee-time bias.
Giobbie-Hurder, Anita; Gelber, Richard D; Regan, Meredith M
2013-08-10
The potential for guarantee-time bias (GTB), also known as immortal time bias, exists whenever an analysis that is timed from enrollment or random assignment, such as disease-free or overall survival, is compared across groups defined by a classifying event occurring sometime during follow-up. The types of events associated with GTB are varied and may include the occurrence of objective disease response, onset of toxicity, or seroconversion. However, comparative analyses using these types of events as predictors are different from analyses using baseline characteristics that are specified completely before the occurrence of any outcome event. Recognizing the potential for GTB is not always straightforward, and it can be challenging to know when GTB is influencing the results of an analysis. This article defines GTB, provides examples of GTB from several published articles, and discusses three analytic techniques that can be used to remove the bias: conditional landmark analysis, extended Cox model, and inverse probability weighting. The strengths and limitations of each technique are presented. As an example, we explore the effect of bisphosphonate use on disease-free survival (DFS) using data from the BIG (Breast International Group) 1-98 randomized clinical trial. An analysis using a naive approach showed substantial benefit for patients who received bisphosphonate therapy. In contrast, analyses using the three methods known to remove GTB showed no statistical evidence of a reduction in risk of a DFS event with bisphosphonate therapy.
Publication bias in epidemiological studies.
Siddiqi, Nazish
2011-06-01
Communication of research findings is the utmost responsibility of all scientists. Publication bias occurs if scientific studies with negative or null results fail to get published. This can happen due to bias in submitting, reviewing, accepting, publishing or aggregating scientific literature that fails to show positive results on a particular topic. Publication bias can make scientific literature unrepresentative of the actual research studies. This can give the reader a false impression about the beneficial effects of a particular treatment or intervention and can influence clinical decision making. Publication bias is more common than it is actually considered to be, but there are ways to detect and prevent it. This paper comments on the occurrence, types and consequences of publication bias and the strategies employed to detect and control it.
Interloper bias in future large-scale structure surveys
Pullen, Anthony R; Dore, Olivier; Raccanelli, Alvise
2015-01-01
Next-generation spectroscopic surveys will map the large-scale structure of the observable universe, using emission line galaxies as tracers. While each survey will map the sky with a specific emission line, interloping emission lines can masquerade as the survey's intended emission line at different redshifts. Interloping lines from galaxies that are not removed can contaminate the power spectrum measurement, mixing correlations from various redshifts and diluting the true signal. We assess the potential for power spectrum contamination, finding that an interloper fraction worse than 0.2% could bias power spectrum measurements for future surveys by more than 10% of statistical errors, while also biasing inferences based on the power spectrum. We also construct a formalism for predicting biases for cosmological parameter measurements, and we demonstrate that a 0.3% interloper fraction could bias measurements of the growth rate by more than 10% of the error, which can affect constraints from upcoming surveys o...
An introduction to Bartlett correction and bias reduction
Cordeiro, Gauss M
2014-01-01
This book presents a concise introduction to Bartlett and Bartlett-type corrections of statistical tests and bias correction of point estimators. The underlying idea behind both groups of corrections is to obtain higher accuracy in small samples. While the main focus is on corrections that can be analytically derived, the authors also present alternative strategies for improving estimators and tests based on bootstrap, a data resampling technique, and discuss concrete applications to several important statistical models.
Linear and non-linear bias: predictions versus measurements
Hoffmann, K.; Bel, J.; Gaztañaga, E.
2017-02-01
We study the linear and non-linear bias parameters which determine the mapping between the distributions of galaxies and the full matter density fields, comparing different measurements and predictions. Associating galaxies with dark matter haloes in the Marenostrum Institut de Ciències de l'Espai (MICE) Grand Challenge N-body simulation, we directly measure the bias parameters by comparing the smoothed density fluctuations of haloes and matter in the same region at different positions as a function of smoothing scale. Alternatively, we measure the bias parameters by matching the probability distributions of halo and matter density fluctuations, which can be applied to observations. These direct bias measurements are compared to corresponding measurements from two-point and different third-order correlations, as well as predictions from the peak-background model, which we presented in previous papers using the same data. We find an overall variation of the linear bias measurements and predictions of ∼5 per cent with respect to results from two-point correlations for different halo samples with masses between ∼1012and1015 h-1 M⊙ at the redshifts z = 0.0 and 0.5. Variations between the second- and third-order bias parameters from the different methods show larger variations, but with consistent trends in mass and redshift. The various bias measurements reveal a tight relation between the linear and the quadratic bias parameters, which is consistent with results from the literature based on simulations with different cosmologies. Such a universal relation might improve constraints on cosmological models, derived from second-order clustering statistics at small scales or higher order clustering statistics.
Natrella, Mary Gibbons
2005-01-01
Formulated to assist scientists and engineers engaged in army ordnance research and development programs, this well-known and highly regarded handbook is a ready reference for advanced undergraduate and graduate students as well as for professionals seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Topics include characterizing and comparing the measured performance of a material, product, or process; general considerations in planning experiments; statistical techniques for analyzing extreme-value data; use of transformations
Meneghetti, M; Dahle, H; Limousin, M
2013-01-01
The existence of an arc statistics problem was at the center of a strong debate in the last fifteen years. With the aim to clarify if the optical depth for giant gravitational arcs by galaxy clusters in the so called concordance model is compatible with observations, several studies were carried out which helped to significantly improve our knowledge of strong lensing clusters, unveiling their extremely complex internal structure. In particular, the abundance and the frequency of strong lensing events like gravitational arcs turned out to be a potentially very powerful tool to trace the structure formation. However, given the limited size of observational and theoretical data-sets, the power of arc statistics as a cosmological tool has been only minimally exploited so far. On the other hand, the last years were characterized by significant advancements in the field, and several cluster surveys that are ongoing or planned for the near future seem to have the potential to make arc statistics a competitive cosmo...
Local model uncertainty and incomplete-data bias
Copas, John; Eguchi, Shinto; Ferguson, Claire; Henderson, Neil; Onabid, Mathias; Parker, Helen; Pritchard, Gareth; Sharif, Maarya; Zhu, Ximin; Wit, Ernst; McGrory, Clare; Barry, Sarah; Fearnside, Alastair; Nguyen, The Mahn; Conte, Rossella Lo; Weir, James; Miller, James; Recchia, Angela; Wit, Ernst; Purutçuoğlu, Vilda; Wit, Ernst
2005-01-01
Problems of the analysis of data with incomplete observations are all too familiar in statistics. They are doubly difficult if we are also uncertain about the choice of model. We propose a general formulation for the discussion of such problems and develop approximations to the resulting bias of max
Cognitive Bias in Systems Verification
Larson, Steve
2012-01-01
Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.
Administrative bias in South Africa
Directory of Open Access Journals (Sweden)
E S Nwauche
2005-01-01
Full Text Available This article reviews the interpretation of section 6(2(aii of the Promotion of Administrative Justice Act which makes an administrator “biased or reasonably suspected of bias” a ground of judicial review. In this regard, the paper reviews the determination of administrative bias in South Africa especially highlighting the concept of institutional bias. The paper notes that inspite of the formulation of the bias ground of review the test for administrative bias is the reasonable apprehension test laid down in the case of President of South Africa v South African Rugby Football Union(2 which on close examination is not the same thing. Accordingly the paper urges an alternative interpretation that is based on the reasonable suspicion test enunciated in BTR Industries South Africa (Pty Ltd v Metal and Allied Workers Union and R v Roberts. Within this context, the paper constructs a model for interpreting the bias ground of review that combines the reasonable suspicion test as interpreted in BTR Industries and R v Roberts, the possibility of the waiver of administrative bias, the curative mechanism of administrative appeal as well as some level of judicial review exemplified by the jurisprudence of article 6(1 of the European Convention of Human Rights, especially in the light of the contemplation of the South African Magistrate Court as a jurisdictional route of judicial review.
Gender bias in academic recruitment
DEFF Research Database (Denmark)
Abramo, Giovanni; D’Angelo, Ciriaco Andrea; Rosati, Francesco
2016-01-01
It is well known that women are underrepresented in the academic systems of many countries. Gender discrimination is one of the factors that could contribute to this phenomenon. This study considers a recent national academic recruitment campaign in Italy, examining whether women are subject...... to more or less bias than men. The findings show that no gender-related differences occur among the candidates who benefit from positive bias, while among those candidates affected by negative bias, the incidence of women is lower than that of men. Among the factors that determine success in a competition...
Obesity, the endocannabinoid system, and bias arising from pharmaceutical sponsorship.
Directory of Open Access Journals (Sweden)
John M McPartland
Full Text Available BACKGROUND: Previous research has shown that academic physicians conflicted by funding from the pharmaceutical industry have corrupted evidence based medicine and helped enlarge the market for drugs. Physicians made pharmaceutical-friendly statements, engaged in disease mongering, and signed biased review articles ghost-authored by corporate employees. This paper tested the hypothesis that bias affects review articles regarding rimonabant, an anti-obesity drug that blocks the central cannabinoid receptor. METHODS/PRINCIPAL FINDINGS: A MEDLINE search was performed for rimonabant review articles, limited to articles authored by USA physicians who served as consultants for the company that manufactures rimonabant. Extracted articles were examined for industry-friendly bias, identified by three methods: analysis with a validated instrument for monitoring bias in continuing medical education (CME; analysis for bias defined as statements that ran contrary to external evidence; and a tally of misrepresentations about the endocannabinoid system. Eight review articles were identified, but only three disclosed authors' financial conflicts of interest, despite easily accessible information to the contrary. The Takhar CME bias instrument demonstrated statistically significant bias in all the review articles. Biased statements that were nearly identical reappeared in the articles, including disease mongering, exaggerating rimonabant's efficacy and safety, lack of criticisms regarding rimonabant clinical trials, and speculations about surrogate markers stated as facts. Distinctive and identical misrepresentations regarding the endocannabinoid system also reappeared in articles by different authors. CONCLUSIONS: The findings are characteristic of bias that arises from financial conflicts of interest, and suggestive of ghostwriting by a common author. Resolutions for this scenario are proposed.
Artificial bias typically neglected in comparisons of uncertain atmospheric data
Pitkänen, Mikko R. A.; Mikkonen, Santtu; Lehtinen, Kari E. J.; Arola, Antti
2016-04-01
Researchers in atmospheric sciences frequently disregard data uncertainty in their choice of methods for data analysis and visualisation. Such methods include the widely used standard least squares line fitting in combination with some variations of scatter plots when comparing two different data sets of the same physical quantity. When using these methods, random data uncertainty (eg. measurement uncertainty) causes artificial systematic bias in the comparison between the extreme values of the data sets, which is then often interpreted falsely as a consequence of some true physical phenomenon or instrument misbehavior. This artificial bias is recognized as regression to the mean (RTM), that is a known effect in the field of statistics, but mostly disregarded in atmospheric sciences and not acknowledged at all in the vast majority of publications in our field. All kinds of data comparisons are subject to the bias, as long as uncertainty is present in the data. This work introduces the concept of RTM bias and demonstrates the necessity of considering the RTM effect in comparisons of data with uncertainties. We not only visualize the RTM effect with synthetic data but also use simulations based on real atmospheric data to estimate the magnitude of RTM bias in data comparisons common in our field. Typically, RTM bias is greater when the reference data (often on the x-axis) has greater uncertainty. For example, mid-visible aerosol optical thickness determined using a sun photometer may have a fairly low uncertainty of +-0.01 and, thus the RTM effect is small when using it as reference data. On the other hand UV index measurements with a broadband instrument may have an uncertainty of 10 % and higher, and the bias caused by RTM becomes larger. The bias caused by RTM is typically greatest for the extreme values of the data sets, emphasizing the need to account for RTM bias when comparing and interpreting these cases.
Directory of Open Access Journals (Sweden)
Orlov A. I.
2016-05-01
Full Text Available Fuzzy sets are the special form of objects of nonnumeric nature. Therefore, in the processing of the sample, the elements of which are fuzzy sets, a variety of methods for the analysis of statistical data of any nature can be used - the calculation of the average, non-parametric density estimators, construction of diagnostic rules, etc. We have told about the development of our work on the theory of fuzziness (1975 - 2015. In the first of our work on fuzzy sets (1975, the theory of random sets is regarded as a generalization of the theory of fuzzy sets. In non-fiction series "Mathematics. Cybernetics" (publishing house "Knowledge" in 1980 the first book by a Soviet author fuzzy sets is published - our brochure "Optimization problems and fuzzy variables". This book is essentially a "squeeze" our research of 70-ies, ie, the research on the theory of stability and in particular on the statistics of objects of non-numeric nature, with a bias in the methodology. The book includes the main results of the fuzzy theory and its note to the random set theory, as well as new results (first publication! of statistics of fuzzy sets. On the basis of further experience, you can expect that the theory of fuzzy sets will be more actively applied in organizational and economic modeling of industry management processes. We discuss the concept of the average value of a fuzzy set. We have considered a number of statements of problems of testing statistical hypotheses on fuzzy sets. We have also proposed and justified some algorithms for restore relationships between fuzzy variables; we have given the representation of various variants of fuzzy cluster analysis of data and variables and described some methods of collection and description of fuzzy data
Sources of method bias in social science research and recommendations on how to control it.
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.
2012-01-01
In 1975 John Tukey proposed a multivariate median which is the 'deepest' point in a given data cloud in R^d. Later, in measuring the depth of an arbitrary point z with respect to the data, David Donoho and Miriam Gasko considered hyperplanes through z and determined its 'depth' by the smallest portion of data that are separated by such a hyperplane. Since then, these ideas has proved extremely fruitful. A rich statistical methodology has developed that is based on data depth and, more general...
Measuring statistical evidence using relative belief
Directory of Open Access Journals (Sweden)
Michael Evans
2016-01-01
Full Text Available A fundamental concern of a theory of statistical inference is how one should measure statistical evidence. Certainly the words “statistical evidence,” or perhaps just “evidence,” are much used in statistical contexts. It is fair to say, however, that the precise characterization of this concept is somewhat elusive. Our goal here is to provide a definition of how to measure statistical evidence for any particular statistical problem. Since evidence is what causes beliefs to change, it is proposed to measure evidence by the amount beliefs change from a priori to a posteriori. As such, our definition involves prior beliefs and this raises issues of subjectivity versus objectivity in statistical analyses. This is dealt with through a principle requiring the falsifiability of any ingredients to a statistical analysis. These concerns lead to checking for prior-data conflict and measuring the a priori bias in a prior.
MLE's bias pathology motivates MCMLE
Yatracos, Yannis G.
2013-01-01
Maximum likelihood estimates are often biased. It is shown that this pathology is inherent to the traditional ML estimation method for two or more parameters, thus motivating from a different angle the use of MCMLE.
Magnetic bearings with zero bias
Brown, Gerald V.; Grodsinsky, Carlos M.
1991-01-01
A magnetic bearing operating without a bias field has supported a shaft rotating at speeds up to 12,000 rpm with the usual four power supplies and with only two. A magnetic bearing is commonly operated with a bias current equal to half of the maximum current allowable in its coils. This linearizes the relation between net force and control current and improves the force slewing rate and hence the band width. The steady bias current dissipates power, even when no force is required from the bearing. The power wasted is equal to two-thirds of the power at maximum force output. Examined here is the zero bias idea. The advantages and disadvantages are noted.
Cognitive biases and language universals
Baronchelli, Andrea; Puglisi, Andrea
2013-01-01
Language universals have been longly attributed to an innate Universal Grammar. An alternative explanation states that linguistic universals emerged independently in every language in response to shared cognitive, though non language-specific, biases. A computational model has recently shown how this could be the case, focusing on the paradigmatic example of the universal properties of color naming patterns, and producing results in accurate agreement with the experimental data. Here we investigate thoroughly the role of a cognitive bias in the framework of this model. We study how, and to what extent, the structure of the bias can influence the corresponding linguistic universal patterns. We show also that the cultural history of a group of speakers introduces population-specific constraints that act against the uniforming pressure of the cognitive bias, and we clarify the interplay between these two forces. We believe that our simulations can help to shed light on the possible mechanisms at work in the evol...
Preferences, country bias, and international trade
S. Roy (Santanu); J.M.A. Viaene (Jean-Marie)
1998-01-01
textabstractAnalyzes international trade where consumer preferences exhibit country bias. Why country biases arise; How trade can occur in the presence of country bias; Implication for the pattern of trade and specialization.
Publication Bias in Meta-Analyses of the Efficacy of Psychotherapeutic Interventions for Depression
Niemeyer, Helen; Musch, Jochen; Pietrowsky, Reinhard
2013-01-01
Objective: The aim of this study was to assess whether systematic reviews investigating psychotherapeutic interventions for depression are affected by publication bias. Only homogeneous data sets were included, as heterogeneous data sets can distort statistical tests of publication bias. Method: We applied Begg and Mazumdar's adjusted rank…
On the linearity of tracer bias around voids
Pollina, Giorgia; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro
2016-01-01
The large-scale structure of the universe can only be observed directly via luminous tracers of the underlying distribution of dark matter. However, the clustering statistics of tracers are biased and depend on various properties of the tracers themselves, such as their host-halo mass and formation and assembly history. On very large scales, where density fluctuations are within the linear regime, this tracer bias results in a constant offset in the clustering amplitude, which is known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centered on cosmic voids, depressions of the density field that spatially dominate the universe. We consider three different types of tracers: galaxies, galaxy clusters and AGNs, extracted from the hydrodynamical simulation suite Magneticum Pathfinder. In contrast to common clustering statistics that focus on the auto-correlation of tracers, we find that void-tra...
Greatbatch, Richard; Drews, Annika; Ding, Hui; Latif, Mojib; Park, Wonsun
2016-04-01
The North Atlantic cold bias, associated with a too zonal path of the North Atlantic Current and a missing "northwest corner", is a common problem in coupled climate and forecast models. The bias affects the North Atlantic and European climate mean state, variability and predictability. We investigate the use of a flow field correction to adjust the path of the North Atlantic Current as well as additional corrections to the surface heat and freshwater fluxes. Results using the Kiel Climate Model show that the flow field correction allows a northward flow into the northwest corner, largely eliminating the bias below the surface layer. A surface cold bias remains but can be eliminated by additionally correcting the surface freshwater flux, without adjusting the surface heat flux seen by the ocean model. A model version in which only the surface fluxes of heat and freshwater are corrected continues to exhibit the incorrect path of the North Atlantic Current and a strong subsurface bias. Removing the bias impacts the multi-decadal time scale variability in the model and leads to a better representation of the SST pattern associated with the Atlantic Multidecadal Variability than the uncorrected model.
The estimation method of GPS instrumental biases
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A model of estimating the global positioning system (GPS) instrumental biases and the methods to calculate the relative instrumental biases of satellite and receiver are presented. The calculated results of GPS instrumental biases, the relative instrumental biases of satellite and receiver, and total electron content (TEC) are also shown. Finally, the stability of GPS instrumental biases as well as that of satellite and receiver instrumental biases are evaluated, indicating that they are very stable during a period of two months and a half.
Is there evidence of publication biases in JDM research?
Directory of Open Access Journals (Sweden)
Frank Renkewitz
2011-12-01
Full Text Available It is a long known problem that the preferential publication of statistically significant results (publication bias may lead to incorrect estimates of the true effects being investigated. Even though other research areas (e.g., medicine, biology are aware of the problem, and have identified strong publication biases, researchers in judgment and decision making (JDM largely ignore it. We reanalyzed two current meta-analyses in this area. Both showed evidence of publication biases that may have led to a substantial overestimation of the true effects they investigated. A review of additional JDM meta-analyses shows that most meta-analyses conducted no or insufficient analyses of publication bias. However, given our results and the rareness of non-significant effects in the literature, we suspect that biases occur quite often. These findings suggest that (a conclusions based on meta-analyses without reported tests of publication bias should be interpreted with caution and (b publication policies and standard research practices should be revised to overcome the problem.
Paine, Gregory Harold
1982-03-01
The primary objective of the thesis is to explore the dynamical properties of small nerve networks by means of the methods of statistical mechanics. To this end, a general formalism is developed and applied to elementary groupings of model neurons which are driven by either constant (steady state) or nonconstant (nonsteady state) forces. Neuronal models described by a system of coupled, nonlinear, first-order, ordinary differential equations are considered. A linearized form of the neuronal equations is studied in detail. A Lagrange function corresponding to the linear neural network is constructed which, through a Legendre transformation, provides a constant of motion. By invoking the Maximum-Entropy Principle with the single integral of motion as a constraint, a probability distribution function for the network in a steady state can be obtained. The formalism is implemented for some simple networks driven by a constant force; accordingly, the analysis focuses on a study of fluctuations about the steady state. In particular, a network composed of N noninteracting neurons, termed Free Thinkers, is considered in detail, with a view to interpretation and numerical estimation of the Lagrange multiplier corresponding to the constant of motion. As an archetypical example of a net of interacting neurons, the classical neural oscillator, consisting of two mutually inhibitory neurons, is investigated. It is further shown that in the case of a network driven by a nonconstant force, the Maximum-Entropy Principle can be applied to determine a probability distribution functional describing the network in a nonsteady state. The above examples are reconsidered with nonconstant driving forces which produce small deviations from the steady state. Numerical studies are performed on simplified models of two physical systems: the starfish central nervous system and the mammalian olfactory bulb. Discussions are given as to how statistical neurodynamics can be used to gain a better
An Approach to the Programming of Biased Regression Algorithms.
1978-11-01
Due to the near nonexistence of computer algorithms for calculating estimators and ancillary statistics that are needed for biased regression methodologies, many users of these methodologies are forced to write their own programs. Brute-force coding of such programs can result in a great waste of computer core and computing time, as well as inefficient and inaccurate computing techniques. This article proposes some guides to more efficient programming by taking advantage of mathematical similarities among several of the more popular biased regression estimators.
Publication bias: what is it? How do we measure it? How do we avoid it?
Directory of Open Access Journals (Sweden)
Song F
2013-07-01
Full Text Available Fujian Song, Lee Hooper, Yoon K LokeNorwich Medical School, University of East Anglia, Norwich, UKAbstract: Publication bias occurs when results of published studies are systematically different from results of unpublished studies. The term "dissemination bias" has also been recommended to describe all forms of biases in the research-dissemination process, including outcome-reporting bias, time-lag bias, gray-literature bias, full-publication bias, language bias, citation bias, and media-attention bias. We can measure publication bias by comparing the results of published and unpublished studies addressing the same question. Following up cohorts of studies from inception and comparing publication levels in studies with statistically significant or "positive" results suggested greater odds of formal publication in those with such results, compared to those without. Within reviews, funnel plots and related statistical methods can be used to indicate presence or absence of publication bias, although these can be unreliable in many circumstances. Methods of avoiding publication bias, by identifying and including unpublished outcomes and unpublished studies, are discussed and evaluated. These include searching without limiting by outcome, searching prospective trials registers, searching informal sources, including meeting abstracts and PhD theses, searching regulatory body websites, contacting authors of included studies, and contacting pharmaceutical or medical device companies for further studies. Adding unpublished studies often alters effect sizes, but may not always eliminate publication bias. The compulsory registration of all clinical trials at inception is an important move forward, but it can be difficult for reviewers to access data from unpublished studies located this way. Publication bias may be reduced by journals by publishing high-quality studies regardless of novelty or unexciting results, and by publishing protocols or full
Gender bias in academic recruitment
DEFF Research Database (Denmark)
Abramo, Giovanni; D’Angelo, Ciriaco Andrea; Rosati, Francesco
2016-01-01
It is well known that women are underrepresented in the academic systems of many countries. Gender discrimination is one of the factors that could contribute to this phenomenon. This study considers a recent national academic recruitment campaign in Italy, examining whether women are subject...... to more or less bias than men. The findings show that no gender-related differences occur among the candidates who benefit from positive bias, while among those candidates affected by negative bias, the incidence of women is lower than that of men. Among the factors that determine success in a competition...... for an academic position, the number of the applicant’s career years in the same university as the committee members assumes greater weight for male candidates than for females. Being of the same gender as the committee president is also a factor that assumes greater weight for male applicants. On the other hand...
Anchoring Bias in Online Voting
Yang, Zimo; Zhou, Tao
2012-01-01
Voting online with explicit ratings could largely reflect people's preferences and objects' qualities, but ratings are always irrational, because they may be affected by many unpredictable factors like mood, weather, as well as other people's votes. By analyzing two real systems, this paper reveals a systematic bias embedding in the individual decision-making processes, namely people tend to give a low rating after a low rating, as well as a high rating following a high rating. This so-called \\emph{anchoring bias} is validated via extensive comparisons with null models, and numerically speaking, the extent of bias decays with interval voting number in a logarithmic form. Our findings could be applied in the design of recommender systems and considered as important complementary materials to previous knowledge about anchoring effects on financial trades, performance judgements, auctions, and so on.
Scale-Scale Correlation as Discriminant Among the Biased Galaxy Formation Models
Institute of Scientific and Technical Information of China (English)
FENG Long-Long; XIANG Shou-Ping
2001-01-01
Using the mock galaxy catalogues created from the N-body simulations, various biasing prescriptions for modelling the relative distribution between the galaxies and the underlying dark matter are statistically tested by using scale-scale correlation. We found that the scale-scale correlation is capable of breaking the model degeneracy indicated by the low-order clustering statistics, and could be taken as an effective discriminant among a variety of biasing models. Particularly, comparing with the APM bright galaxy catalogue, we infer that the two parameter Lagrangian biasing model gives the best fit to the observed clustering features.
Unpacking the Evidence of Gender Bias
Fulmer, Connie L.
2010-01-01
The purpose of this study was to investigate gender bias in pre-service principals using the Gender-Leader Implicit Association Test. Analyses of student-learning narratives revealed how students made sense of gender bias (biased or not-biased) and how each reacted to evidence (surprised or not-surprised). Two implications were: (1) the need for…
Without Bias: A Guidebook for Nondiscriminatory Communication.
Pickens, Judy E., Ed.; And Others
This guidebook discusses ways to eliminate various types of discrimination from business communications. Separately authored chapters discuss eliminating racial and ethnic bias; eliminating sexual bias; achieving communication sensitive about handicaps of disabled persons; eliminating bias from visual media; eliminating bias from meetings,…
Measurement Bias Detection through Factor Analysis
Barendse, M. T.; Oort, F. J.; Werner, C. S.; Ligtvoet, R.; Schermelleh-Engel, K.
2012-01-01
Measurement bias is defined as a violation of measurement invariance, which can be investigated through multigroup factor analysis (MGFA), by testing across-group differences in intercepts (uniform bias) and factor loadings (nonuniform bias). Restricted factor analysis (RFA) can also be used to detect measurement bias. To also enable nonuniform…
The Truth and Bias Model of Judgment
West, Tessa V.; Kenny, David A.
2011-01-01
We present a new model for the general study of how the truth and biases affect human judgment. In the truth and bias model, judgments about the world are pulled by 2 primary forces, the truth force and the bias force, and these 2 forces are interrelated. The truth and bias model differentiates force and value, where the force is the strength of…
The Threshold of Embedded M Collider Bias and Confounding Bias
Kelcey, Benjamin; Carlisle, Joanne
2011-01-01
Of particular import to this study, is collider bias originating from stratification on retreatment variables forming an embedded M or bowtie structural design. That is, rather than assume an M structural design which suggests that "X" is a collider but not a confounder, the authors adopt what they consider to be a more reasonable…
Information filtering via biased heat conduction
Liu, Jian-Guo; Guo, Qiang
2011-01-01
Heat conduction process has recently found its application in personalized recommendation [T. Zhou \\emph{et al.}, PNAS 107, 4511 (2010)], which is of high diversity but low accuracy. By decreasing the temperatures of small-degree objects, we present an improved algorithm, called biased heat conduction (BHC), which could simultaneously enhance the accuracy and diversity. Extensive experimental analyses demonstrate that the accuracy on MovieLens, Netflix and Delicious datasets could be improved by 43.5%, 55.4% and 19.2% compared with the standard heat conduction algorithm, and the diversity is also increased or approximately unchanged. Further statistical analyses suggest that the present algorithm could simultaneously identify users' mainstream and special tastes, resulting in better performance than the standard heat conduction algorithm. This work provides a creditable way for highly efficient information filtering.
Information filtering via biased heat conduction
Liu, Jian-Guo; Zhou, Tao; Guo, Qiang
2011-09-01
The process of heat conduction has recently found application in personalized recommendation [Zhou , Proc. Natl. Acad. Sci. USA PNASA60027-842410.1073/pnas.1000488107107, 4511 (2010)], which is of high diversity but low accuracy. By decreasing the temperatures of small-degree objects, we present an improved algorithm, called biased heat conduction, which could simultaneously enhance the accuracy and diversity. Extensive experimental analyses demonstrate that the accuracy on MovieLens, Netflix, and Delicious datasets could be improved by 43.5%, 55.4% and 19.2%, respectively, compared with the standard heat conduction algorithm and also the diversity is increased or approximately unchanged. Further statistical analyses suggest that the present algorithm could simultaneously identify users' mainstream and special tastes, resulting in better performance than the standard heat conduction algorithm. This work provides a creditable way for highly efficient information filtering.
Excess success for three related papers on racial bias.
Francis, Gregory
2015-01-01
Three related articles reported that racial bias altered perceptual experience and influenced decision-making. These findings have been applied to training programs for law enforcement, and elsewhere, to mitigate racial bias. However, a statistical analysis of each of the three articles finds that the reported experimental results should be rare, even if the theoretical ideas were correct. The analysis estimates that the probability of the reported experimental success for the articles is 0.003, 0.048, and 0.070, respectively. These low probabilities suggest that similar future work is unlikely to produce as successful outcomes and indicates that readers should be skeptical about the validity of the reported findings and their theoretical implications. The reported findings should not be used to guide policies related to racial bias, and new experimental work is needed to judge the merit of the theoretical ideas.
Excess success for three related papers on racial bias
Directory of Open Access Journals (Sweden)
Gregory eFrancis
2015-05-01
Full Text Available Three related articles reported that racial bias altered perceptual experience and influenced decision-making. These findings have been applied to training programs for law enforcement, and elsewhere, to mitigate racial bias. However, a statistical analysis of each of the three articles finds that the reported experimental results should be rare, even if the theoretical ideas were correct. The analysis estimates that the probability of the reported experimental success for the articles is 0.003, 0.048, and 0.070, respectively. These low probabilities suggest that similar future work is unlikely to produce as successful outcomes and indicates that readers should be skeptical about the validity of the reported findings and their theoretical implications. The reported findings should not be used to guide policies related to racial bias, and new experimental work is needed to judge the merit of the theoretical ideas.
Saito, Shun; Vlah, Zvonimir; Seljak, Uroš; Okumura, Teppei; McDonald, Patrick
2014-01-01
Understanding the relation between underlying matter distribution and biased tracers such as galaxy or dark matter halo is essential to extract cosmological information from ongoing or future galaxy redshift surveys. At sufficiently large scales such as the BAO scale, a standard approach for the bias problem on the basis of the perturbation theory (PT) is to assume the `local bias' model in which the density field of biased tracers is deterministically expanded in terms of matter density field at the same position. The higher-order bias parameters are then determined by combining the power spectrum with higher-order statistics such as the bispectrum. As is pointed out by recent studies, however, nonlinear gravitational evolution naturally induces nonlocal bias terms even if initially starting only with purely local bias. As a matter of fact, previous works showed that the second-order nonlocal bias term, which corresponds to the gravitational tidal field, is important to explain the characteristic scale-depen...
Bias in Dynamic Monte Carlo Alpha Calculations
Energy Technology Data Exchange (ETDEWEB)
Sweezy, Jeremy Ed [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nolen, Steven Douglas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Adams, Terry R. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-02-06
A 1/N bias in the estimate of the neutron time-constant (commonly denoted as α) has been seen in dynamic neutronic calculations performed with MCATK. In this paper we show that the bias is most likely caused by taking the logarithm of a stochastic quantity. We also investigate the known bias due to the particle population control method used in MCATK. We conclude that this bias due to the particle population control method is negligible compared to other sources of bias.
Measurement Bias in Multilevel Data
Jak, Suzanne; Oort, Frans J.; Dolan, Conor V.
2014-01-01
Measurement bias can be detected using structural equation modeling (SEM), by testing measurement invariance with multigroup factor analysis (Jöreskog, 1971;Meredith, 1993;Sörbom, 1974) MIMIC modeling (Muthén, 1989) or restricted factor analysis (Oort, 1992,1998). In educational research, data often
Measurement bias in multilevel data
Jak, S.; Oort, F.J.; Dolan, C.V.
2014-01-01
Measurement bias can be detected using structural equation modeling (SEM), by testing measurement invariance with multigroup factor analysis (Jöreskog, 1971;Meredith, 1993;Sörbom, 1974) MIMIC modeling (Muthén, 1989) or restricted factor analysis (Oort, 1992,1998). In educational research, data often
Perception bias in route choice
Vreeswijk, J.D.; Thomas, T.; Berkum, van E.C.; Arem, van B.
2014-01-01
Travel time is probably one of the most studied attributes in route choice. Recently, perception of travel time received more attention as several studies have shown its importance in explaining route choice behavior. In particular, travel time estimates by travelers appear to be biased against non-
Attentional bias in math anxiety
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. PMID:26528208
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.
Sex Bias in Counseling Materials
Harway, Michele
1977-01-01
This article reviews findings of bias in counseling materials and presents results of three original studies. Indications are that textbooks used by practitioners present the sexes in stereotypical fashion, and a greater proportion of college catalog context is devoted to men than to women. (Author)
Ratio Bias and Policy Preferences
DEFF Research Database (Denmark)
Pedersen, Rasmus Tue
2016-01-01
Numbers permeate modern political communication. While current scholarship on framing effects has focused on the persuasive effects of words and arguments, this article shows that framing of numbers can also substantially affect policy preferences. Such effects are caused by ratio bias, which is ...
Attentional bias in math anxiety.
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.
Addressing selection bias in dental health services research.
Lee, J Y; Rozier, R G; Norton, E C; Vann, W F
2005-10-01
When randomization is not possible, researchers must control for non-random assignment to experimental groups. One technique for statistical adjustment for non-random assignment is through the use of a two-stage analytical technique. The purpose of this study was to demonstrate the use of this technique to control for selection bias in examining the effects of the The Supplemental Program for Women, Infants, and Children's (WIC) on dental visits. From 5 data sources, an analysis file was constructed for 49,512 children ages 1-5 years. The two-stage technique was used to control for selection bias in WIC participation, the potentially endogenous variable. Specification tests showed that WIC participation was not random and that selection bias was present. The effects of the WIC on dental use differed by 36% after adjustment for selection bias by means of the two-stage technique. This technique can be used to control for potential selection bias in dental research when randomization is not possible.
Bias Adjusted Precipitation Threat Scores
Directory of Open Access Journals (Sweden)
F. Mesinger
2008-04-01
Full Text Available Among the wide variety of performance measures available for the assessment of skill of deterministic precipitation forecasts, the equitable threat score (ETS might well be the one used most frequently. It is typically used in conjunction with the bias score. However, apart from its mathematical definition the meaning of the ETS is not clear. It has been pointed out (Mason, 1989; Hamill, 1999 that forecasts with a larger bias tend to have a higher ETS. Even so, the present author has not seen this having been accounted for in any of numerous papers that in recent years have used the ETS along with bias "as a measure of forecast accuracy".
A method to adjust the threat score (TS or the ETS so as to arrive at their values that correspond to unit bias in order to show the model's or forecaster's accuracy in extit{placing} precipitation has been proposed earlier by the present author (Mesinger and Brill, the so-called dH/dF method. A serious deficiency however has since been noted with the dH/dF method in that the hypothetical function that it arrives at to interpolate or extrapolate the observed value of hits to unit bias can have values of hits greater than forecast when the forecast area tends to zero. Another method is proposed here based on the assumption that the increase in hits per unit increase in false alarms is proportional to the yet unhit area. This new method removes the deficiency of the dH/dF method. Examples of its performance for 12 months of forecasts by three NCEP operational models are given.
Statistical Methods for Material Characterization and Qualification
Energy Technology Data Exchange (ETDEWEB)
Kercher, A.K.
2005-04-01
This document describes a suite of statistical methods that can be used to infer lot parameters from the data obtained from inspection/testing of random samples taken from that lot. Some of these methods will be needed to perform the statistical acceptance tests required by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program. Special focus has been placed on proper interpretation of acceptance criteria and unambiguous methods of reporting the statistical results. In addition, modified statistical methods are described that can provide valuable measures of quality for different lots of material. This document has been written for use as a reference and a guide for performing these statistical calculations. Examples of each method are provided. Uncertainty analysis (e.g., measurement uncertainty due to instrumental bias) is not included in this document, but should be considered when reporting statistical results.
Statistical methods for material characterization and qualification
Energy Technology Data Exchange (ETDEWEB)
Hunn, John D [ORNL; Kercher, Andrew K [ORNL
2005-01-01
This document describes a suite of statistical methods that can be used to infer lot parameters from the data obtained from inspection/testing of random samples taken from that lot. Some of these methods will be needed to perform the statistical acceptance tests required by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program. Special focus has been placed on proper interpretation of acceptance criteria and unambiguous methods of reporting the statistical results. In addition, modified statistical methods are described that can provide valuable measures of quality for different lots of material. This document has been written for use as a reference and a guide for performing these statistical calculations. Examples of each method are provided. Uncertainty analysis (e.g., measurement uncertainty due to instrumental bias) is not included in this document, but should be considered when reporting statistical results.
Systematic Bias in Cosmic Shear: Beyond the Fisher Matrix
Amara, Adam
2007-01-01
We describe a method for computing the biases that systematic signals introduce in parameter estimation using a simple extension of the Fisher matrix formalism. This allows us to calculate the offset of the best fit parameters relative to the fiducial model, in addition to the usual statistical error ellipse. As an application, we study the impact that residual systematics in tomographic weak lensing measurements. In particular we explore three different types of shape measurement systematics: (i) additive systematic with no redshift evolution; (ii) additive systematic with redshift evolution; and (iii) multiplicative systematic. In each case, we consider a wide range of scale dependence and redshift evolution of the systematics signal. For a future DUNE-like full sky survey, we find that, for cases with mild redshift evolution, the variance of the additive systematic signal should be kept below 10^-7 to ensure biases on cosmological parameters that are sub-dominant to the statistical errors. For the multipli...
Thompson, Michael; Owen, Linda; Wilkinson, Kate; Wood, Roger; Damant, Andrew
2004-12-01
Bias between the Dumas and the Kjeldahl methods for the determination of protein nitrogen in food was studied by conducting an interlaboratory study involving 40 laboratories and 20 different test materials. Biases were found to be small and statistically significant only for the chicken test materials, where a bias of 0.020±0.004% m/m was detected.
Information environment, behavioral biases, and home bias in analysts’ recommendations
DEFF Research Database (Denmark)
Farooq, Omar; Taouss, Mohammed
2012-01-01
’ recommendations. Using a large data of analysts’ recommendations from Asian emerging markets, we show that local analysts issue more optimistic recommendations than their foreign counterparts. However, optimism difference between the two groups is greater for firms with poor information environment. Our results......Can information environment of a firm explain home bias in analysts’ recommendations? Can the extent of agency problems explain optimism difference between foreign and local analysts? This paper answers these questions by documenting the effect of information environment on home bias in analysts...... show that optimism difference between the two groups is more than twice as much in firms with poor information environment than in firms with better information environment. We argue that poor information environment pose greater information asymmetries to foreign analysts regarding local firms...
Types of Research Bias Encountered in IR.
Gabr, Ahmed; Kallini, Joseph Ralph; Desai, Kush; Hickey, Ryan; Thornburg, Bartley; Kulik, Laura; Lewandowski, Robert J; Salem, Riad
2016-04-01
Bias is a systemic error in studies that leads to inaccurate deductions. Relevant biases in the field of IR and interventional oncology were identified after reviewing articles published in the Journal of Vascular and Interventional Radiology and CardioVascular and Interventional Radiology. Biases cited in these articles were divided into three categories: preinterventional (health care access, participation, referral, and sample biases), periinterventional (contamination, investigator, and operator biases), and postinterventional (guarantee-time, lead time, loss to follow-up, recall, and reporting biases).
... Room Employment Feedback Contact Select Page Childhood Cancer Statistics Home > Cancer Resources > Childhood Cancer Statistics Childhood Cancer Statistics – Graphs and Infographics Number of Diagnoses Incidence Rates ...
Biased estimators on Quotient spaces
Miolane, Nina; Pennec, Xavier
2015-01-01
International audience; Usual statistics are defined, studied and implemented on Euclidean spaces. But what about statistics on other mathematical spaces, like manifolds with additional properties: Lie groups, Quotient spaces, Stratified spaces etc. How can we describe the interaction between statistics and geometry? The structure of Quotient space in particular is widely used to model data, for example every time one deals with shape data. These can be shapes of constellations in Astronomy, ...
Opinion Dynamics with Confirmation Bias
Allahverdyan, A E
2014-01-01
Background: Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science. Methodology/Principal Findings: We formulate a (non-Bayesian) model for revising subjective probabilistic opinion of a confirmationally-biased agent in the light of a persuasive opinion. The revision rule ensures that the agent does not react to persuasion that is either far from his current opinion or coincides with it. We demonstrate that the model accounts for the basic phenomenology of the social judgment theory, and allows to study various phenomena such as cognitive dissonance and boomerang effect. The model also displays the order of presentation effect|when consecutively exposed to two opinions, the preferenc...
Are temperature reconstructions regionally biased?
Bothe, O
2012-01-01
Are temperature reconstructions possibly biased due to regionally differing density of utilized proxy-networks? This question is assessed utilizing a simple process-based forward model of tree growth in the virtual reality of two simulations of the climate of the last millennium with different amplitude of solar forcing variations. The pseudo-tree ring series cluster in high latitudes of the northern hemisphere and east Asia. Only weak biases are found for the full network. However, for a strong solar forcing amplitude the high latitudes indicate a warmer first half of the last millennium while mid-latitudes and Asia were slightly colder than the extratropical hemispheric average. Reconstruction skill is weak or non-existent for two simple reconstruction schemes, and comparison of virtual reality target and reconstructions reveals strong deficiencies. The temporal resolution of the proxies has an influence on the reconstruction task and results are sensitive to the construction of the proxy-network. Existing ...
Mindfulness reduces the correspondence bias.
Hopthrow, Tim; Hooper, Nic; Mahmood, Lynsey; Meier, Brian P; Weger, Ulrich
2017-03-01
The correspondence bias (CB) refers to the idea that people sometimes give undue weight to dispositional rather than situational factors when explaining behaviours and attitudes. Three experiments examined whether mindfulness, a non-judgmental focus on the present moment, could reduce the CB. Participants engaged in a brief mindfulness exercise (the raisin task), a control task, or an attention to detail task before completing a typical CB measure involving an attitude-attribution paradigm. The results indicated that participants in the mindfulness condition experienced a significant reduction in the CB compared to participants in the control or attention to detail conditions. These results suggest that mindfulness training can play a unique role in reducing social biases related to person perception.
Belief bias and relational reasoning.
Roberts, Maxwell J; Sykes, Elizabeth D A
2003-01-01
When people evaluate categorical syllogisms, they tend to reject unbelievable conclusions and accept believable ones irrespective of their validity. Typically, this effect is particularly marked for invalid conclusions that are possible, but do not necessarily follow, given the premises. However, smaller believability effects can also be detected for other types of conclusion. Three experiments are reported here, in which an attempt was made to determine whether belief bias effects can manifest themselves on the relational inference task. Subjects evaluated the validity of conclusions such as William the Conqueror was king after the Pyramids were built (temporal task) or Manchester is north of Bournemouth (spatial task) with respect to their premises. All of the major findings for equivalent categorical syllogism tasks were replicated. However, the overall size of the main effect of believability appears to be related to task presentation, a phenomenon not previously identified for categorical syllogisms and which current theories of belief bias have difficulty explaining.
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Competition and Commercial Media Bias
A. Blasco; F. Sobbrio
2011-01-01
This paper reviews the empirical evidence on commercial media bias (i.e., advertisers influence over media accuracy) and then introduces a simple model to summarize the main elements of the theoretical literature. The analysis provides three main policy insights for media regulators: i) Media regulators should target their monitoring efforts towards news contents upon which advertisers are likely to share similar preferences; ii) In advertising industries characterized by high correlation in ...
BEHAVIORAL BIASES IN TRADING SECURITIES
Directory of Open Access Journals (Sweden)
Turcan Ciprian Sebastian
2010-12-01
Full Text Available The main thesis of this paper represents the importance and the effects that human behavior has over capital markets. It is important to see the link between the asset valuation and investor sentiment that motivate to pay for an asset a certain prices over/below the intrinsic value. The main behavioral aspects discussed are emotional factors such as: fear of regret, overconfidence, perseverance, loss aversion ,heuristic biases, misinformation and thinking errors, herding and their consequences.
Measuring bias from unbiased observable
Lee, Seokcheon
2014-01-01
Since Kaiser introduced galaxies as a biased tracer of the underlying total mass field, the linear galaxies bias, b(z) appears ubiquitously both in theoretical calculations and in observational measurements related to galaxy surveys. However, the generic approaches to the galaxy density is a non-local and stochastic function of the underlying dark matter density and it becomes difficult to make the analytic form of b(z). Due to this fact, b(z) is known as a nuisance parameter and the effort has been made to measure bias free observable quantities. We provide the exact and analytic function of b(z) which also can be measured from galaxy surveys using the redshift space distortions parameters, more accurately unbiased observable \\beta \\sigma_{\\rm{gal}} = f \\sigma_8. We also introduce approximate solutions for b(z) for different gravity theories. One can generalize these approximate solutions to be exact when one solves the exact evolutions for the dark matter density fluctuation of given gravity theories. These...
Response bias in plaintiffs' histories.
Lees-Haley, P R; Williams, C W; Zasler, N D; Marguilies, S; English, L T; Stevens, K B
1997-11-01
This study investigated response bias in self-reported history of factors relevant to the assessment of traumatic brain injury, toxic brain injury and related emotional distress. Response bias refers to systematic error in self-report data. A total of 446 subjects (comprising 131 litigating and 315 non-litigating adults from five locations in the United States) completed a symptom questionnaire. Data were obtained from university faculty and students, from patients in clinics specializing in physiatry neurology, and family medicine, and from plaintiffs undergoing forensic neuropsychological evaluations. Comparisons were made for litigant and non litigant ratings of their past and current cognitive and emotional functioning, including life in general, ability to concentrate, memory, depression, anxiety, alcohol, drugs, ability to work or attend school, irritability, headaches, confusion, self-esteem, and fatigue. Although there is no basis for hypothesizing plaintiffs to be healthier than the general population, plaintiffs rated their pre-injury functioning superior to non-plaintiffs. These findings suggest that response biases need to be taken into account by forensic examiners when relying on litigants' self-reports of pre-injury status.
The Empirical Nature and Statistical Treatment of Missing Data
Tannenbaum, Christyn E.
2009-01-01
Introduction. Missing data is a common problem in research and can produce severely misleading analyses, including biased estimates of statistical parameters, and erroneous conclusions. In its 1999 report, the APA Task Force on Statistical Inference encouraged authors to report complications such as missing data and discouraged the use of…
Fundamental statistical limitations of future dark matter direct detection experiments
Strege, C.; Trotta, F.; Bertone, G.; Peter, A.H.G.; Scott, P.
2012-01-01
We discuss irreducible statistical limitations of future ton-scale dark matter direct detection experiments. We focus in particular on the coverage of confidence intervals, which quantifies the reliability of the statistical method used to reconstruct the dark matter parameters and the bias of the r
... PSN PSEN GRAFT Contact Us News Plastic Surgery Statistics Plastic surgery procedural statistics from the American Society of Plastic Surgeons. Statistics by Year Print 2016 Plastic Surgery Statistics 2015 ...
... Standards Act and Program MQSA Insights MQSA National Statistics Share Tweet Linkedin Pin it More sharing options ... but should level off with time. Archived Scorecard Statistics 2017 Scorecard Statistics 2016 Scorecard Statistics (Archived) 2015 ...
Bias-correction in vector autoregressive models
DEFF Research Database (Denmark)
Engsted, Tom; Pedersen, Thomas Quistgaard
2014-01-01
We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study......, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find...
A Pharmacological Primer of Biased Agonism
Andresen, Bradley T.
2011-01-01
Biased agonism is one of the fastest growing topics in G protein-coupled receptor pharmacology; moreover, biased agonists are used in the clinic today: carvedilol (Coreg®) is a biased agonist of beta-adrenergic receptors. However, there is a general lack of understanding of biased agonism when compared to traditional pharmacological terminology. Therefore, this review is designed to provide a basic introduction to classical pharmacology as well as G protein-coupled receptor signal transductio...
Calamaras, Martha R; Tully, Erin C; Tone, Erin B; Price, Matthew; Anderson, Page L
2015-08-01
Reductions in judgmental biases concerning the cost and probability of negative social events are presumed to be mechanisms of treatment for SAD. Methodological limitations of extant studies, however, leave open the possibility that, instead of causing symptom relief, reductions in judgmental biases are correlates or consequences of it. The present study evaluated changes in judgmental biases as mechanisms explaining the efficacy of CBT for SAD. Participants were 86 individuals who met DSM-IV-TR criteria for a primary diagnosis of SAD, participated in one of two treatment outcome studies of CBT for SAD, and completed measures of judgmental (i.e., cost and probability) biases and social anxiety at pre-, mid-, and posttreatment. Treated participants had significantly greater reductions in judgmental biases than not-treated participants; pre-to-post changes in cost and probability biases statistically mediated treatment outcome; and probability bias at midtreatment was a significant predictor of treatment outcome, even when modeled with a plausible rival mediator, working alliance. Contrary to hypotheses, cost bias at midtreatment was not a significant predictor of treatment outcome. Results suggest that reduction in probability bias is a mechanism by which CBT for SAD exerts its effects.
Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias.
Directory of Open Access Journals (Sweden)
Thomas Pfeiffer
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
Attentional bias predicts heroin relapse following treatment
M.A.E. Marissen; I.H.A. Franken; A.J. Waters; P. Blanken; W. van den Brink; V.M. Hendriks
2006-01-01
Aims Previous studies have shown that abstinent heroin addicts exhibit an attentional bias to heroin-related stimuli. It has been suggested that attentional bias may represent a vulnerability to relapse into drug use. In the present study, the predictive value of pre-treatment attentional bias on re
Biased managers, organizational design, and incentive provision
Moreira, Humberto Ataíde; Costa, Cristiano Machado; Ferreira, Daniel Bernardo Soares
2004-01-01
We model the tradeoff between the balance and the strength of incentives implicit in the choice between hierarchical and matrix organizational structures. We show that managerial biases determine which structure is optimal: hierarchical forms are preferred when biases are low, while matrix structures are preferred when biases are high.
Using Newspapers to Study Media Bias.
Kirman, Joseph M.
1992-01-01
Suggests that students can learn to recognize media bias by studying media reports of current events or historical topics. Describes a study unit using media coverage of the second anniversary of the Palestinian uprising against Israel. Discusses lesson objectives, planning, defining bias teaching procedures, and criteria for determining bias. (DK)
Culturally Biased Assumptions in Counseling Psychology
Pedersen, Paul B.
2003-01-01
Eight clusters of culturally biased assumptions are identified for further discussion from Leong and Ponterotto's (2003) article. The presence of cultural bias demonstrates that cultural bias is so robust and pervasive that is permeates the profession of counseling psychology, even including those articles that effectively attack cultural bias…
A Review of Studies on Media Bias at Home
Institute of Scientific and Technical Information of China (English)
辛一丹
2015-01-01
Bias is widely existed nowadays.Domestic scholars have done a lot of research on the bias,especially the media bias.They studied the media bias from different perspectives,such as the bias on China image,the bias of a certain media FOX,the bias on the venerable group,the bias on women and so on.The author plans to give a review of the studies on media bias at home in this paper.
A Review of Studies on Media Bias at Home
Institute of Scientific and Technical Information of China (English)
辛一丹
2015-01-01
Bias is widely existed nowadays. Domestic scholars have done a lot of research on the bias, especially the media bias. They studied the media bias from different perspectives, such as the bias on China image,the bias of a certain media FOX, the bias on the venerable group, the bias on women and so on. The author plans to give a review of the studies on media bias at home in this paper.
DiPonio, Joseph M.
2010-01-01
The primary object of this study was to determine whether racial and/or gender bias were evidenced in the use of the ICIS-Principal. Specifically, will the use of the ICIS-Principal result in biased scores at a statistically significant level when rating current practicing administrators of varying gender and race. The study involved simulated…
Andrich, David; Marais, Ida; Humphry, Stephen Mark
2016-01-01
Recent research has shown how the statistical bias in Rasch model difficulty estimates induced by guessing in multiple-choice items can be eliminated. Using vertical scaling of a high-profile national reading test, it is shown that the dominant effect of removing such bias is a nonlinear change in the unit of scale across the continuum. The…
Less than meets the eye: reappraising the clinical relevance of attentional bias in addiction.
Christiansen, Paul; Schoenmakers, Tim M; Field, Matt
2015-05-01
Recent years have seen an explosion of interest in attentional bias in addiction, particularly its clinical relevance. Specifically, numerous articles claimed to demonstrate either that (1) attentional bias measured in treatment settings could predict subsequent relapse to substance use, or (2) direct modification of attentional bias reduced substance use and improved treatment outcomes. In this paper, we critically evaluate empirical studies that investigated these issues. We show that the evidence regarding both of these claims is decidedly mixed, and that many of the studies that appear to yield positive findings have serious methodological and statistical limitations. We contend that the available literature suggests that attentional bias for drug cues fluctuates within individuals because it is an output of the underlying motivational state at that moment in time, but there is no convincing evidence that it exerts a causal influence on substance use. Future research should make use of experience sampling methodology to characterise the clinical significance of fluctuations in attentional bias over time.
Introducing Decorated HODs: modeling assembly bias in the galaxy-halo connection
Hearin, Andrew P; Bosch, Frank C van den; Campbell, Duncan; Tollerud, Erik
2015-01-01
The connection between galaxies and dark matter halos is often inferred from data using probabilistic models, such as the Halo Occupation Distribution (HOD). Conventional HOD formulations assume that only halo mass governs the galaxy-halo connection. Violations of this assumption, known as galaxy assembly bias, threaten the HOD program. We introduce decorated HODs, a new, flexible class of models designed to account for assembly bias. Decorated HODs minimally expand the parameter space and maximize the independence between traditional and novel HOD parameters. We use decorated HODs to quantify the influence of assembly bias on clustering and lensing statistics. For SDSS-like samples, the impact of assembly bias on galaxy clustering can be as large as a factor of two on r ~ 200 kpc scales and ~15% in the linear regime. Assembly bias can either enhance or diminish clustering on large scales, but generally increases clustering on scales r <~ 1 Mpc. We performed our calculations with Halotools, an open-source,...
Bias in Peripheral Depression Biomarkers
DEFF Research Database (Denmark)
Carvalho, André F; Köhler, Cristiano A; Brunoni, André R
2016-01-01
BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...... sizes has been conducted. METHODS: Here, we performed a comprehensive review of meta-analyses of peripheral nongenetic biomarkers that could discriminate individuals with MDD from nondepressed controls. PubMed/MEDLINE, EMBASE, and PsycINFO databases were searched through April 10, 2015. RESULTS: From 15...
MODIS/Terra 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands V006
National Aeronautics and Space Administration — MODIS 8-day clear-sky radiance bias (observed - calculated) statistics are provided for 1Deg latitudinal zones and selected thermal bands. Separation by day and...
MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands V006
National Aeronautics and Space Administration — MODIS 8-day clear-sky radiance bias (observed - calculated) statistics are provided for 1Deg latitudinal zones and selected thermal bands. Separation by day and...
Predict! Teaching Statistics Using Informational Statistical Inference
Makar, Katie
2013-01-01
Statistics is one of the most widely used topics for everyday life in the school mathematics curriculum. Unfortunately, the statistics taught in schools focuses on calculations and procedures before students have a chance to see it as a useful and powerful tool. Researchers have found that a dominant view of statistics is as an assortment of tools…
Squeezing the halo bispectrum: a test of bias models
Dizgah, Azadeh Moradinezhad; Noreña, Jorge; Biagetti, Matteo; Desjacques, Vincent
2015-01-01
We study the halo-matter cross bispectrum in the presence of primordial non-Gaussianity of the local type. We restrict ourselves to the squeezed limit, for which the calculation are straightforward, and perform the measurements in the initial conditions of N-body simulations, to mitigate the contamination induced by nonlinear gravitational evolution. Interestingly, the halo-matter cross bispectrum is not trivial even in this simple limit as it is strongly sensitive to the scale-dependence of the quadratic and third-order halo bias. Therefore, it can be used to test biasing prescriptions. We consider three different prescription for halo clustering: excursion set peaks (ESP), local bias and a model in which the halo bias parameters are explicitly derived from a peak-background split. In all cases, the model parameters are fully constrained with statistics other than the cross bispectrum. We measure the cross bispectrum involving one halo fluctuation field and two mass overdensity fields for various halo masses...
A Biased Review of Sociophysics
Stauffer, Dietrich
2012-01-01
Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.
A Biased Review of Sociophysics
Stauffer, Dietrich
2013-04-01
Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.
Measuring the effects of publication bias in political science
Directory of Open Access Journals (Sweden)
Justin Esarey
2016-09-01
Full Text Available Prior research finds that statistically significant results are overrepresented in scientific publications. If significant results are consistently favored in the review process, published results could systematically overstate the magnitude of their findings even under ideal conditions. In this paper, we measure the impact of this publication bias on political science using a new data set of published quantitative results. Although any measurement of publication bias depends on the prior distribution of empirical relationships, we determine that published estimates in political science are on average substantially larger than their true value under a variety of reasonable choices for this prior. We also find that many published estimates have a false positive probability substantially greater than the conventional α = 0.05 threshold for statistical significance if the prior probability of a null relationship exceeds 50%. Finally, although the proportion of published false positives would be reduced if significance tests used a smaller α, this change would not solve the problem of upward bias in the magnitude of published results.
Selecting, weeding, and weighting biased climate model ensembles
Jackson, C. S.; Picton, J.; Huerta, G.; Nosedal Sanchez, A.
2012-12-01
In the Bayesian formulation, the "log-likelihood" is a test statistic for selecting, weeding, or weighting climate model ensembles with observational data. This statistic has the potential to synthesize the physical and data constraints on quantities of interest. One of the thorny issues for formulating the log-likelihood is how one should account for biases. While in the past we have included a generic discrepancy term, not all biases affect predictions of quantities of interest. We make use of a 165-member ensemble CAM3.1/slab ocean climate models with different parameter settings to think through the issues that are involved with predicting each model's sensitivity to greenhouse gas forcing given what can be observed from the base state. In particular we use multivariate empirical orthogonal functions to decompose the differences that exist among this ensemble to discover what fields and regions matter to the model's sensitivity. We find that the differences that matter are a small fraction of the total discrepancy. Moreover, weighting members of the ensemble using this knowledge does a relatively poor job of adjusting the ensemble mean toward the known answer. This points out the shortcomings of using weights to correct for biases in climate model ensembles created by a selection process that does not emphasize the priorities of your log-likelihood.
Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data
DEFF Research Database (Denmark)
Greve, Douglas N; Svarer, Claus; Fisher, Patrick M;
2014-01-01
-based smoothing resulted in dramatically less bias and the least variance of the methods tested for smoothing levels 5mm and higher. When used in combination with PVC, surface-based smoothing minimized the bias without significantly increasing the variance. Surface-based smoothing resulted in 2-4 times less...... intersubject variance than when volume smoothing was used. This translates into more than 4 times fewer subjects needed in a group analysis to achieve similarly powered statistical tests. Surface-based smoothing has less bias and variance because it respects cortical geometry by smoothing the PET data only...
[The National Danish Survey of Patient Experiences has a small positive bias].
Rosenstjerne Andersen, Angelo; Fuglsang, Marie; Kyed, Daisy
2012-10-01
The response rate in The National Danish Survey of Patient Experiences in 2009 was 54%. In order to evaluate bias due to non-responders, The Unit of Patient-perceived Quality merged survey data and data on patient background from Statistics Denmark. The relationships between the responding patients' background and their answers to six questions in the survey questionnaire are estimated with logistic regression analysis and subsequently used for predicting the answers of the non-responders. Results indicate a small positive bias in four of the questions and no bias in the remaining two.
Redshift data and statistical inference
Newman, William I.; Haynes, Martha P.; Terzian, Yervant
1994-01-01
Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.
Preferential Biases for Texts That Include Neuroscientific Jargon.
Tabacchi, Marco E; Cardaci, Maurizio
2016-06-01
The results of an experiment of preferential biases for texts that include neuroscientific jargon are presented. Such preferential bias has been reported even when the presented jargon is meaningless. In a variation of the well-known Weisberg et al. experiment, a group of undergraduate students (N = 150; females 48%, males 52%, other 0%; M age = 22.4 year, SD = 2.6) chose between two possible explanations for a psychological phenomenon: a correct explanation or a circular restatement of facts. Unrelated neuroscientific terms were added to one of the explanations. Participants were asked to choose the correct explanation. There was a statistically significant preference for the explanation without neuroscientific terms. These findings differ from Weisberg et al.'s experiment and a number of others. The implications of this discrepancy are discussed.
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.
Cognitive advantage in bilingualism: an example of publication bias?
de Bruin, Angela; Treccani, Barbara; Della Sala, Sergio
2015-01-01
It is a widely held belief that bilinguals have an advantage over monolinguals in executive-control tasks, but is this what all studies actually demonstrate? The idea of a bilingual advantage may result from a publication bias favoring studies with positive results over studies with null or negative effects. To test this hypothesis, we looked at conference abstracts from 1999 to 2012 on the topic of bilingualism and executive control. We then determined which of the studies they reported were subsequently published. Studies with results fully supporting the bilingual-advantage theory were most likely to be published, followed by studies with mixed results. Studies challenging the bilingual advantage were published the least. This discrepancy was not due to differences in sample size, tests used, or statistical power. A test for funnel-plot asymmetry provided further evidence for the existence of a publication bias.
Weak Lensing Peak Finding: Estimators, Filters, and Biases
Schmidt, Fabian
2010-01-01
Large catalogs of shear-selected peaks have recently become a reality. In order to properly interpret the abundance and properties of these peaks, it is necessary to take into account the effects of the clustering of source galaxies, among themselves and with the lens. In addition, the preferred selection of lensed galaxies in a flux- and size-limited sample leads to fluctuations in the apparent source density which correlate with the lensing field (lensing bias). In this paper, we investigate these issues for two different choices of shear estimators which are commonly in use today: globally-normalized and locally-normalized estimators. While in principle equivalent, in practice these estimators respond differently to systematic effects such as lensing bias and cluster member dilution. Furthermore, we find that which estimator is statistically superior depends on the specific shape of the filter employed for peak finding; suboptimal choices of the estimator+filter combination can result in a suppression of t...
Observations and Models of Galaxy Assembly Bias
Campbell, Duncan A.
2017-01-01
The assembly history of dark matter haloes imparts various correlations between a halo’s physical properties and its large scale environment, i.e. assembly bias. It is common for models of the galaxy-halo connection to assume that galaxy properties are only a function of halo mass, implicitly ignoring how assembly bias may affect galaxies. Recently, programs to model and constrain the degree to which galaxy properties are influenced by assembly bias have been undertaken; however, the extent and character of galaxy assembly bias remains a mystery. Nevertheless, characterizing and modeling galaxy assembly bias is an important step in understanding galaxy evolution and limiting any systematic effects assembly bias may pose in cosmological measurements using galaxy surveys.I will present work on modeling and constraining the effect of assembly bias in two galaxy properties: stellar mass and star-formation rate. Conditional abundance matching allows for these galaxy properties to be tied to halo formation history to a variable degree, making studies of the relative strength of assembly bias possible. Galaxy-galaxy clustering and galactic conformity, the degree to which galaxy color is correlated between neighbors, are sensitive observational measures of galaxy assembly bias. I will show how these measurements can be used to constrain galaxy assembly bias and the peril of ignoring it.
Population stratification bias in the case-only study for gene-environment interactions.
Wang, Liang-Yi; Lee, Wen-Chung
2008-07-15
The case-only study is a convenient approach and provides increased statistical efficiency in detecting gene-environment interactions. The validity of a case-only study hinges on one well-recognized assumption: The susceptibility genotypes and the environmental exposures of interest are independent in the population. Otherwise, the study will be biased. The authors show that hidden stratification in the study population could also ruin a case-only study. They derive the formulas for population stratification bias. The bias involves three terms: 1) the coefficient of variation of the exposure prevalence odds, 2) the coefficient of variation of the genotype frequency odds, and 3) the correlation coefficient between the exposure prevalence odds and the genotype frequency odds. The authors perform simulation to investigate the magnitude of bias over a wide range of realistic scenarios. It is found that the estimated interaction effect is frequently biased by more than 5%. For a rarer gene and a rarer exposure, the bias becomes even larger (>30%). Because of the potentially large bias, researchers conducting case-only studies should use the boundary formula presented in this paper to make more prudent interpretations of their results, or they should use stratified analysis or a modeling approach to adjust for population stratification bias in their studies.
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
Directory of Open Access Journals (Sweden)
Muntazir Hussain
2013-05-01
Full Text Available We studied the hindsight bias and investor decision making by employing the novel approach asset selection effect and sign of return effect. The study investigated the hindsight bias and investor decision making through questionnaires. The respondents are divided into three groups namely bank financial managers, stock market investors and students. The statistical significance of the asset selection effect and sign of return effect is tested by proportional z-test. Furthermore, the correlation of the memory error and recall error is also determined. The overall perceived error (hindsight bias relationship is checked with the confidence in recall and confidence in estimate. We found strong evidence of hindsight bias in all respondents groups and its worst consequence on investment decision making. The bank financial managers were found less exposed to hindsight bias in comparison to stock market investors in asset selection effect. However, in sign of return effect the financial managers were more hindsight biased than the stock market investors. The relationship of hindsight bias and confidence in recall and confidence in estimate also confirms that all the respondents were hindsight biased and more confident in their estimate and less confident in their recall. All the respondents claim that they knew the phenomenon all along are wrong in their estimate. The respondents were unable to learn from previous errors and unable to detect their errors in estimate and recall. This error in prediction leads the investor to bear the risk above their accepted level which is harmful to their wealth.
Non-local bias contribution to third-order galaxy correlations
Bel, Julien; Gaztañaga, Enrique
2015-01-01
We study halo clustering bias with second- and third-order statistics of halo and matter density fields in the MICE Grand Challenge simulation. We verify that two-point correlations deliver reliable estimates of the linear bias parameters at large scales, while estimations from the variance can be significantly affected by non-linear and possibly non-local contributions to the bias function. Combining three-point auto- and cross-correlations we find, for the first time in configuration space, evidence for the presence of such non-local contributions. These contributions are consistent with predicted second-order non-local effects on the bias functions originating from the dark matter tidal field. Samples of massive haloes show indications of bias (local or non-local) beyond second order. Ignoring non-local bias causes $20-30$\\% and $5-10$\\% overestimation of the linear bias from three-point auto- and cross-correlations respectively. We study two third-order bias estimators which are not affected by second-ord...
Adrenal Gland Tumors: Statistics
... Gland Tumor: Statistics Request Permissions Adrenal Gland Tumor: Statistics Approved by the Cancer.Net Editorial Board , 03/ ... primary adrenal gland tumor is very uncommon. Exact statistics are not available for this type of tumor ...
Neuroendocrine Tumor: Statistics
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Savage, Leonard J
1972-01-01
Classic analysis of the foundations of statistics and development of personal probability, one of the greatest controversies in modern statistical thought. Revised edition. Calculus, probability, statistics, and Boolean algebra are recommended.
Quality assurance and statistical control
DEFF Research Database (Denmark)
Heydorn, K.
1991-01-01
In scientific research laboratories it is rarely possible to use quality assurance schemes, developed for large-scale analysis. Instead methods have been developed to control the quality of modest numbers of analytical results by relying on statistical control: Analysis of precision serves...... to detect analytical errors by comparing the a priori precision of the analytical results with the actual variability observed among replicates or duplicates. The method relies on the chi-square distribution to detect excess variability and is quite sensitive even for 5-10 results. Interference control...... serves to detect analytical bias by comparing results obtained by two different analytical methods, each relying on a different detection principle and therefore exhibiting different influence from matrix elements; only 5-10 sets of results are required to establish whether a regression line passes...
Algebraic statistics computational commutative algebra in statistics
Pistone, Giovanni; Wynn, Henry P
2000-01-01
Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. It begins with an introduction to Gröbner bases and a thorough description of their applications to experimental design. A special chapter covers the binary case with new application to coherent systems in reliability and two level factorial designs. The work paves the way, in the last two chapters, for the application of computer algebra to discrete probability and statistical modelling through the important concept of an algebraic statistical model.As the first book on the subject, Algebraic Statistics presents many opportunities for spin-off research and applications and should become a landmark work welcomed by both the statistical community and its relatives in mathematics and computer science.
Modeling confirmation bias and polarization
Del Vicario, Michela; Caldarelli, Guido; Stanley, H Eugene; Quattrociocchi, Walter
2016-01-01
Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social debates and the related polarization dynamics. We assume the basic updating rule of the Bounded Confidence Model (BCM) and we develop two variations a) the Rewire with Bounded Confidence Model (RBCM), in which discordant links are broken until convergence is reached; and b) the Unbounded Confidence Model, under which the interaction among discordant pairs of users is allowed even with a negative feedback, either with the rewiring step (RUCM) or without it (UCM). From numerical simulations we find that the new models (UCM...
Forecasts: uncertain, inaccurate and biased?
DEFF Research Database (Denmark)
Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang
2012-01-01
Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts...... accuracy of project benefits. This paper presents results from an on-going research project on uncertainties in transport project evaluation (UNITE) that find forecasts of demand to be not only uncertain, but at times also highly inaccurate and often displaying a concerning degree of bias. Demand for road...... projects appear to be systematically underestimated, while demand for rail projects appears to be systematically overestimated. We compare the findings in the present study with those of previous studies and discuss the implications for the validity of project appraisal in the form of CBA...
Social reward shapes attentional biases.
Anderson, Brian A
2016-01-01
Paying attention to stimuli that predict a reward outcome is important for an organism to survive and thrive. When visual stimuli are associated with tangible, extrinsic rewards such as money or food, these stimuli acquire high attentional priority and come to automatically capture attention. In humans and other primates, however, many behaviors are not motivated directly by such extrinsic rewards, but rather by the social feedback that results from performing those behaviors. In the present study, I examine whether positive social feedback can similarly influence attentional bias. The results show that stimuli previously associated with a high probability of positive social feedback elicit value-driven attentional capture, much like stimuli associated with extrinsic rewards. Unlike with extrinsic rewards, however, such stimuli also influence task-specific motivation. My findings offer a potential mechanism by which social reward shapes the information that we prioritize when perceiving the world around us.
Forecasts: uncertain, inaccurate and biased?
DEFF Research Database (Denmark)
Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang
2012-01-01
Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts...... of construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting...... accuracy of project benefits. This paper presents results from an on-going research project on uncertainties in transport project evaluation (UNITE) that find forecasts of demand to be not only uncertain, but at times also highly inaccurate and often displaying a concerning degree of bias. Demand for road...
STATISTICAL ANALYSIS, REPORTS), (*PROBABILITY, REPORTS), INFORMATION THEORY, DIFFERENTIAL EQUATIONS, STATISTICAL PROCESSES, STOCHASTIC PROCESSES, MULTIVARIATE ANALYSIS, DISTRIBUTION THEORY , DECISION THEORY, MEASURE THEORY, OPTIMIZATION
Symmetry as Bias: Rediscovering Special Relativity
Lowry, Michael R.
1992-01-01
This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.
Professional Culture and Climate: Addressing Unconscious Bias
Knezek, Patricia
2016-10-01
Unconscious bias reflects expectations or stereotypes that influence our judgments of others (regardless of our own group). Everyone has unconscious biases. The end result of unconscious bias can be an accumulation of advantage or disadvantage that impacts the long term career success of individuals, depending on which biases they are subject to. In order to foster a professional culture and climate, being aware of these unconscious biases and mitigating against them is a first step. This is particularly important when judgements are needed, such as in cases for recruitment, choice of speakers for conferences, and even reviewing papers submitted for publication. This presentation will cover how unconscious bias manifests itself, what evidence exists to demonstrate it exists, and ways it can be addressed.
Biased random walks on multiplex networks
Battiston, Federico; Latora, Vito
2015-01-01
Biased random walks on complex networks are a particular type of walks whose motion is biased on properties of the destination node, such as its degree. In recent years they have been exploited to design efficient strategies to explore a network, for instance by constructing maximally mixing trajectories or by sampling homogeneously the nodes. In multiplex networks, the nodes are related through different types of links (layers or communication channels), and the presence of connections at different layers multiplies the number of possible paths in the graph. In this work we introduce biased random walks on multiplex networks and provide analytical solutions for their long-term properties such as the stationary distribution and the entropy rate. We focus on degree-biased walks and distinguish between two subclasses of random walks: extensive biased walks consider the properties of each node separately at each layer, intensive biased walks deal instead with intrinsically multiplex variables. We study the effec...
When Do Children Exhibit a "Yes" Bias?
Okanda, Mako; Itakura, Shoji
2010-01-01
This study investigated whether one hundred and thirty-five 3- to 6-year-old children exhibit a yes bias to various yes-no questions and whether their knowledge status affects the production of a yes bias. Three-year-olds exhibited a yes bias to all yes-no questions such as "preference-object" and "knowledge-object" questions pertaining to…
Political Accountability, Electoral Control, and Media Bias
Adachi, Takanori; Hizen, Yoichi
2012-01-01
Are anti-establishment mass media really useful in preventing politicians from behaving dishonestly? This paper proposes a voting model for analyzing how differences in the direction of media bias affect politicians' behavior. In particular, the probability of corruption by an incumbent is higher (than that in the case of no media bias) if and only if the mass media have some degree of "anti-incumbent" bias (i.e., information favorable to the incumbent is converted into unfavorable news about...
Bayesian long branch attraction bias and corrections.
Susko, Edward
2015-03-01
Previous work on the star-tree paradox has shown that Bayesian methods suffer from a long branch attraction bias. That work is extended to settings involving more taxa and partially resolved trees. The long branch attraction bias is confirmed to arise more broadly and an additional source of bias is found. A by-product of the analysis is methods that correct for biases toward particular topologies. The corrections can be easily calculated using existing Bayesian software. Posterior support for a set of two or more trees can thus be supplemented with corrected versions to cross-check or replace results. Simulations show the corrections to be highly effective.
Guidelines for reducing bias in nursing examinations.
Klisch, M L
1994-01-01
As our nation becomes more diversified, many schools of nursing strive to improve the recruitment and retention of English as a Second Language (ESL) and minority nursing students. An important aspect of this commitment to diversity is the reduction of biased items in nursing examinations, with the goal of making the evaluation process fair for all students. The author defines test and item bias, provides examples of biased items, and presents specific guidelines for decreasing item bias in teacher-made nursing examinations. A discussion of the related topic of whether ESL students should be given extended testing time is included.
Attribution bias and social anxiety in schizophrenia
Directory of Open Access Journals (Sweden)
Amelie M. Achim
2016-06-01
Full Text Available Studies on attribution biases in schizophrenia have produced mixed results, whereas such biases have been more consistently reported in people with anxiety disorders. Anxiety comorbidities are frequent in schizophrenia, in particular social anxiety disorder, which could influence their patterns of attribution biases. The objective of the present study was thus to determine if individuals with schizophrenia and a comorbid social anxiety disorder (SZ+ show distinct attribution biases as compared with individuals with schizophrenia without social anxiety (SZ− and healthy controls. Attribution biases were assessed with the Internal, Personal, and Situational Attributions Questionnaire in 41 individual with schizophrenia and 41 healthy controls. Results revealed the lack of the normal externalizing bias in SZ+, whereas SZ− did not significantly differ from healthy controls on this dimension. The personalizing bias was not influenced by social anxiety but was in contrast linked with delusions, with a greater personalizing bias in individuals with current delusions. Future studies on attribution biases in schizophrenia should carefully document symptom presentation, including social anxiety.
Explorations in statistics: statistical facets of reproducibility.
Curran-Everett, Douglas
2016-06-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eleventh installment of Explorations in Statistics explores statistical facets of reproducibility. If we obtain an experimental result that is scientifically meaningful and statistically unusual, we would like to know that our result reflects a general biological phenomenon that another researcher could reproduce if (s)he repeated our experiment. But more often than not, we may learn this researcher cannot replicate our result. The National Institutes of Health and the Federation of American Societies for Experimental Biology have created training modules and outlined strategies to help improve the reproducibility of research. These particular approaches are necessary, but they are not sufficient. The principles of hypothesis testing and estimation are inherent to the notion of reproducibility in science. If we want to improve the reproducibility of our research, then we need to rethink how we apply fundamental concepts of statistics to our science.
Purohit, Sudha G; Deshmukh, Shailaja R
2015-01-01
STATISTICS USING R will be useful at different levels, from an undergraduate course in statistics, through graduate courses in biological sciences, engineering, management and so on. The book introduces statistical terminology and defines it for the benefit of a novice. For a practicing statistician, it will serve as a guide to R language for statistical analysis. For a researcher, it is a dual guide, simultaneously explaining appropriate statistical methods for the problems at hand and indicating how these methods can be implemented using the R language. For a software developer, it is a guide in a variety of statistical methods for development of a suite of statistical procedures.
Media bias under direct and indirect government control: when is the bias smaller?
Abhra Roy
2015-01-01
We present an analytical framework to compare media bias under direct and indirect government control. In this context, we show that direct control can lead to a smaller bias and higher welfare than indirect control. We further show that the size of the advertising market affects media bias only under direct control. Media bias, under indirect control, is not affected by the size of the advertising market.
Modeling confirmation bias and polarization
Del Vicario, Michela; Scala, Antonio; Caldarelli, Guido; Stanley, H. Eugene; Quattrociocchi, Walter
2017-01-01
Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social debates and the related polarization dynamics. We assume the basic updating rule of the Bounded Confidence Model (BCM) and we develop two variations a) the Rewire with Bounded Confidence Model (RBCM), in which discordant links are broken until convergence is reached; and b) the Unbounded Confidence Model, under which the interaction among discordant pairs of users is allowed even with a negative feedback, either with the rewiring step (RUCM) or without it (UCM). From numerical simulations we find that the new models (UCM and RUCM), unlike the BCM, are able to explain the coexistence of two stable final opinions, often observed in reality. Lastly, we present a mean field approximation of the newly introduced models. PMID:28074874
Modeling confirmation bias and polarization
Del Vicario, Michela; Scala, Antonio; Caldarelli, Guido; Stanley, H. Eugene; Quattrociocchi, Walter
2017-01-01
Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social debates and the related polarization dynamics. We assume the basic updating rule of the Bounded Confidence Model (BCM) and we develop two variations a) the Rewire with Bounded Confidence Model (RBCM), in which discordant links are broken until convergence is reached; and b) the Unbounded Confidence Model, under which the interaction among discordant pairs of users is allowed even with a negative feedback, either with the rewiring step (RUCM) or without it (UCM). From numerical simulations we find that the new models (UCM and RUCM), unlike the BCM, are able to explain the coexistence of two stable final opinions, often observed in reality. Lastly, we present a mean field approximation of the newly introduced models.
Ganichev, Sergey D.; Bel'Kov, Vasily V.; Tarasenko, Sergey A.; Danilov, Sergey N.; Giglberger, Stephan; Hoffmann, Christoph; Ivchenko, Eougenious L.; Weiss, Dieter; Wegscheider, Werner; Gerl, Christian; Schuh, Dieter; Stahl, Joachim; de Boeck, Jo; Borghs, Gustaaf; Prettl, Wilhelm
2006-09-01
The generation, manipulation and detection of spin-polarized electrons in low-dimensional semiconductors are at the heart of spintronics. Pure spin currents, that is, fluxes of magnetization without charge current, are quite attractive in this respect. A paradigmatic example is the spin Hall effect, where an electrical current drives a transverse spin current and causes a non-equilibrium spin accumulation observed near the sample boundary. Here we provide evidence for an another effect causing spin currents which is fundamentally different from the spin Hall effect. In contrast to the spin Hall effect, it does not require an electric current to flow: without bias the spin separation is achieved by spin-dependent scattering of electrons in media with suitable symmetry. We show, by free-carrier absorption of terahertz (THz) radiation, that spin currents flow in a wide range of temperatures. Moreover, the experimental results provide evidence that simple electron gas heating by any means is already sufficient to yield spin separation due to spin-dependent energy-relaxation processes.
Distinctive Characteristics of Sexual Orientation Bias Crimes
Stacey, Michele
2011-01-01
Despite increased attention in the area of hate crime research in the past 20 years, sexual orientation bias crimes have rarely been singled out for study. When these types of crimes are looked at, the studies are typically descriptive in nature. This article seeks to increase our knowledge of sexual orientation bias by answering the question:…
On Measurement Bias in Causal Inference
Pearl, Judea
2012-01-01
This paper addresses the problem of measurement errors in causal inference and highlights several algebraic and graphical methods for eliminating systematic bias induced by such errors. In particulars, the paper discusses the control of partially observable confounders in parametric and non parametric models and the computational problem of obtaining bias-free effect estimates in such models.
Understanding Implicit Bias: What Educators Should Know
Staats, Cheryl
2016-01-01
The desire to ensure the best for children is precisely why educators should become aware of the concept of implicit bias: the attitudes or stereotypes that affect our understanding, actions, and decisions in an unconscious manner. Operating outside of our conscious awareness, implicit biases are pervasive, and they can challenge even the most…
Racially Biased Policing: Determinants of Citizen Perceptions
Weitzer, Ronald; Tuch, Steven A.
2005-01-01
The current controversy surrounding racial profiling in America has focused renewed attention on the larger issue of racial bias by the police. Yet little is known about the extent of police racial bias and even less about public perceptions of the problem. This article analyzes recent national survey data on citizens' views of and reported…
Developmental Changes in the Whole Number Bias
Braithwaite, David W.; Siegler, Robert S.
2017-01-01
Many students' knowledge of fractions is adversely affected by whole number bias, the tendency to focus on the separate whole number components (numerator and denominator) of a fraction rather than on the fraction's integrated magnitude (ratio of numerator to denominator). Although whole number bias appears early in the fraction learning process…
COVARIATION BIAS AND THE RETURN OF FEAR
de Jong, Peter; VANDENHOUT, MA; MERCKELBACH, H
1995-01-01
Several studies have indicated that phobic fear is accompanied by a covariation bias, i.e. that phobic Ss tend to overassociate fear relevant stimuli and aversive outcomes. Such a covariation bias seems to be a fairly direct and powerful way to confirm danger expectations and enhance fear. Therefore
Understanding Unconscious Bias and Unintentional Racism
Moule, Jean
2009-01-01
Unconscious biases affect one's relationships, whether they are fleeting relationships in airports or longer term relationships between teachers and students, teachers and parents, teachers and other educators. In this article, the author argues that understanding one's possible biases is essential for developing community in schools.…
System Model Bias Processing Approach for Regional Coordinated States Information Involved Filtering
Directory of Open Access Journals (Sweden)
Zebo Zhou
2016-01-01
Full Text Available In the Kalman filtering applications, the conventional dynamic model which connects the states information of two consecutive epochs by state transition matrix is usually predefined and assumed to be invariant. Aiming to improve the adaptability and accuracy of dynamic model, we propose multiple historical states involved filtering algorithm. An autoregressive model is used as the dynamic model which is subsequently combined with observation model for deriving the optimal window-recursive filter formulae in the sense of minimum mean square error principle. The corresponding test statistics characteristics of system residuals are discussed in details. The test statistics of regional predicted residuals are then constructed in a time-window for model bias testing with two hypotheses, that is, the null and alternative hypotheses. Based on the innovations test statistics, we develop a model bias processing procedure including bias detection, location identification, and state correction. Finally, the minimum detectable bias and bias-to-noise ratio are both computed for evaluating the internal and external reliability of overall system, respectively.
Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach
Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio
2015-01-01
This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447–2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8–30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics. PMID:26452043
Uses and biases of volunteer water quality data
Loperfido, J.V.; Beyer, P.; Just, C.L.; Schnoor, J.L.
2010-01-01
State water quality monitoring has been augmented by volunteer monitoring programs throughout the United States. Although a significant effort has been put forth by volunteers, questions remain as to whether volunteer data are accurate and can be used by regulators. In this study, typical volunteer water quality measurements from laboratory and environmental samples in Iowa were analyzed for error and bias. Volunteer measurements of nitrate+nitrite were significantly lower (about 2-fold) than concentrations determined via standard methods in both laboratory-prepared and environmental samples. Total reactive phosphorus concentrations analyzed by volunteers were similar to measurements determined via standard methods in laboratory-prepared samples and environmental samples, but were statistically lower than the actual concentration in four of the five laboratory-prepared samples. Volunteer water quality measurements were successful in identifying and classifying most of the waters which violate United States Environmental Protection Agency recommended water quality criteria for total nitrogen (66%) and for total phosphorus (52%) with the accuracy improving when accounting for error and biases in the volunteer data. An understanding of the error and bias in volunteer water quality measurements can allow regulators to incorporate volunteer water quality data into total maximum daily load planning or state water quality reporting. ?? 2010 American Chemical Society.
Modelling large-scale halo bias using the bispectrum
Pollack, Jennifer E; Porciani, Cristiano
2011-01-01
We study the relation between the halo and matter density fields -- commonly termed bias -- in the LCDM framework. In particular, we examine the local model of biasing at quadratic order in matter density. This model is characterized by parameters b_1 and b_2. Using an ensemble of N-body simulations, we apply several statistical methods to estimate the parameters. We measure halo and matter fluctuations smoothed on various scales and find that the parameters vary with smoothing scale. We argue that, for real-space measurements, owing to the mixing of wavemodes, no scale can be found for which the parameters are independent of smoothing. However, this is not the case in Fourier space. We measure halo power spectra and construct estimates for an effective large-scale bias. We measure the configuration dependence of the halo bispectra B_hhh and reduced bispectra Q_hhh for very large-scale k-space triangles. From this we constrain b_1 and b_2. Using the lowest-order perturbation theory, we find that for B_hhh the...
A catalog of biases in questionnaires.
Choi, Bernard C K; Pak, Anita W P
2005-01-01
Bias in questionnaires is an important issue in public health research. To collect the most accurate data from respondents, investigators must understand and be able to prevent or at least minimize bias in the design of their questionnaires. This paper identifies and categorizes 48 types of bias in questionnaires based on a review of the literature and offers an example of each type. The types are categorized according to three main sources of bias: the way a question is designed, the way the questionnaire as a whole is designed, and how the questionnaire is administered. This paper is intended to help investigators in public health understand the mechanism and dynamics of problems in questionnaire design and to provide a checklist for identifying potential bias in a questionnaire before it is administered.
Are all biases missing data problems?
Howe, Chanelle J; Cain, Lauren E; Hogan, Joseph W
2015-09-01
Estimating causal effects is a frequent goal of epidemiologic studies. Traditionally, there have been three established systematic threats to consistent estimation of causal effects. These three threats are bias due to confounders, selection, and measurement error. Confounding, selection, and measurement bias have typically been characterized as distinct types of biases. However, each of these biases can also be characterized as missing data problems that can be addressed with missing data solutions. Here we describe how the aforementioned systematic threats arise from missing data as well as review methods and their related assumptions for reducing each bias type. We also link the assumptions made by the reviewed methods to the missing completely at random (MCAR) and missing at random (MAR) assumptions made in the missing data framework that allow for valid inferences to be made based on the observed, incomplete data.
A Simulation Platform for Quantifying Survival Bias
DEFF Research Database (Denmark)
Mayeda, Elizabeth Rose; Tchetgen Tchetgen, Eric J; Power, Melinda C;
2016-01-01
Bias due to selective mortality is a potential concern in many studies and is especially relevant in cognitive aging research because cognitive impairment strongly predicts subsequent mortality. Biased estimation of the effect of an exposure on rate of cognitive decline can occur when mortality......-mortality situations. This simulation platform provides a flexible tool for evaluating biases in studies with high mortality, as is common in cognitive aging research....... is a common effect of exposure and an unmeasured determinant of cognitive decline and in similar settings. This potential is often represented as collider-stratification bias in directed acyclic graphs, but it is difficult to anticipate the magnitude of bias. In this paper, we present a flexible simulation...
Composite biasing in Monte Carlo radiative transfer
Baes, Maarten; Lunttila, Tuomas; Bianchi, Simone; Camps, Peter; Juvela, Mika; Kuiper, Rolf
2016-01-01
Biasing or importance sampling is a powerful technique in Monte Carlo radiative transfer, and can be applied in different forms to increase the accuracy and efficiency of simulations. One of the drawbacks of the use of biasing is the potential introduction of large weight factors. We discuss a general strategy, composite biasing, to suppress the appearance of large weight factors. We use this composite biasing approach for two different problems faced by current state-of-the-art Monte Carlo radiative transfer codes: the generation of photon packages from multiple components, and the penetration of radiation through high optical depth barriers. In both cases, the implementation of the relevant algorithms is trivial and does not interfere with any other optimisation techniques. Through simple test models, we demonstrate the general applicability, accuracy and efficiency of the composite biasing approach. In particular, for the penetration of high optical depths, the gain in efficiency is spectacular for the spe...
Implicit Social Biases in People With Autism.
Birmingham, Elina; Stanley, Damian; Nair, Remya; Adolphs, Ralph
2015-11-01
Implicit social biases are ubiquitous and are known to influence social behavior. A core diagnostic criterion of autism spectrum disorders (ASD) is abnormal social behavior. We investigated the extent to which individuals with ASD might show a specific attenuation of implicit social biases, using Implicit Association Tests (IATs) involving social (gender, race) and nonsocial (nature, shoes) categories. High-functioning adults with ASD showed intact but reduced IAT effects relative to healthy control participants. We observed no selective attenuation of implicit social (vs. nonsocial) biases in our ASD population. To extend these results, we supplemented our healthy control data with data collected from a large online sample from the general population and explored correlations between autistic traits and IAT effects. We observed no systematic relationship between autistic traits and implicit social biases in our online and control samples. Taken together, these results suggest that implicit social biases, as measured by the IAT, are largely intact in ASD.
Sampling Bias on Cup Anemometer Mean Winds
Kristensen, L.; Hansen, O. F.; Højstrup, J.
2003-10-01
The cup anemometer signal can be sampled in several ways to obtain the mean wind speed. Here we discuss the sampling of series of mean wind speeds from consecutive rotor rotations, followed by unweighted and weighted averaging. It is shown that the unweighted averaging creates a positive bias on the long-term mean wind speed, which is at least one order of magnitude larger than the positive bias from the weighted averaging, also known as the sample-and-hold method. For a homogeneous, neutrally stratified flow the first biases are 1%-2%. For comparison the biases due to fluctuations of the three wind velocity components and due to calibration non-linearity are determined under the same conditions. The largest of these is the v-bias from direction fluctuations. The calculations pertain to the Risø P2546A model cup anemometer.
Wind models for the NSTS ascent trajectory biasing for wind load alleviation
Smith, O. E.; Adelfang, S. I.; Batts, G. W.
1990-01-01
New concepts are presented for aerospace vehicle ascent wind profile biasing. The purpose for wind biasing the ascent trajectory is to provide ascent wind loads relief and thus decrease the probability for launch delays due to wind loads exceeding critical limits. Wind biasing trajectories to the the profile of monthly mean winds have been widely used for this purpose. The wind profile models presented give additional alternatives for wind biased trajectories. They are derived from the properties of the bivariate normal probability function using the available wind statistical parameters for the launch site. The analytical expressions are presented to permit generalizations. Specific examples are given to illustrate the procedures. The wind profile models can be used to establish the ascent trajectory steering commands to guide the vehicle through the first stage. For the National Space Transportation System (NSTS) program these steering commands are called I-loads.
Expressing precision and bias in calorimetry
Energy Technology Data Exchange (ETDEWEB)
Hauck, Danielle K [Los Alamos National Laboratory; Croft, Stephen [Los Alamos National Laboratory; Bracken, David S [Los Alamos National Laboratory
2010-01-01
The calibration and calibration verification of a nuclear calorimeter represents a substantial investment of time in part because a single calorimeter measurement takes of the order of 2 to 24h to complete. The time to complete a measurement generally increases with the size of the calorimeter measurement well. It is therefore important to plan the sequence of measurements rather carefully so as to cover the dynamic range and achieve the required accuracy within a reasonable time frame. This work will discuss how calibrations and their verification has been done in the past and what we consider to be good general practice in this regard. A proposed approach to calibration and calibration verification is presented which, in the final analysis, makes use of all the available data - both calibration and verification collectively - in order to obtain the best (in a best fit sense) possible calibration. The combination of sample variance and percent recovery are traditionally taken as sufficient to capture the random (precision) and systematic (bias) contributions to the uncertainty in a calorimetric assay. These terms have been defined as well as formulated for a basic calibration. It has been tradition to assume that sensitivity is a linear function of power. However, the availability of computer power and statistical packages should be utilized to fit the response function as accurately as possible using whatever functions are deemed most suitable. Allowing for more flexibility in the response function fit will enable the calibration to be updated according to the results from regular validation measurements through the year. In a companion paper to be published elsewhere we plan to discuss alternative fitting functions.
Biased selection in Twin Cities health plans.
Dowd, B; Feldman, R
1985-01-01
The data in Tables 1 through 4 show significant differences in the enrollment of higher health-related financial risk individuals and their families among health plans. FFS enrollees are older and exhibit more chronic illness on average. IPAs enroll a greater proportion of females than do PGP or FFS plans. PGPs and IPAs do not differ significantly in the age and chronic illness of their enrollees, but IPAs enroll a significantly greater proportion of females than do PGPs. The age difference between FFS and prepaid plans appears to be greater for long-term enrollees. The same pattern is true of chronic illness, but the results are often not statistically significant. We do not have time-series data, however, and cannot conclude that future comparisons among long-term enrollees will remains as they are now. In any care our data do not support the hypothesis that biased selection is a short-term problem that will be corrected as the population in prepaid plans ages. Our data contain a cross-section of environments for health plans in firms: long- and short-term offerings, long- and short-term enrollees, high and low out-of-pocket premium costs, etc. Our strongest results are the simplest: across all plans and environments there are significant differences in enrollee characteristics. These differences would not be inefficient if all groups paid actuarially fair premiums. However, mandatory offering and community-rating allow prepaid plans to enroll a younger population with less chronic illness and to maintain an information asymmetry that prevents employers and employees from determining--either prior to or following enrollment--the relationship of the prepaid plan's premium to its marginal cost.
Heterozygosity and extra-pair paternity: biased tests result from the use of shared markers.
Wetzel, Daniel P; Westneat, David F
2009-05-01
Recent studies of extra-pair paternity have found support for the idea that heterozygous males have an advantage in siring offspring. Most studies use DNA microsatellite loci to determine paternity and then use the same loci to estimate individual heterozygosity. However, because the likelihood of detecting extra-pair offspring depends on the combinations of parental alleles, it is possible that biases arise from particular allele combinations. This might produce false support for the influence of heterozygosity on mating behaviour. We used a simulation model to assess how large this bias might be. We found two sources of bias. First, we found a bias in the null hypothesis of a simple statistical test commonly used to test several predictions of the heterozygosity hypothesis. The use of randomization tests could eliminate this bias. Second, we found that using the same loci for both paternity and heterozygosity can cause an increase in results supporting the heterozygosity hypothesis when no effect of heterozygosity actually exists. This bias is reduced through the use of more markers with higher levels of polymorphism and heterozygosity, but can be eliminated entirely by using a separate set of markers to determine paternity and assess heterozygosity. The two sources of bias reduce evidence favouring the heterozygosity hypothesis, but do not negate all of the studies that support it. We suggest that further studies of heterozygosity and extra-pair paternity are important and likely to be informative, but our recommendations should be incorporated by researchers to improve the reliability of their conclusions.
Nikulin, Grigory; Bosshard, Thomas; Wilcke, Renate; Yang, Wei; Kjellström, Erik; Bärring, Lars
2015-04-01
Bias adjustment has become an integral part of pre-processing of climate simulations for use in impact modeling studies. Considered now as a necessary step to deal with inability of climate models to accurately simulate the present/recent climate, bias adjustment is a statistical approach missing physical arguments. Even if bias adjustment is widely used nowadays it is still a topic for debates and criticism. One of the main questions is what level of uncertainty does bias adjustment introduce to future climate projections? In this study, using an ensemble of the CORDEX-Africa simulations, we investigate potential impact of bias adjustment on the simulated rainy season in West Africa. A number of characteristics reflecting different aspects of the rainy season are used, namely: onset and cessation of the rainy season, mean intensity, total amount of precipitation and intra-seasonal variability within the rainy season. All these characteristics are evaluated in the original CORDEX-Africa simulations and in bias-adjusted ones for a reference period first and then future climate projections of these characteristics are compared between two ensembles. Additionally, we examine how bias adjustment may impact selection of a smaller more manageable ensemble of regional climate simulations from a grand one.
Medical journal peer review: process and bias.
Manchikanti, Laxmaiah; Kaye, Alan D; Boswell, Mark V; Hirsch, Joshua A
2015-01-01
Scientific peer review is pivotal in health care research in that it facilitates the evaluation of findings for competence, significance, and originality by qualified experts. While the origins of peer review can be traced to the societies of the eighteenth century, it became an institutionalized part of the scholarly process in the latter half of the twentieth century. This was a response to the growth of research and greater subject specialization. With the current increase in the number of specialty journals, the peer review process continues to evolve to meet the needs of patients, clinicians, and policy makers. The peer review process itself faces challenges. Unblinded peer review might suffer from positive or negative bias towards certain authors, specialties, and institutions. Peer review can also suffer when editors and/or reviewers might be unable to understand the contents of the submitted manuscript. This can result in an inability to detect major flaws, or revelations of major flaws after acceptance of publication by the editors. Other concerns include potentially long delays in publication and challenges uncovering plagiarism, duplication, corruption and scientific misconduct. Conversely, a multitude of these challenges have led to claims of scientific misconduct and an erosion of faith. These challenges have invited criticism of the peer review process itself. However, despite its imperfections, the peer review process enjoys widespread support in the scientific community. Peer review bias is one of the major focuses of today's scientific assessment of the literature. Various types of peer review bias include content-based bias, confirmation bias, bias due to conservatism, bias against interdisciplinary research, publication bias, and the bias of conflicts of interest. Consequently, peer review would benefit from various changes and improvements with appropriate training of reviewers to provide quality reviews to maintain the quality and integrity of
Industrial statistics with Minitab
Cintas, Pere Grima; Llabres, Xavier Tort-Martorell
2012-01-01
Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.Explores
Rumsey, Deborah
2011-01-01
The fun and easy way to get down to business with statistics Stymied by statistics? No fear ? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more.Tracks to a typical first semester statistics cou
Formulas for precisely and efficiently estimating the bias and variance of the length measurements
Xue, Shuqiang; Yang, Yuanxi; Dang, Yamin
2016-10-01
Error analysis in length measurements is an important problem in geographic information system and cartographic operations. The distance between two random points—i.e., the length of a random line segment—may be viewed as a nonlinear mapping of the coordinates of the two points. In real-world applications, an unbiased length statistic may be expected in high-precision contexts, but the variance of the unbiased statistic is of concern in assessing the quality. This paper suggesting the use of a k-order bias correction formula and a nonlinear error propagation approach to the distance equation provides a useful way to describe the length of a line. The study shows that the bias is determined by the relative precision of the random line segment, and that the use of the higher-order bias correction is only needed for short-distance applications.
Experiment in Elementary Statistics
Fernando, P. C. B.
1976-01-01
Presents an undergraduate laboratory exercise in elementary statistics in which students verify empirically the various aspects of the Gaussian distribution. Sampling techniques and other commonly used statistical procedures are introduced. (CP)
Mathematical and statistical analysis
Houston, A. Glen
1988-01-01
The goal of the mathematical and statistical analysis component of RICIS is to research, develop, and evaluate mathematical and statistical techniques for aerospace technology applications. Specific research areas of interest include modeling, simulation, experiment design, reliability assessment, and numerical analysis.
U.S. Department of Health & Human Services — The CMS Office of Enterprise Data and Analytics has developed CMS Program Statistics, which includes detailed summary statistics on national health care, Medicare...
DEFF Research Database (Denmark)
Lindström, Erik; Madsen, Henrik; Nielsen, Jan Nygaard
Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics...
Overweight and Obesity Statistics
... the full list of resources . Overweight and Obesity Statistics Page Content About Overweight and Obesity Prevalence of ... adults age 20 and older [ Top ] Physical Activity Statistics Adults Research Findings Research suggests that staying active ...
... Research AMIGAS Fighting Cervical Cancer Worldwide Stay Informed Statistics for Other Kinds of Cancer Breast Cervical Colorectal ( ... Skin Vaginal and Vulvar Cancer Home Uterine Cancer Statistics Language: English Español (Spanish) Recommend on Facebook Tweet ...
... Standard Drink? Drinking Levels Defined Alcohol Facts and Statistics Print version Alcohol Use in the United States: ... 1245, 2004. PMID: 15010446 11 National Center for Statistics and Analysis. 2014 Crash Data Key Findings (Traffic ...
Recreational Boating Statistics 2012
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Recreational Boating Statistics 2013
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Systematic bias in NMR diffusion measurements on polydisperse systems.
Zhou, Xiaoyue; Xu, Kaipin; Zhang, Shanmin
2015-03-01
Least-squares fitting of the Stejskal-Tanner equation is a routine process in the measurement of molecular diffusion coefficient (MDC) using Nuclear Magnetic Resonance (NMR) Spectroscopy. It is simple and elegant. However, a bias of the MDC is noticed when the system is polydispersed. This is due to improper accounts of the diffusion coefficient distribution. Eventually, it leads to a discrepancy between the observed MDC and the statistical mean value of the distribution. To reveal the discrepancy, an analytical solution is derived when the diffusion data is taken a logarithmic linearization. Computer simulation is also applied to obtain a non-linear regression result. For a Gaussian distribution of the MDCs, the bias is proportional to the square of the distribution width (linear regression), but it is also inversely proportional to the statistical mean value of the distribution (non-linear regression). This indicates that the MDC derived from Stejskal-Tanner equation only holds well for narrow distribution of MDCs. Otherwise, molecular radius derived from the Stokes-Einstein equation needs to be reconsidered due to the incorrect estimation of the MDC.
Subhalo abundance matching and assembly bias in the EAGLE simulation
Chaves-Montero, Jonás; Angulo, Raul E.; Schaye, Joop; Schaller, Matthieu; Crain, Robert A.; Furlong, Michelle; Theuns, Tom
2016-08-01
Subhalo abundance matching (SHAM) is a widely used method to connect galaxies with dark matter structures in numerical simulations. SHAM predictions agree remarkably well with observations, yet they still lack strong theoretical support. We examine the performance, implementation, and assumptions of SHAM using the `Evolution and Assembly of Galaxies and their Environment' (EAGLE) project simulations. We find that Vrelax, the highest value of the circular velocity attained by a subhalo while it satisfies a relaxation criterion, is the subhalo property that correlates most strongly with galaxy stellar mass (Mstar). Using this parameter in SHAM, we retrieve the real-space clustering of EAGLE to within our statistical uncertainties on scales greater than 2 Mpc for galaxies with 8.77 EAGLE. The agreement is even better in redshift space, where the clustering is recovered to within our statistical uncertainties for all masses and separations. Additionally, we analyse the dependence of galaxy clustering on properties other than halo mass, i.e. the assembly bias. We demonstrate assembly bias alters the clustering in EAGLE by 20 per cent and Vrelax captures its effect to within 15 per cent. We trace small differences in the clustering to the failure of SHAM as typically implemented, i.e. the Mstar assigned to a subhalo does not depend on (i) its host halo mass, (ii) whether it is a central or a satellite. In EAGLE, we find that these assumptions are not completely satisfied.
Software for Spatial Statistics
Edzer Pebesma; Roger Bivand; Paulo Justiniano Ribeiro
2015-01-01
We give an overview of the papers published in this special issue on spatial statistics, of the Journal of Statistical Software. 21 papers address issues covering visualization (micromaps, links to Google Maps or Google Earth), point pattern analysis, geostatistics, analysis of areal aggregated or lattice data, spatio-temporal statistics, Bayesian spatial statistics, and Laplace approximations. We also point to earlier publications in this journal on the same topic.
Software for Spatial Statistics
Directory of Open Access Journals (Sweden)
Edzer Pebesma
2015-02-01
Full Text Available We give an overview of the papers published in this special issue on spatial statistics, of the Journal of Statistical Software. 21 papers address issues covering visualization (micromaps, links to Google Maps or Google Earth, point pattern analysis, geostatistics, analysis of areal aggregated or lattice data, spatio-temporal statistics, Bayesian spatial statistics, and Laplace approximations. We also point to earlier publications in this journal on the same topic.
The familiar versus the unfamiliar: Familiarity bias amongst individual investors
Directory of Open Access Journals (Sweden)
Annalien De Vries
2017-01-01
Full Text Available Purpose: The purpose of this study was to investigate the existence of familiarity bias amongst individual investors in the South African stock market. Problem investigated: According to Warren Buffet, one needs to maintain emotional detachment if one wants to be a successful investor. However, recent research indicates that the perceptions of companies’ products and brands may influence individuals’ investment decisions in the stock market. This phenomenon implies that the investment decisions of individual investors are not purely based on firm fundamentals as suggested by traditional finance theories, but might be driven partly by the positive or negative attitude they have towards certain companies’ products and brands. The existence of familiarity bias amongst individual investors was investigated to determine if individuals prefer to invest in companies they are familiar with as opposed to unfamiliar companies. Methodology: A quantitative approach was followed. An online survey was used to show images of familiar and unfamiliar company brands to respondents, whereafter respondents were asked to indicate whether they will invest in the shares of the identified companies. The statistical analysis entailed descriptive statistics as well as one-way analyses of variance to test the stated hypotheses. Main findings: The results of this exploratory study indicate that investors do exhibit familiarity bias when choosing between different companies to invest in. Value of the research: The inclination of individual investors to invest in familiar corporate brands can have implications for the marketing industry, financial markets, the performance of companies as well as the investment performance of individual investors in the sense that it would seem that company brands could have an influence on investment decisions.
Detecting errors in micro and trace analysis by using statistics
DEFF Research Database (Denmark)
Heydorn, K.
1993-01-01
to be in statistical control. Significant deviations between analytical results from different laboratories reveal the presence of systematic errors, and agreement between different laboratories indicate the absence of systematic errors. This statistical approach, referred to as the analysis of precision, was applied...... to results for chlorine in freshwater from BCR certification analyses by highly competent analytical laboratories in the EC. Titration showed systematic errors of several percent, while radiochemical neutron activation analysis produced results without detectable bias....
Lenard, Christopher; McCarthy, Sally; Mills, Terence
2014-01-01
There are many different aspects of statistics. Statistics involves mathematics, computing, and applications to almost every field of endeavour. Each aspect provides an opportunity to spark someone's interest in the subject. In this paper we discuss some ethical aspects of statistics, and describe how an introduction to ethics has been…
Youth Sports Safety Statistics
... 6):794-799. 31 American Heart Association. CPR statistics. www.heart.org/HEARTORG/CPRAndECC/WhatisCPR/CPRFactsandStats/CPRpercent20Statistics_ ... Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. (January 10, 2013). The DAWN Report: ...
Bounding the bias of contrastive divergence learning
DEFF Research Database (Denmark)
Fischer, Anja; Igel, Christian
2011-01-01
Optimization based on k-step contrastive divergence (CD) has become a common way to train restricted Boltzmann machines (RBMs). The k-step CD is a biased estimator of the log-likelihood gradient relying on Gibbs sampling. We derive a new upper bound for this bias. Its magnitude depends on k......, the number of variables in the RBM, and the maximum change in energy that can be produced by changing a single variable. The last reflects the dependence on the absolute values of the RBM parameters. The magnitude of the bias is also affected by the distance in variation between the modeled distribution...
Forecast Bias Correction: A Second Order Method
Crowell, Sean
2010-01-01
The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.
Removing Malmquist bias from linear regressions
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.
Exchange bias effect in alloys and compounds.
Giri, S; Patra, M; Majumdar, S
2011-02-23
The phenomenology of exchange bias effects observed in structurally single-phase alloys and compounds but composed of a variety of coexisting magnetic phases such as ferromagnetic, antiferromagnetic, ferrimagnetic, spin-glass, cluster-glass and disordered magnetic states are reviewed. The investigations on exchange bias effects are discussed in diverse types of alloys and compounds where qualitative and quantitative aspects of magnetism are focused based on macroscopic experimental tools such as magnetization and magnetoresistance measurements. Here, we focus on improvement of fundamental issues of the exchange bias effects rather than on their technological importance.
Reducing status quo bias in choice experiments
DEFF Research Database (Denmark)
Bonnichsen, Ole; Ladenburg, Jacob
In stated preference literature, the tendency to choose the alternative representing the status quo situation seems to exceed real life status quo effects. Accordingly, status quo bias can be a problem. In Choice Experiments, status quo bias is found to be strongly correlated with protest attitudes...... toward the cost attribute. If economic values are to be elicited, this problem is difficult to remedy. In a split sample framework we test a novel ex-ante entreaty aimed specifically at the cost attribute and find that it effectively reduces status quo bias and improves the internal validity...
Reducing status quo bias in choice experiments
DEFF Research Database (Denmark)
Bonnichsen, Ole; Ladenburg, Jacob
2015-01-01
to be superior, i.e. a status quo effect. However, in the stated preference literature, the tendency to choose the alternative representing the status quo situation seems to exceed real life status quo effects. Accordingly, status quo bias can be a problem. In the Choice Experiment literature, status quo bias...... is found to be a function of protest attitudes concerning the payment of the hypothetical good. In a split sample framework we test an ex-ante entreaty aimed at reducing payment based protest attitudes. We find that the entreaty reduces status quo bias and improves the internal validity of stated...
Selling statistics[Statistics in scientific progress
Energy Technology Data Exchange (ETDEWEB)
Bridle, S. [Astrophysics Group, University College London (United Kingdom)]. E-mail: sarah@star.ucl.ac.uk
2006-09-15
From Cosmos to Chaos- Peter Coles, 2006, Oxford University Press, 224pp. To confirm or refute a scientific theory you have to make a measurement. Unfortunately, however, measurements are never perfect: the rest is statistics. Indeed, statistics is at the very heart of scientific progress, but it is often poorly taught and badly received; for many, the very word conjures up half-remembered nightmares of 'null hypotheses' and 'student's t-tests'. From Cosmos to Chaos by Peter Coles, a cosmologist at Nottingham University, is an approachable antidote that places statistics in a range of catchy contexts. Using this book you will be able to calculate the probabilities in a game of bridge or in a legal trial based on DNA fingerprinting, impress friends by talking confidently about entropy, and stretch your mind thinking about quantum mechanics. (U.K.)
Boslaugh, Sarah
2013-01-01
Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts. Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.
Business statistics for dummies
Anderson, Alan
2013-01-01
Score higher in your business statistics course? Easy. Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons. Business Statistics For Dummies tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, w
Statistics & probaility for dummies
Rumsey, Deborah J
2013-01-01
Two complete eBooks for one low price! Created and compiled by the publisher, this Statistics I and Statistics II bundle brings together two math titles in one, e-only bundle. With this special bundle, you'll get the complete text of the following two titles: Statistics For Dummies, 2nd Edition Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tra
Nonparametric statistical inference
Gibbons, Jean Dickinson
2010-01-01
Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente
Griffiths, Dawn
2009-01-01
Wouldn't it be great if there were a statistics book that made histograms, probability distributions, and chi square analysis more enjoyable than going to the dentist? Head First Statistics brings this typically dry subject to life, teaching you everything you want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples. Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics
Statistics Essentials For Dummies
Rumsey, Deborah
2010-01-01
Statistics Essentials For Dummies not only provides students enrolled in Statistics I with an excellent high-level overview of key concepts, but it also serves as a reference or refresher for students in upper-level statistics courses. Free of review and ramp-up material, Statistics Essentials For Dummies sticks to the point, with content focused on key course topics only. It provides discrete explanations of essential concepts taught in a typical first semester college-level statistics course, from odds and error margins to confidence intervals and conclusions. This guide is also a perfect re
Estimation and inferential statistics
Sahu, Pradip Kumar; Das, Ajit Kumar
2015-01-01
This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. Every concept is supported with relevant research examples to help readers to find the most suitable application. Statistical tools have been presented by using real-life examples, removing the “fear factor” usually associated with this complex subject. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.
Lectures on algebraic statistics
Drton, Mathias; Sullivant, Seth
2009-01-01
How does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of "algebraic statistics". In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models.
Popularity, similarity, and the network extraversion bias.
Feiler, Daniel C; Kleinbaum, Adam M
2015-05-01
Using the emergent friendship network of an incoming cohort of students in an M.B.A. program, we examined the role of extraversion in shaping social networks. Extraversion has two important implications for the emergence of network ties: a popularity effect, in which extraverts accumulate more friends than introverts do, and a homophily effect, in which the more similar are two people's levels of extraversion, the more likely they are to become friends. These effects result in a systematic network extraversion bias, in which people's social networks will tend to be overpopulated with extraverts and underpopulated with introverts. Moreover, the most extraverted people have the greatest network extraversion bias, and the most introverted people have the least network extraversion bias. Our finding that social networks were systematically misrepresentative of the broader social environment raises questions about whether there is a societal bias toward believing other people are more extraverted than they actually are and whether introverts are better socially calibrated than extraverts.
Autobiographical memory bias in social anxiety.
Krans, Julie; de Bree, June; Bryant, Richard A
2014-01-01
In social anxiety the psychological self is closely related to the feared stimulus. Socially anxious individuals are, by definition, concerned about how the self is perceived and evaluated by others. As autobiographical memory is strongly related to views of the self it follows that biases in autobiographical memory play an important role in social anxiety. In the present study high (n = 19) and low (n = 29) socially anxious individuals were compared on autobiographical memory bias, current goals, and self-discrepancy. Individuals high in social anxiety showed a bias towards recalling more negative and more social anxiety-related autobiographical memories, reported more current goals related to overcoming social anxiety, and showed larger self-discrepancies. The pattern of results is largely in line with earlier research in individuals with PTSD and complicated grief. This suggests that the relation between autobiographical memory bias and the self is a potentially valuable trans-diagnostic factor.
Accounting for Unobservable Exposure Time Bias Wh...
U.S. Department of Health & Human Services — Accounting for Unobservable Exposure Time Bias When Using Medicare Prescription Drug Data Unobservable exposure time is common among Medicare Part D beneficiaries,...
Biased liquid crystal photonic bandgap fiber
DEFF Research Database (Denmark)
Weirich, Johannes; Lægsgaard, Jesper; Alkeskjold, Thomas Tanggaard;
2008-01-01
We simulate the director structure of all capillaries in a biased photonic crystal fiber infiltrated with liquid crystals. Various mode simulations for different capillaries show the necessity to consider the entire structure....
Bias Modeling for Distantly Supervised Relation Extraction
Directory of Open Access Journals (Sweden)
Yang Xiang
2015-01-01
Full Text Available Distant supervision (DS automatically annotates free text with relation mentions from existing knowledge bases (KBs, providing a way to alleviate the problem of insufficient training data for relation extraction in natural language processing (NLP. However, the heuristic annotation process does not guarantee the correctness of the generated labels, promoting a hot research issue on how to efficiently make use of the noisy training data. In this paper, we model two types of biases to reduce noise: (1 bias-dist to model the relative distance between points (instances and classes (relation centers; (2 bias-reward to model the possibility of each heuristically generated label being incorrect. Based on the biases, we propose three noise tolerant models: MIML-dist, MIML-dist-classify, and MIML-reward, building on top of a state-of-the-art distantly supervised learning algorithm. Experimental evaluations compared with three landmark methods on the KBP dataset validate the effectiveness of the proposed methods.
Reducing hypothetical bias in choice experiments
DEFF Research Database (Denmark)
Ladenburg, Jacob; Olsen, Søren Bøye; Nielsen, Rasmus Christian Fejer
Hypothetical bias in stated preference studies is an essential problem which reduces the validity of the obtained welfare estimates for non-market goods. In the attempt to mitigate hypothetical bias, a type of reminder known as Cheap Talk, has been applied in previous studies and found to overall...... eliminate some of the hypothetical bias. The present paper tests an addition to Cheap Talk, an Opt-Out Reminder. The Opt-Out Reminder is an objective short script presented prior to the choice sets, prompting the respondent to choose the opt-out alternative, if he/she finds the proposed policy generated...... alternatives in a choice set too expensive. The results suggest that adding an Opt-Out Reminder to Cheap Talk can in fact reduce hypothetical bias even further and reduces some of the ineffectiveness of CT in relation to the survey bid range and experienced respondents....
Neurocognition and cognitive biases in schizophrenia.
Garcia, Cristina P; Sacks, Stephanie A; Weisman de Mamani, Amy G
2012-08-01
Individuals with schizophrenia have been found to exhibit a number of information processing biases that may play a role in the development and exacerbation of symptoms and may impair overall functioning. However, little is known about the factors that are associated with these cognitive biases. Recently, researchers have begun to consider whether neurocognitive deficits, common in schizophrenia, may be risk factors for the development of cognitive biases. In the present study, we assessed neurocognition (verbal learning, delayed verbal recall memory, and verbal recognition memory) and cognitive biases (knowledge corruption and impaired cognitive insight) in 72 individuals with schizophrenia or schizoaffective disorder. As hypothesized, poorer delayed verbal recall memory was associated with increased knowledge corruption. Contrary to expectations, verbal learning and verbal memory were not associated with cognitive insight. These findings suggest that an inadequate recall memory system may put patients with schizophrenia at greater risk for cognitive distortions.
Fixed points of occasionally weakly biased mappings
Directory of Open Access Journals (Sweden)
Y. Mahendra Singh, M. R. Singh
2012-09-01
Full Text Available Common fixed point results due to Pant et al. [Pant et al., Weak reciprocal continuity and fixed point theorems, Ann Univ Ferrara, 57(1, 181-190 (2011] are extended to a class of non commuting operators called occasionally weakly biased pair[ N. Hussain, M. A. Khamsi A. Latif, Commonfixed points for JH-operators and occasionally weakly biased pairs under relaxed conditions, Nonlinear Analysis, 74, 2133-2140 (2011]. We also provideillustrative examples to justify the improvements. Abstract. Common fixed point results due to Pant et al. [Pant et al., Weakreciprocal continuity and fixed point theorems, Ann Univ Ferrara, 57(1, 181-190 (2011] are extended to a class of non commuting operators called occasionally weakly biased pair[ N. Hussain, M. A. Khamsi A. Latif, Common fixed points for JH-operators and occasionally weakly biased pairs under relaxed conditions, Nonlinear Analysis, 74, 2133-2140 (2011]. We also provide illustrative examples to justify the improvements.
Measuring the bias of technological change
Doraszelski, Ulrich; Jaumandreu, Jordi
2014-01-01
Technological change can increase the productivity of the various factors of production in equal terms or it can be biased towards a specific factor. We develop an estimator for production functions when productivity is multi-dimensional. We directly assess the bias of technological change by measuring, at the level of the individual firm, how much of it is factor neutral and how much is labor augmenting. Applying our estimator to panel data from Spain, we find that technological change is in...
Reduction of Photodiode Nonlinearities by Adaptive Biasing
2016-10-14
7 Bias setting from current detection . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Ghost detection...noise floor for a 5V bias. In other words, this IMD2 signal would present a ghost signal and would degrade the system’s SFDR. We are thus led to the...here, we only mention this as a possibility and will not describe it further. 10 Frigo, Hutchinson, Williams Ghost detection through interactive
SUBJECTIVE AGE BIASES AMONG ADOLESCENT GIRLS
Guiot, Denis
2000-01-01
International audience; Until now, the concept of subjective age has only been used to segment the mature market. Research on consumer behavior has shown the effects of a youthful bias, the tendency to see oneself as younger. Using a conceptual framework based on self-concept, social comparison, and symbolic consumption, this research proposes to characterize the antecedents and the effects of an analogous but opposed tendency: an older bias among adolescent girls. An empirical study carried ...
Perceptual and performance biases in action selection
2008-01-01
When we see an object in the world, there may be a large number of different ways to interact with that object. This large 'visuomotor space' can be constrained through affordances (perceptually available object properties defining potential uses), task demands and the actor's intentions. The effects of perceptual biases can be modified by performance factors, such as a limb's end-state-comfort (ESC; Rosenbaum et al. 1990). We investigated how two other potential performance biases affected i...
Implicit Social Biases in People With Autism
2015-01-01
Implicit social biases are ubiquitous and are known to influence social behavior. A core diagnostic criterion of autism spectrum disorders (ASD) is abnormal social behavior. We investigated the extent to which individuals with ASD might show a specific attenuation of implicit social biases, using Implicit Association Tests (IATs) involving social (gender, race) and nonsocial (nature, shoes) categories. High-functioning adults with ASD showed intact but reduced IAT effects relative to healthy ...
Baseline Statistics of Linked Statistical Data
Scharnhorst, Andrea; Meroño-Peñuela, Albert; Guéret, Christophe
2014-01-01
We are surrounded by an ever increasing ocean of information, everybody will agree to that. We build sophisticated strategies to govern this information: design data models, develop infrastructures for data sharing, building tool for data analysis. Statistical datasets curated by National Statistica
Gaidos, Eric
2012-01-01
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 towards large, more luminous stars and underestimation of the radii of about one third of candidate planets, especially those larger than Neptune. Third,...
Neural correlates of attentional bias in addiction.
Hester, Robert; Luijten, Maartje
2014-06-01
A small but growing neuroimaging literature has begun to examine the neural mechanisms underlying the difficulty that substance-use dependent (SUD) groups have with ignoring salient, drug-related stimuli. Drug-related attentional bias appears to implicate the countermanding forces of cognitive control and reward salience. Basic cognitive neuroscience research suggests that ignoring emotionally evocative stimuli in our environment requires both up-regulation of control networks and down-regulation of processing in emotion and reward regions. Research to date suggests that attentional biases for drug-related stimuli emerge from a failure to sufficiently increase control of attention over salient, but task-irrelevant stimuli. While SUD samples have typically shown increased activity in the cognitive control regions (ie, lateral prefrontal and dorsal anterior cingulate), during attentional bias such increases appear to have been insufficient for the concomitant increases in processing by the emotion/reward regions (ie, amygdala, insula, and striatum). Given the potential contribution of attentional biases to perpetuating drug use and the development of interventions (both pharmaceutical and cognitive-behavioral) to treat biases, understanding the neural basis of successfully reducing bias remains an important, but as yet unanswered, question for our field.
Constraints on Assembly Bias from Galaxy Clustering
Zentner, Andrew R; Bosch, Frank C van den; Lange, Johannes U; Villarreal, Antonio
2016-01-01
We constrain the newly-introduced decorated Halo Occupation Distribution (HOD) model using SDSS DR7 measurements of projected galaxy clustering or r-band luminosity threshold samples. The decorated HOD is a model for the galaxy-halo connection that augments the HOD by allowing for the possibility of galaxy assembly bias: galaxy luminosity may be correlated with dark matter halo properties besides mass, Mvir. We demonstrate that it is not possible to rule out galaxy assembly bias using DR7 measurements of galaxy clustering alone. Moreover, galaxy samples with Mr < -20 and Mr < -20.5 favor strong central galaxy assembly bias. These samples prefer scenarios in which high-concentration are more likely to host a central galaxy relative to low-concentration halos of the same mass. We exclude zero assembly bias with high significance for these samples. Satellite galaxy assembly bias is significant for the faintest sample, Mr < -19. We find no evidence for assembly bias in the Mr < -21 sample. Assembly bi...
The statistical stability phenomenon
Gorban, Igor I
2017-01-01
This monograph investigates violations of statistical stability of physical events, variables, and processes and develops a new physical-mathematical theory taking into consideration such violations – the theory of hyper-random phenomena. There are five parts. The first describes the phenomenon of statistical stability and its features, and develops methods for detecting violations of statistical stability, in particular when data is limited. The second part presents several examples of real processes of different physical nature and demonstrates the violation of statistical stability over broad observation intervals. The third part outlines the mathematical foundations of the theory of hyper-random phenomena, while the fourth develops the foundations of the mathematical analysis of divergent and many-valued functions. The fifth part contains theoretical and experimental studies of statistical laws where there is violation of statistical stability. The monograph should be of particular interest to engineers...
Random walk with nonuniform angular distribution biased by an external periodic pulse
Acharyya, Aranyak
2016-11-01
We studied the motion of a random walker in two dimensions with nonuniform angular distribution biased by an external periodic pulse. Here, we analytically calculated the mean square displacement (end-to-end distance of a walk after n time steps), without bias and with bias. We determined the average x-component of the final displacement of the walker. Interestingly, we noted that for a particular periodicity of the bias, this average x-component of the final displacement becomes approximately zero. The average y-component of the final displacement is found to be zero for any perodicity of the bias, and its reason can be attributed to the nature of the probability density function of the angle (subtended by the displacement vector with the x-axis). These analytical results are also supported by computer simulations. The present study may be thought of as a model for arresting the bacterial motion (along a preferred direction) by an external periodic bias. This article will be useful for undergraduate students of physics, statistics and biology as an example of an interdisciplinary approach to understand a way to control bacterial motion.
Sleep-related attentional bias in insomnia: A state-of-the-science review.
Harris, Kamelia; Spiegelhalder, Kai; Espie, Colin A; MacMahon, Kenneth M A; Woods, Heather Cleland; Kyle, Simon D
2015-12-01
Prominent models of insomnia posit that sleep-related attentional bias plays an important role in the development and maintenance of insomnia. Here we conduct the first systematic review of the sleep-related attentional bias construct, indexed through reaction time-based experimental tasks. Literature search identified 13 studies that met pre-defined inclusion/exclusion criteria. Included studies involved between-group comparisons (poor sleepers versus controls), as well as sleep manipulations and correlational investigations with healthy sleepers. For studies involving comparisons between poor sleepers and healthy controls, effect size estimates were computed for task-relevant dependent variables. Six of the nine studies comparing poor sleepers and controls revealed statistically significant group differences in support of a differential sleep-related attentional bias (medium-to-large effect sizes), with flicker, dot-probe and Posner tasks being most sensitive to group effects. Due to the paucity of studies and variability in design and measurement, no conclusions could be reached regarding manipulation or induction of attentional bias in good sleepers. Results from the relatively small number of studies support the presence of sleep-related attentional bias in insomnia; however, its role in the development and/or maintenance of insomnia remains to be elucidated. We set out a research agenda aimed at advancing the understanding of sleep-related attention bias.
Model free audit methodology for bias evaluation of tumour progression in oncology.
Stone, Andrew; Macpherson, Euan; Smith, Ann; Jennison, Christopher
2015-01-01
Many oncology studies incorporate a blinded independent central review (BICR) to make an assessment of the integrity of the primary endpoint, progression free survival. Recently, it has been suggested that, in order to assess the potential for bias amongst investigators, a BICR amongst only a sample of patients could be performed; if evidence of bias is detected, according to a predefined threshold, the BICR is then assessed in all patients, otherwise, it is concluded that the sample was sufficient to rule out meaningful levels of bias. In this paper, we present an approach that adapts a method originally created for defining futility bounds in group sequential designs. The hazard ratio ratio, the ratio of the hazard ratio (HR) for the treatment effect estimated from the BICR to the corresponding HR for the investigator assessments, is used as the metric to define bias. The approach is simple to implement and ensures a high probability that a substantial true bias will be detected. In the absence of bias, there is a high probability of accepting the accuracy of local evaluations based on the sample, in which case an expensive BICR of all patients is avoided. The properties of the approach are demonstrated by retrospective application to a completed Phase III trial in colorectal cancer. The same approach could easily be adapted for other disease settings, and for test statistics other than the hazard ratio.
Equilibrium statistical mechanics
Jackson, E Atlee
2000-01-01
Ideal as an elementary introduction to equilibrium statistical mechanics, this volume covers both classical and quantum methodology for open and closed systems. Introductory chapters familiarize readers with probability and microscopic models of systems, while additional chapters describe the general derivation of the fundamental statistical mechanics relationships. The final chapter contains 16 sections, each dealing with a different application, ordered according to complexity, from classical through degenerate quantum statistical mechanics. Key features include an elementary introduction t
Campbell, M J
2011-01-01
The new edition of this international bestseller continues to throw light on the world of statistics for health care professionals and medical students. Revised throughout, the 11th edition features new material in the areas of relative risk, absolute risk and numbers needed to treat diagnostic tests, sensitivity, specificity, ROC curves free statistical software The popular self-testing exercises at the end of every chapter are strengthened by the addition of new sections on reading and reporting statistics and formula appreciation.
Applied statistics for economists
Lewis, Margaret
2012-01-01
This book is an undergraduate text that introduces students to commonly-used statistical methods in economics. Using examples based on contemporary economic issues and readily-available data, it not only explains the mechanics of the various methods, it also guides students to connect statistical results to detailed economic interpretations. Because the goal is for students to be able to apply the statistical methods presented, online sources for economic data and directions for performing each task in Excel are also included.
Contributions to industrial statistics
2015-01-01
This thesis is about statistics' contributions to industry. It is an article compendium comprising four articles divided in two blocks: (i) two contributions for a water supply company, and (ii) significance of the effects in Design of Experiments. In the first block, great emphasis is placed on how the research design and statistics can be applied to various real problems that a water company raises and it aims to convince water management companies that statistics can be very useful to impr...
Lectures on statistical mechanics
Bowler, M G
1982-01-01
Anyone dissatisfied with the almost ritual dullness of many 'standard' texts in statistical mechanics will be grateful for the lucid explanation and generally reassuring tone. Aimed at securing firm foundations for equilibrium statistical mechanics, topics of great subtlety are presented transparently and enthusiastically. Very little mathematical preparation is required beyond elementary calculus and prerequisites in physics are limited to some elementary classical thermodynamics. Suitable as a basis for a first course in statistical mechanics, the book is an ideal supplement to more convent
Mathematical statistics with applications
Wackerly, Dennis D; Scheaffer, Richard L
2008-01-01
In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps you discover the nature of statistics and understand its essential role in scientific research.
Equilibrium statistical mechanics
Mayer, J E
1968-01-01
The International Encyclopedia of Physical Chemistry and Chemical Physics, Volume 1: Equilibrium Statistical Mechanics covers the fundamental principles and the development of theoretical aspects of equilibrium statistical mechanics. Statistical mechanical is the study of the connection between the macroscopic behavior of bulk matter and the microscopic properties of its constituent atoms and molecules. This book contains eight chapters, and begins with a presentation of the master equation used for the calculation of the fundamental thermodynamic functions. The succeeding chapters highlight t
Optimization techniques in statistics
Rustagi, Jagdish S
1994-01-01
Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimiza
Mahalanobis, P C
1965-01-01
Contributions to Statistics focuses on the processes, methodologies, and approaches involved in statistics. The book is presented to Professor P. C. Mahalanobis on the occasion of his 70th birthday. The selection first offers information on the recovery of ancillary information and combinatorial properties of partially balanced designs and association schemes. Discussions focus on combinatorial applications of the algebra of association matrices, sample size analogy, association matrices and the algebra of association schemes, and conceptual statistical experiments. The book then examines latt
Placebo effect studies are susceptible to response bias and to other types of biases
DEFF Research Database (Denmark)
Hróbjartsson, Asbjørn; Kaptchuk, Ted J; Miller, Franklin G
2011-01-01
Investigations of the effect of placebo are often challenging to conduct and interpret. The history of placebo shows that assessment of its clinical significance has a real potential to be biased. We analyze and discuss typical types of bias in studies on placebo.......Investigations of the effect of placebo are often challenging to conduct and interpret. The history of placebo shows that assessment of its clinical significance has a real potential to be biased. We analyze and discuss typical types of bias in studies on placebo....
Annual Statistical Supplement, 2015
Social Security Administration — The Annual Statistical Supplement, 2015 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2002
Social Security Administration — The Annual Statistical Supplement, 2002 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2014
Social Security Administration — The Annual Statistical Supplement, 2014 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2000
Social Security Administration — The Annual Statistical Supplement, 2000 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2010
Social Security Administration — The Annual Statistical Supplement, 2010 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2009
Social Security Administration — The Annual Statistical Supplement, 2009 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2004
Social Security Administration — The Annual Statistical Supplement, 2004 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Shasha, Dennis
2010-01-01
Statistics is the activity of inferring results about a population given a sample. Historically, statistics books assume an underlying distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot normally be sure of the underlying distribution. For that reason, this book presents a distribution-independent approach to statistics based on a simple computational counting idea called resampling. This book explains the basic concepts of resampling, then systematically presents the standard statistical measures along
Kanji, Gopal K
2006-01-01
This expanded and updated Third Edition of Gopal K. Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test's purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example, and the numerical calculation. 100 Statistical Tests, Third Edition is the one indispensable guide for users of statistical materials and consumers of statistical information at all levels and across all disciplines.
Annual Statistical Supplement, 2011
Social Security Administration — The Annual Statistical Supplement, 2011 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
2009-01-01
Ericsson is a global provider of telecommunications systems equipment and related services for mobile and fixed network operators. 3Gsim is a tool used by Ericsson in tests of the 3G RNC node. In order to validate the tests, statistics are constantly gathered within 3Gsim and users can use telnet to access the statistics using some system specific 3Gsim commands. The statistics can be retrieved but is unstructured for the human eye and needs parsing and arranging to be readable. The statist...
Boslaugh, Sarah
2008-01-01
Need to learn statistics as part of your job, or want some help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference that's perfect for anyone with no previous background in the subject. This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrat
Record Statistics and Dynamics
DEFF Research Database (Denmark)
Sibani, Paolo; Jensen, Henrik J.
2009-01-01
The term record statistics covers the statistical properties of records within an ordered series of numerical data obtained from observations or measurements. A record within such series is simply a value larger (or smaller) than all preceding values. The mathematical properties of records strongly...... fluctuations of e. g. the energy are able to push the system past some sort of ‘edge of stability’, inducing irreversible configurational changes, whose statistics then closely follows the statistics of record fluctuations....
Annual Statistical Supplement, 2006
Social Security Administration — The Annual Statistical Supplement, 2006 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2001
Social Security Administration — The Annual Statistical Supplement, 2001 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2003
Social Security Administration — The Annual Statistical Supplement, 2003 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2005
Social Security Administration — The Annual Statistical Supplement, 2005 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2008
Social Security Administration — The Annual Statistical Supplement, 2008 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Ariwahjoedi, Seramika; Kosasih, Jusak Sali; Rovelli, Carlo; Zen, Freddy Permana
2016-01-01
Following our earlier work, we construct statistical discrete geometry by applying statistical mechanics to discrete (Regge) gravity. We propose a coarse-graining method for discrete geometry under the assumptions of atomism and background independence. To maintain these assumptions, restrictions are given to the theory by introducing cut-offs, both in ultraviolet and infrared regime. Having a well-defined statistical picture of discrete Regge geometry, we take the infinite degrees of freedom (large n) limit. We argue that the correct limit consistent with the restrictions and the background independence concept is not the continuum limit of statistical mechanics, but the thermodynamical limit.
Annual Statistical Supplement, 2007
Social Security Administration — The Annual Statistical Supplement, 2007 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Bulmer, M G
1979-01-01
There are many textbooks which describe current methods of statistical analysis, while neglecting related theory. There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again fo
Systematic Biases in Parameter Estimation of Binary Black-Hole Mergers
Littenberg, Tyson B.; Baker, John G.; Buonanno, Alessandra; Kelly, Bernard J.
2012-01-01
Parameter estimation of binary-black-hole merger events in gravitational-wave data relies on matched filtering techniques, which, in turn, depend on accurate model waveforms. Here we characterize the systematic biases introduced in measuring astrophysical parameters of binary black holes by applying the currently most accurate effective-one-body templates to simulated data containing non-spinning numerical-relativity waveforms. For advanced ground-based detectors, we find that the systematic biases are well within the statistical error for realistic signal-to-noise ratios (SNR). These biases grow to be comparable to the statistical errors at high signal-to-noise ratios for ground-based instruments (SNR approximately 50) but never dominate the error budget. At the much larger signal-to-noise ratios expected for space-based detectors, these biases will become large compared to the statistical errors but are small enough (at most a few percent in the black-hole masses) that we expect they should not affect broad astrophysical conclusions that may be drawn from the data.
Directory of Open Access Journals (Sweden)
van Duijn Cornelia M
2007-03-01
Full Text Available Abstract Scientific literature may be biased because of the internal validity of studies being compromised by different forms of measurement error, and/or because of the selective reporting of positive and 'statistically significant' results. While the first source of bias might be prevented, and in some cases corrected to a degree, the second represents a pervasive problem afflicting the medical literature; a situation that can only be 'corrected' by a change in the mindset of authors, reviewers, and editors. This review focuses on the concepts of confounding, selection bias and information bias, utilising explanatory examples and simple rules to recognise and, when possible, to correct for them. Confounding is a mixing of effects resulting from an imbalance of some of the causes of disease across the compared groups. It can be prevented by randomization and restriction, and controlled by stratification, standardization or by using multivariable techniques. Selection bias stems from an absence of comparability among the groups being studied, while information bias arises from distorted information collection techniques. Publication bias of medical research results can invalidate evidence-based medicine, when a researcher attempting to collect all the published studies on a specific topic actually gathers only a proportion of them, usually the ones reporting 'positive' results. The selective publication of 'statistically significant' results represents a problem that researchers and readers have to be aware of in order to face the entire body of published medical evidence with a degree of scepticism.
Bias-correction and Spatial Disaggregation for Climate Change Impact Assessments at a basin scale
Nyunt, Cho; Koike, Toshio; Yamamoto, Akio; Nemoto, Toshihoro; Kitsuregawa, Masaru
2013-04-01
Basin-scale climate change impact studies mainly rely on general circulation models (GCMs) comprising the related emission scenarios. Realistic and reliable data from GCM is crucial for national scale or basin scale impact and vulnerability assessments to build safety society under climate change. However, GCM fail to simulate regional climate features due to the imprecise parameterization schemes in atmospheric physics and coarse resolution scale. This study describes how to exclude some unsatisfactory GCMs with respect to focused basin, how to minimize the biases of GCM precipitation through statistical bias correction and how to cover spatial disaggregation scheme, a kind of downscaling, within in a basin. GCMs rejection is based on the regional climate features of seasonal evolution as a bench mark and mainly depends on spatial correlation and root mean square error of precipitation and atmospheric variables over the target region. Global Precipitation Climatology Project (GPCP) and Japanese 25-uear Reanalysis Project (JRA-25) are specified as references in figuring spatial pattern and error of GCM. Statistical bias-correction scheme comprises improvements of three main flaws of GCM precipitation such as low intensity drizzled rain days with no dry day, underestimation of heavy rainfall and inter-annual variability of local climate. Biases of heavy rainfall are conducted by generalized Pareto distribution (GPD) fitting over a peak over threshold series. Frequency of rain day error is fixed by rank order statistics and seasonal variation problem is solved by using a gamma distribution fitting in each month against insi-tu stations vs. corresponding GCM grids. By implementing the proposed bias-correction technique to all insi-tu stations and their respective GCM grid, an easy and effective downscaling process for impact studies at the basin scale is accomplished. The proposed method have been examined its applicability to some of the basins in various climate
Contextual modulation of biases in face recognition.
Directory of Open Access Journals (Sweden)
Fatima Maria Felisberti
Full Text Available BACKGROUND: The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. METHODOLOGY AND FINDINGS: Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174. An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2. Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3. Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4. CONCLUSION: The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context.
A novel statistical method for classifying habitat generalists and specialists
DEFF Research Database (Denmark)
Chazdon, Robin L; Chao, Anne; Colwell, Robert K
2011-01-01
We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types...... as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups...... fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest...
On the relative independence of thinking biases and cognitive ability.
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.
Robust Control Methods for On-Line Statistical Learning
Directory of Open Access Journals (Sweden)
Capobianco Enrico
2001-01-01
Full Text Available The issue of controlling that data processing in an experiment results not affected by the presence of outliers is relevant for statistical control and learning studies. Learning schemes should thus be tested for their capacity of handling outliers in the observed training set so to achieve reliable estimates with respect to the crucial bias and variance aspects. We describe possible ways of endowing neural networks with statistically robust properties by defining feasible error criteria. It is convenient to cast neural nets in state space representations and apply both Kalman filter and stochastic approximation procedures in order to suggest statistically robustified solutions for on-line learning.
Statistical error analysis of reactivity measurement
Energy Technology Data Exchange (ETDEWEB)
Thammaluckan, Sithisak; Hah, Chang Joo [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)
2013-10-15
After statistical analysis, it was confirmed that each group were sampled from same population. It is observed in Table 7 that the mean error decreases as core size increases. Application of bias factor obtained from this research reduces mean error further. The point kinetic model had been used to measure control rod worth without 3D spatial information of neutron flux or power distribution, which causes inaccurate result. Dynamic Control rod Reactivity Measurement (DCRM) was employed to take into account of 3D spatial information of flux in the point kinetics model. The measured bank worth probably contains some uncertainty such as methodology uncertainty and measurement uncertainty. Those uncertainties may varies with size of core and magnitude of reactivity. The goal of this research is to investigate the effect of core size and magnitude of control rod worth on the error of reactivity measurement using statistics.
Python for probability, statistics, and machine learning
Unpingco, José
2016-01-01
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...
Pointwise probability reinforcements for robust statistical inference.
Frénay, Benoît; Verleysen, Michel
2014-02-01
Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation.
Deconstructing Statistical Analysis
Snell, Joel
2014-01-01
Using a very complex statistical analysis and research method for the sake of enhancing the prestige of an article or making a new product or service legitimate needs to be monitored and questioned for accuracy. 1) The more complicated the statistical analysis, and research the fewer the number of learned readers can understand it. This adds a…
Statistical mechanics of pluripotency.
MacArthur, Ben D; Lemischka, Ihor R
2013-08-01
Recent reports using single-cell profiling have indicated a remarkably dynamic view of pluripotent stem cell identity. Here, we argue that the pluripotent state is not well defined at the single-cell level but rather is a statistical property of stem cell populations, amenable to analysis using the tools of statistical mechanics and information theory.
Inductive Logic and Statistics
Romeijn, J. -W.
2009-01-01
This chapter concerns inductive logic in relation to mathematical statistics. I start by introducing a general notion of probabilistic induc- tive inference. Then I introduce Carnapian inductive logic, and I show that it can be related to Bayesian statistical inference via de Finetti's representatio
Practical statistics for educators
Ravid, Ruth
2014-01-01
Practical Statistics for Educators, Fifth Edition, is a clear and easy-to-follow text written specifically for education students in introductory statistics courses and in action research courses. It is also a valuable resource and guidebook for educational practitioners who wish to study their own settings.
Practical statistics simply explained
Langley, Dr Russell A
1971-01-01
For those who need to know statistics but shy away from math, this book teaches how to extract truth and draw valid conclusions from numerical data using logic and the philosophy of statistics rather than complex formulae. Lucid discussion of averages and scatter, investigation design, more. Problems with solutions.
Handbook of Spatial Statistics
Gelfand, Alan E
2010-01-01
Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.
Statistics 101 for Radiologists.
Anvari, Arash; Halpern, Elkan F; Samir, Anthony E
2015-10-01
Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced.
DEFF Research Database (Denmark)
Lauritzen, Steffen Lilholt
This book studies the brilliant Danish 19th Century astronomer, T.N. Thiele who made important contributions to statistics, actuarial science, astronomy and mathematics. The most important of these contributions in statistics are translated into English for the first time, and the text includes...
Council of Ontario Universities, Toronto.
Summary statistics on application and registration patterns of applicants wishing to pursue full-time study in first-year places in Ontario universities (for the fall of 1987) are given. Data on registrations were received indirectly from the universities as part of their annual submission of USIS/UAR enrollment data to Statistics Canada and MCU.…
Statistical Engine Knock Control
DEFF Research Database (Denmark)
Stotsky, Alexander A.
2008-01-01
A new statistical concept of the knock control of a spark ignition automotive engine is proposed . The control aim is associated with the statistical hy pothesis test which compares the threshold value to the average value of the max imal amplitud e of the knock sensor signal at a given freq uency...
Huizingh, Eelko K. R. E.
2007-01-01
Accessibly written and easy to use, "Applied Statistics Using SPSS" is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. What is unique about Eelko Huizingh's approach is that this book is based around the needs of undergraduate students embarking on their own research project, and its self-help style is designed to…
Introduction to Bayesian statistics
Bolstad, William M
2017-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Statistical laws in linguistics
Altmann, Eduardo G
2015-01-01
Zipf's law is just one out of many universal laws proposed to describe statistical regularities in language. Here we review and critically discuss how these laws can be statistically interpreted, fitted, and tested (falsified). The modern availability of large databases of written text allows for tests with an unprecedent statistical accuracy and also a characterization of the fluctuations around the typical behavior. We find that fluctuations are usually much larger than expected based on simplifying statistical assumptions (e.g., independence and lack of correlations between observations).These simplifications appear also in usual statistical tests so that the large fluctuations can be erroneously interpreted as a falsification of the law. Instead, here we argue that linguistic laws are only meaningful (falsifiable) if accompanied by a model for which the fluctuations can be computed (e.g., a generative model of the text). The large fluctuations we report show that the constraints imposed by linguistic laws...
Statistical Methods for Astronomy
Feigelson, Eric D
2012-01-01
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches to statistical inference are treated. Resampling methods, particularly the bootstrap, provide valuable procedures when distributions functions of statistics are not known. Several approaches to model selection and good- ness of fit are considered. Applied statistics relevant to astronomical research are briefly discussed: nonparametric methods for use when little is known about the behavior of the astronomical populations or processes; data smoothing with kernel density estimation and nonparametric regression; unsupervised clustering and supervised classification procedures for multivariate problems; survival analysis for astronomical datasets with nondetections; time- and frequency-domain times series analysis for light curves; and spatial statistics to interpret the spati...
Confounding and bias in the attributable fraction.
Darrow, Lyndsey A; Steenland, N Kyle
2011-01-01
Inappropriate methods are frequently used to calculate the population attributable fraction (AF) for a given exposure of interest. This commonly occurs when authors use adjusted relative risks (RRs) reported in the literature (the "source" data), without access to the original data. In this analysis, we examine the relationship between the direction and magnitude of confounding in the source data and resulting bias in the attributable fraction when incorrect methods are used. We assess confounding by the confounding risk ratio, which is the ratio of the crude RR to the adjusted RR. We assess bias in the AF by the ratio of the incorrectly calculated AF to the correctly calculated AF. Using generated data, we examine the relationship between confounding and AF bias under various scenarios of population prevalence of exposure and strength of the exposure-disease association. For confounding risk ratios greater than 1.0 (ie, crude RR >adjusted RR), the AF is underestimated; for confounding risk ratios less than 1.0 (ie, crude RR confounding increases, and is dependent on the prevalence of exposure in the total population, with bias greatest at the lowest prevalence of exposure. Bias in the AF is also higher when the exposure-disease association is weaker. Results of these analyses can assist interpretation of incorrectly calculated attributable fraction estimates commonly reported in the epidemiologic literature.
Colin, Pierre; Kravtsov, A V; Colin, Pedro; Klypin, Anatoly; Kravtsov, Andrey V.
2000-01-01
We use N-body simulations to study the velocity bias of dark matter halos, the difference in the velocity fields of dark matter and halos, in a flat low- density LCDM model. The high force, 2kpc/h, and mass, 10^9Msun/h, resolution allows dark matter halos to survive in very dense environments of groups and clusters making it possible to use halos as galaxy tracers. We find that the velocity bias pvb measured as a ratio of pairwise velocities of the halos to that of the dark matter evolves with time and depends on scale. At high redshifts (z ~5) halos move generally faster than the dark matter almost on all scales: pvb(r)~1.2, r>0.5Mpc/h. At later moments the bias decreases and gets below unity on scales less than r=5Mpc/h: pvb(r)~(0.6-0.8) at z=0. We find that the evolution of the pairwise velocity bias follows and probably is defined by the spatial antibias of the dark matter halos at small scales. One-point velocity bias b_v, defined as the ratio of the rms velocities of halos and dark matter, provides a mo...
Electrostatically biased binding of kinesin to microtubules.
Directory of Open Access Journals (Sweden)
Barry J Grant
2011-11-01
Full Text Available The minimum motor domain of kinesin-1 is a single head. Recent evidence suggests that such minimal motor domains generate force by a biased binding mechanism, in which they preferentially select binding sites on the microtubule that lie ahead in the progress direction of the motor. A specific molecular mechanism for biased binding has, however, so far been lacking. Here we use atomistic Brownian dynamics simulations combined with experimental mutagenesis to show that incoming kinesin heads undergo electrostatically guided diffusion-to-capture by microtubules, and that this produces directionally biased binding. Kinesin-1 heads are initially rotated by the electrostatic field so that their tubulin-binding sites face inwards, and then steered towards a plus-endwards binding site. In tethered kinesin dimers, this bias is amplified. A 3-residue sequence (RAK in kinesin helix alpha-6 is predicted to be important for electrostatic guidance. Real-world mutagenesis of this sequence powerfully influences kinesin-driven microtubule sliding, with one mutant producing a 5-fold acceleration over wild type. We conclude that electrostatic interactions play an important role in the kinesin stepping mechanism, by biasing the diffusional association of kinesin with microtubules.
CD bias control on hole pattern
Koike, Kyohei; Hara, Arisa; Natori, Sakurako; Yamauchi, Shohei; Yamato, Masatoshi; Oyama, Kenichi; Yaegashi, Hidetami
2016-03-01
Gridded design rules[1] is major process in configuring logic circuit used 193-immersion lithography. In the scaling of grid patterning, we can make 10nm order line and space pattern by using multiple patterning techniques such as self-aligned multiple patterning (SAMP) and litho-etch- litho-etch (LELE)[2][3][5] . On the other hand, Line cut process has some error parameters such as pattern defect, placement error, roughness and X-Y CD bias with the decreasing scale. Especially roughness and X-Y CD bias are paid attention because it cause cut error and pattern defect. In this case, we applied some smoothing process to care hole roughness[4]. Each smoothing process showed different effect on X-Y CD bias. In this paper, we will report the pattern controllability comparison of trench and block + inverse. It include X-Y CD bias, roughness and process usability. Furthermore we will discuss optimum method focused on X-Y CD bias when we use additional process such as smoothing and shrink etching .
Graphene nanoribbon devices at high bias
Han, Melinda Y.; Kim, Philip
2014-02-01
We present the electron transport in graphene nanoribbons (GNRs) at high electric bias conduction. When graphene is patterned into a few tens of nanometer width of a ribbon shape, the carriers are confined to a quasi-one-dimensional (1D) system. Combining with the disorders in the system, this quantum confinement can lead into a transport gap in the energy spectrum of the GNRs. Similar to CNTs, this gap depends on the width of the GNR. In this review, we examine the electronic properties of lithographically fabricated GNRs, focusing on the high bias transport characteristics of GNRs as a function of density tuned by a gate voltage. We investigate the transport behavior of devices biased up to a few volts, a regime more relevant for electronics applications. We find that the high bias transport behavior in this limit can be described by hot electron scattered by the surface phonon emission, leading to a carrier velocity saturation. We also showed an enhanced current saturation effect in the GNRs with an efficient gate coupling. This effect results from the introduction of the charge neutrality point into the channel, and is similar to pinch-off in MOSFET devices. We also observe that heating effects in graphene at high bias are significant.
Evans, Richard B; O'Connor, Annette
2007-05-01
Evidence-based veterinary medicine relies critically on the scientific validity of research. A component of validity is the statistical design and subsequent analysis of data collected during the study. Correct statistical design reduces bias and improves generalizability, and correct analysis leads to appropriate inferences. Inference is the art and science of making correct decisions based on data. Because veterinarians are responsible for the medical care of their patents, it is also their responsibility to understand inferences about treatments presented in papers. This article is designed to assist veterinarians with the interpretation and understanding of statistics presented in papers.
Thermospheric density model biases at the 23rd sunspot maximum
Pardini, C.; Moe, K.; Anselmo, L.
2012-07-01
statistically significant. The minimum average biases were obtained with JB2008, NRLMSISE-00 and GOST-2004. Above 500 km, where only one satellite was analyzed (at 630 km), and errors tend to increase with altitude, it cannot be asserted that the calculated biases are significant. Nevertheless, they are presented to show how the various models diverge at higher altitudes. Around 630 km, NRLMSISE-00 had a negligible average bias, while the other models underestimated (GOST-2004) or overestimated the average density, by amounts varying between 6% and 16%. However, in terms of semi-major axis root mean square residuals, JB2006 and JB2008 were the best in any case. Below 500 km, the short-term behavior of the models was also investigated by fitting the semi-major axis decay over 30-day arcs. The resulting fitted drag coefficients displayed a significant variability, probably associated with mismodeled density variations, but JB2008, followed by JB2006, provided the smallest semi-major axis residuals and a reduced short-term variability of the density bias at just a few frequencies, having been probably successful in removing a significant fraction of the mismodeling sources.
Significance analysis of lexical bias in microarray data
Directory of Open Access Journals (Sweden)
Falkow Stanley
2003-04-01
Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.
Expectancy biases in fear and anxiety and their link to biases in attention.
Aue, Tatjana; Okon-Singer, Hadas
2015-12-01
Healthy individuals often exhibit prioritized processing of aversive information, as manifested in enhanced orientation of attention to threatening stimuli compared with neutral items. In contrast to this adaptive behavior, anxious, fearful, and phobic individuals show exaggerated attention biases to threat. In addition, they overestimate the likelihood of encountering their feared stimulus and the severity of the consequences; both are examples of expectancy biases. The co-occurrence of attention and expectancy biases in fear and anxiety raises the question about causal influences. Herein, we summarize findings related to expectancy biases in fear and anxiety, and their association with attention biases. We suggest that evidence calls for more comprehensive research strategies in the investigation of mutual influences between expectancy and attention biases, as well as their combined effects on fear and anxiety. Moreover, both types of bias need to be related to other types of distorted information processing commonly observed in fear and anxiety (e.g., memory and interpretation biases). Finally, we propose new research directions that may be worth considering in developing more effective treatments for anxiety disorders.
Cognitive Bias Modification Training in Adolescents: Effects on Interpretation Biases and Mood
Lothmann, Claudia; Holmes, Emily A.; Chan, Stella W. Y.; Lau, Jennifer Y. F.
2011-01-01
Background: Negative biases in the interpretation of ambiguous material have been linked to anxiety and mood problems. Accumulating data from adults show that positive and negative interpretation styles can be induced through cognitive bias modification (CBM) paradigms with accompanying changes in mood. Despite the therapeutic potential of…
Strick, M.A.; Stoeckart, P.F.; Dijksterhuis, A.J.
2015-01-01
It is a common research finding that conscious thought helps people to avoid racial discrimination. These three experiments, however, illustrate that conscious thought may increase biased face memory, which leads to increased judgment bias (i.e., preferring White to Black individuals). In Experiment
A Comparison of attentional biases and memory biases in social phobia and major depression
Rinck, M.; Becker, E.S.
2005-01-01
Cognitive processes play an important role in the etiology and maintenance of anxiety and depression. Current theories differ, however, in their predictions regarding the occurrence of attentional biases and memory biases in depression and anxiety. To allow for a systematic comparison of disorders a
Hindsight bias and outcome bias in the social construction of medical negligence: a review.
Hugh, Thomas B; Dekker, Sidney W A
2009-05-01
Medical negligence has been the subject of much public debate in recent decades. Although the steep increase in the frequency and size of claims against doctors at the end of the last century appears to have plateaued, in Australia at least, medical indemnity costs and consequences are still a matter of concern for doctors, medical defence organisations and governments in most developed countries. Imprecision in the legal definition of negligence opens the possibility that judgments of this issue at several levels may be subject to hindsight and outcome bias. Hindsight bias relates to the probability of an adverse event perceived by a retrospective observer ("I would have known it was going to happen"), while outcome bias is a largely subconscious cognitive distortion produced by the observer's knowledge of the adverse outcome. This review examines the relevant legal, medical, psychological and sociological literature on the operation of these pervasive and universal biases in the retrospective evaluation of adverse events. A finding of medical negligence is essentially an after-the-event social construction and is invariably affected by hindsight bias and knowledge of the adverse outcome. Such biases obviously pose a threat to the fairness of judgments. A number of debiasing strategies have been suggested but are relatively ineffective because of the universality and strength of these biases and the inherent difficulty of concealing from expert witnesses knowledge of the outcome. Education about the effect of the biases is therefore important for lawyers, medical expert witnesses and the judiciary.
Placebo effect studies are susceptible to response bias and to other types of biases
DEFF Research Database (Denmark)
Hróbjartsson, Asbjørn; Kaptchuk, Ted J; Miller, Franklin G
2011-01-01
Investigations of the effect of placebo are often challenging to conduct and interpret. The history of placebo shows that assessment of its clinical significance has a real potential to be biased. We analyze and discuss typical types of bias in studies on placebo....
Statistical downscaling using K-nearest neighbors
Gangopadhyay, Subhrendu; Clark, Martyn; Rajagopalan, Balaji
2005-02-01
Statistical downscaling provides a technique for deriving local-scale information of precipitation and temperature from numerical weather prediction model output. The K-nearest neighbor (K-nn) is a new analog-type approach that is used in this paper to downscale the National Centers for Environmental Prediction 1998 medium-range forecast model output. The K-nn algorithm queries days similar to a given feature vector in this archive and using empirical orthogonal function analysis identifies a subset of days (K) similar to the feature day. These K days are then weighted using a bisquare weight function and randomly sampled to generate ensembles. A set of 15 medium-range forecast runs was used, and seven ensemble members were generated from each run. The ensemble of 105 members was then used to select the local-scale precipitation and temperature values in four diverse basins across the contiguous United States. These downscaled precipitation and temperature estimates were subsequently analyzed to test the performance of this downscaling approach. The downscaled ensembles were evaluated in terms of bias, the ranked probability skill score as a measure of forecast skill, spatial covariability between stations, temporal persistence, consistency between variables, and conditional bias and to develop spread-skill relationships. Though this approach does not explicitly model the space-time variability of the weather fields at each individual station, the above statistics were extremely well captured. The K-nn method was also compared with a multiple-linear-regression-based downscaling model.
Reciprocity-induced bias in digital reputation
Livan, Giacomo; Aste, Tomaso
2016-01-01
The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases the digital reputations of the users of P2P networks, showing that P2P networks display exceedingly high levels of reciprocity. In fact, these are so large that they are close to the highest levels structurally compatible with the networks' reputation landscape. This shows that the crowdsourcing process underpinning digital reputation is significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings. We show that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to suppress the bias itself.
Linearity Limits of Biased 1337 Trap Detectors
Balling, Petr
2015-01-01
The upper power limit of linear response of light trap detectors was recently measured [2,3]. We have completed this measurement with test of traps with bias voltage at several visible wavelengths using silicon photodiodes Hamamatsu S1337 1010 and made a brief test of S5227 1010. Bias extends the linearity limit by factor of more than 10 for very narrow beams and more than 30 for wide beams [5]. No irreversible changes were detected even for the highest irradiance of 33 W/cm2 at 406nm. Here we present measurement of minimal bias voltage necessary for 99%, 99.8% and 99.95% linearity for several beam sizes.
Cosmology of biased discrete symmetry breaking
Gelmini, Graciela B.; Gleiser, Marcelo; Kolb, Edward W.
1988-01-01
The cosmological consequences of spontaneous breaking of an approximate discrete symmetry are studied. The breaking leads to formation of proto-domains of false and true vacuum separated by domain walls of thickness determined by the mass scale of the model. The cosmological evolution of the walls is extremely sensitive to the magnitude of the biasing; several scenarios are possible, depending on the interplay between the surface tension on the walls and the volume pressure from the biasing. Walls may disappear almost immediately after they form, or may live long enough to dominate the energy density of the Universe and cause power-law inflation. Limits are obtained on the biasing that characterizes each possible scenario.
Recognition bias and the physical attractiveness stereotype.
Rohner, Jean-Christophe; Rasmussen, Anders
2012-06-01
Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon.
Addressing PCR Biases in Environmental Microbiology Studies
Sipos, Rita; Székely, Anna; Révész, Sára; Márialigeti, Károly
Each step of a molecular environmental microbiology study is prone to errors, though the qualitative and quantitative biases of PCR amplification could result in the most serious biases. One has to be aware of this fact, and well-characterized PCR biases have to be avoided by using target-optimized PCR protocols. The most important tasks are primer and thermal profile optimization. We have shown that primer mismatches, even in the case of universal primers, can cause almost complete missing of common taxa from clone libraries, for example. Similarly high annealing temperatures can drastically distort community composition of the sample in the PCR product. Strategies of primer selection and PCR thermal profile design are discussed in detail.
Racial bias in perceptions of others' pain.
Directory of Open Access Journals (Sweden)
Sophie Trawalter
Full Text Available The present work provides evidence that people assume a priori that Blacks feel less pain than do Whites. It also demonstrates that this bias is rooted in perceptions of status and the privilege (or hardship status confers, not race per se. Archival data from the National Football League injury reports reveal that, relative to injured White players, injured Black players are deemed more likely to play in a subsequent game, possibly because people assume they feel less pain. Experiments 1-4 show that White and Black Americans-including registered nurses and nursing students-assume that Black people feel less pain than do White people. Finally, Experiments 5 and 6 provide evidence that this bias is rooted in perceptions of status, not race per se. Taken together, these data have important implications for understanding race-related biases and healthcare disparities.
Skill-Biased Technological Change in Denmark
DEFF Research Database (Denmark)
Malchow-Møller, Nikolaj; Rose Skaksen, Jan
2003-01-01
information aboutfuture labour requirements, as the relative importance of these industries must be expectedto grow, thereby reinforcing the shift in demand for skilled labour.JEL Classification: J24, J31, L6Keywords: skill-biased technological change, Danish industries......Skill-Biased Technological Change in Denmark:A Disaggregate Perspective@*In this paper, we provide an industry-level analysis of skill-biased technological change(SBTC) in Denmark over the last two decades. The analysis shows that SBTC has variedconsiderably across industries, and traditionally...... large Danish industries have experiencedrelatively less SBTC. This may partly explain why wage inequality between skilled and lessskilled has risen less in Denmark than in other countries. We also find that SBTC has beenconcentrated in already skill-intensive industries. This contains important...
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.
Recursive bias estimation for high dimensional smoothers
Energy Technology Data Exchange (ETDEWEB)
Hengartner, Nicolas W [Los Alamos National Laboratory; Matzner-lober, Eric [UHB, FRANCE; Cornillon, Pierre - Andre [INRA
2008-01-01
In multivariate nonparametric analysis, sparseness of the covariates also called curse of dimensionality, forces one to use large smoothing parameters. This leads to biased smoothers. Instead of focusing on optimally selecting the smoothing parameter, we fix it to some reasonably large value to ensure an over-smoothing of the data. The resulting smoother has a small variance but a substantial bias. In this paper, we propose to iteratively correct the bias initial estimator by an estimate of the latter obtained by smoothing the residuals. We examine in detail the convergence of the iterated procedure for classical smoothers and relate our procedure to L{sub 2}-Boosting. We apply our method to simulated and real data and show that our method compares favorably with existing procedures.
Validation of models with constant bias: an applied approach
Directory of Open Access Journals (Sweden)
Salvador Medina-Peralta
2014-06-01
Full Text Available Objective. This paper presents extensions to the statistical validation method based on the procedure of Freese when a model shows constant bias (CB in its predictions and illustrate the method with data from a new mechanistic model that predict weight gain in cattle. Materials and methods. The extensions were the hypothesis tests and maximum anticipated error for the alternative approach, and the confidence interval for a quantile of the distribution of errors. Results. The model evaluated showed CB, once the CB is removed and with a confidence level of 95%, the magnitude of the error does not exceed 0.575 kg. Therefore, the validated model can be used to predict the daily weight gain of cattle, although it will require an adjustment in its structure based on the presence of CB to increase the accuracy of its forecasts. Conclusions. The confidence interval for the 1-α quantile of the distribution of errors after correcting the constant bias, allows determining the top limit for the magnitude of the error of prediction and use it to evaluate the evolution of the model in the forecasting of the system. The confidence interval approach to validate a model is more informative than the hypothesis tests for the same purpose.
Bias modulated scanning ion conductance microscopy.
McKelvey, Kim; Perry, David; Byers, Joshua C; Colburn, Alex W; Unwin, Patrick R
2014-04-01
Nanopipets are versatile tools for nanoscience, particularly when used in scanning ion conductance microscopy (SICM) to determine, in a noncontact manner, the topography of a sample. We present a new method, applying an oscillating bias between a quasi-reference counter electrode (QRCE) in the SICM nanopipet probe and a second QRCE in the bulk solution, to generate a feedback signal to control the distance between the end of a nanopipet and a surface. Both the amplitude and phase of the oscillating ion current, induced by the oscillating bias and extracted using a phase-sensitive detector, are shown to be sensitive to the probe-surface distance and are used to provide stable feedback signals. The phase signal is particularly sensitive at high frequencies of the oscillating bias (up to 30 kHz herein). This development eliminates the need to physically oscillate the probe to generate an oscillating ion current feedback signal, as needed for conventional SICM modes. Moreover, bias modulation allows a feedback signal to be generated without any net ion current flow, ensuring that any polarization of the quasi reference counter electrodes, electro-osmotic effects, and perturbations of the supporting electrolyte composition are minimized. Both feedback signals, magnitude and phase, are analyzed through approach curve measurements to different surfaces at a range of distinct frequencies and via impedance measurements at different distances from a surface. The bias modulated response is readily understood via a simple equivalent circuit model. Bias modulated (BM)-SICM is compared to conventional SICM imaging through measurements of substrates with distinct topographical features and yields equivalent results. Finally, BM-SICM with both amplitude and phase feedback is used for topographical imaging of subtle etch features in a calcite crystal surface. The 2 modes yield similar results, but phase-detection opens up the prospect of faster imaging.
Godleski, Stephanie A.; Ostrov, Jamie M.
2010-01-01
The present study used both categorical and dimensional approaches to test the association between relational and physical aggression and hostile intent attributions for both relational and instrumental provocation situations using the National Institute of Child Health and Human Development longitudinal Study of Early Child Care and Youth…
Grandfather regulations, new source bias, and state air toxics regulations
Energy Technology Data Exchange (ETDEWEB)
Levinson, Arik [University of Wisconsin Economics Department, 1180 Observatory Drive, Madison, WI 53706 (United States)
1999-02-01
This paper uses plant-level data from the Census of Manufactures and the variation in toxic air pollution regulations across states to measure the effects of laws that are more stringent for new sources of pollution than for existing sources (so-called `grandfather` regulations). Of particular interest is the resulting `new source bias` and its effects on capital vintage and investment. Two industries are examined: commercial printing, which has a local product market; and paint manufacturing, which has a more national market. In general, there seem to be no statistically significant differences in capital vintage or investment between plants in states that grandfather new sources of pollution, plants in states that have no air toxics regulations, and plants in states that regulate both new and existing sources
Pseudo exchange bias due to rotational anisotropy
Ehrmann, A.; Komraus, S.; Blachowicz, T.; Domino, K.; Nees, M. K.; Jakobs, P. J.; Leiste, H.; Mathes, M.; Schaarschmidt, M.
2016-08-01
Ferromagnetic nanostructure arrays with particle dimensions between 160 nm and 400 nm were created by electron-beam lithography. The permalloy structures consist of rectangular-shaped walls around a square open space. While measuring their magnetic properties using the Magneto-Optical Kerr Effect (MOKE), in some angular regions an exchange bias (EB) seemed to appear. This paper gives an overview of possible reasons for this "pseudo exchange bias" and shows experimentally and by means of micromagnetic simulations that this effect can be attributed to unintentionally measuring minor loops.
Terahertz Bloch oscillator with a modulated bias.
Hyart, Timo; Alexeeva, Natalia V; Mattas, Jussi; Alekseev, Kirill N
2009-04-10
Electrons performing Bloch oscillations in an energy band of a dc-biased superlattice in the presence of weak dissipation can potentially generate THz fields at room temperature. The realization of such a Bloch oscillator is a long-standing problem due to the instability of a homogeneous electric field in conditions of negative differential conductivity. We establish the theoretical feasibility of stable THz gain in a long superlattice device in which the bias is quasistatically modulated by microwave fields. The modulation waveforms must have at least two harmonics in their spectra.
Optimal design of APD biasing circuit
Institute of Scientific and Technical Information of China (English)
SUN Chun-sheng; QIN Shi-qiao; WANG Xing-shu; ZHU Dong-hua
2007-01-01
This paper proposes a control method for avalanche photodiode (APD) reverse bias with temperature compensation and load resistance compensation. The influence of background light and load resistance on APD detection circuit is analyzed in detail. A theoretical model of temperature compensation and load resistance compensation is established, which is used for APD biasing circuit designing. It is predicted that this control method is especially suitable for LD laser range finder used on vehicles. Experimental results confirm thatthe design proposed in this paper can considerablely improve the performance of range finder.
Liao, Tim Futing
2011-01-01
An incomparably useful examination of statistical methods for comparisonThe nature of doing science, be it natural or social, inevitably calls for comparison. Statistical methods are at the heart of such comparison, for they not only help us gain understanding of the world around us but often define how our research is to be carried out. The need to compare between groups is best exemplified by experiments, which have clearly defined statistical methods. However, true experiments are not always possible. What complicates the matter more is a great deal of diversity in factors that are not inde
Mauro, John
2013-01-01
Written to reveal statistical deceptions often thrust upon unsuspecting journalists, this book views the use of numbers from a public perspective. Illustrating how the statistical naivete of journalists often nourishes quantitative misinformation, the author's intent is to make journalists more critical appraisers of numerical data so that in reporting them they do not deceive the public. The book frequently uses actual reported examples of misused statistical data reported by mass media and describes how journalists can avoid being taken in by them. Because reports of survey findings seldom g
Statistics of football dynamics
Mendes, R S; Anteneodo, C
2007-01-01
We investigate the dynamics of football matches. Our goal is to characterize statistically the temporal sequence of ball movements in this collective sport game, searching for traits of complex behavior. Data were collected over a variety of matches in South American, European and World championships throughout 2005 and 2006. We show that the statistics of ball touches presents power-law tails and can be described by $q$-gamma distributions. To explain such behavior we propose a model that provides information on the characteristics of football dynamics. Furthermore, we discuss the statistics of duration of out-of-play intervals, not directly related to the previous scenario.
Commentary: statistics for biomarkers.
Lovell, David P
2012-05-01
This short commentary discusses Biomarkers' requirements for the reporting of statistical analyses in submitted papers. It is expected that submitters will follow the general instructions of the journal, the more detailed guidance given by the International Committee of Medical Journal Editors, the specific guidelines developed by the EQUATOR network, and those of various specialist groups. Biomarkers expects that the study design and subsequent statistical analyses are clearly reported and that the data reported can be made available for independent assessment. The journal recognizes that there is continuing debate about different approaches to statistical science. Biomarkers appreciates that the field continues to develop rapidly and encourages the use of new methodologies.
Young, M.; Koslovsky, M.; Schaefer, Caroline M.; Feiveson, A. H.
2017-01-01
Back by popular demand, the JSC Biostatistics Laboratory and LSAH statisticians are offering an opportunity to discuss your statistical challenges and needs. Take the opportunity to meet the individuals offering expert statistical support to the JSC community. Join us for an informal conversation about any questions you may have encountered with issues of experimental design, analysis, or data visualization. Get answers to common questions about sample size, repeated measures, statistical assumptions, missing data, multiple testing, time-to-event data, and when to trust the results of your analyses.
Approximating Stationary Statistical Properties
Institute of Scientific and Technical Information of China (English)
Xiaoming WANG
2009-01-01
It is well-known that physical laws for large chaotic dynamical systems are revealed statistically. Many times these statistical properties of the system must be approximated numerically. The main contribution of this manuscript is to provide simple and natural criterions on numerical methods (temporal and spatial discretization) that are able to capture the stationary statistical properties of the underlying dissipative chaotic dynamical systems asymptotically. The result on temporal approximation is a recent finding of the author, and the result on spatial approximation is a new one. Applications to the infinite Prandtl number model for convection and the barotropic quasi-geostrophic model are also discussed.
Statistics a complete introduction
Graham, Alan
2013-01-01
Statistics: A Complete Introduction is the most comprehensive yet easy-to-use introduction to using Statistics. Written by a leading expert, this book will help you if you are studying for an important exam or essay, or if you simply want to improve your knowledge. The book covers all the key areas of Statistics including graphs, data interpretation, spreadsheets, regression, correlation and probability. Everything you will need is here in this one book. Each chapter includes not only an explanation of the knowledge and skills you need, but also worked examples and test questions.
Siegel, Andrew
2011-01-01
Practical Business Statistics, Sixth Edition, is a conceptual, realistic, and matter-of-fact approach to managerial statistics that carefully maintains-but does not overemphasize-mathematical correctness. The book offers a deep understanding of how to learn from data and how to deal with uncertainty while promoting the use of practical computer applications. This teaches present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand the concepts at hand and to interpret results. The text uses excellent examples with
Multivariate Statistical Process Control
DEFF Research Database (Denmark)
Kulahci, Murat
2013-01-01
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...
Wallis, W Allen
2014-01-01
Focusing on everyday applications as well as those of scientific research, this classic of modern statistical methods requires little to no mathematical background. Readers develop basic skills for evaluating and using statistical data. Lively, relevant examples include applications to business, government, social and physical sciences, genetics, medicine, and public health. ""W. Allen Wallis and Harry V. Roberts have made statistics fascinating."" - The New York Times ""The authors have set out with considerable success, to write a text which would be of interest and value to the student who,
D'Alessio, Michael
2012-01-01
AP Statistics Crash Course - Gets You a Higher Advanced Placement Score in Less Time Crash Course is perfect for the time-crunched student, the last-minute studier, or anyone who wants a refresher on the subject. AP Statistics Crash Course gives you: Targeted, Focused Review - Study Only What You Need to Know Crash Course is based on an in-depth analysis of the AP Statistics course description outline and actual Advanced Placement test questions. It covers only the information tested on the exam, so you can make the most of your valuable study time. Our easy-to-read format covers: exploring da
Evolutionary Statistical Procedures
Baragona, Roberto; Poli, Irene
2011-01-01
This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions a
Relative Age Effect in Elite Sports: Methodological Bias or Real Discrimination?
Delorme, Nicolas; Raspaud, Michel; 10.1080/17461390903271584
2010-01-01
Sport sciences researchers talk about a relative age effect when they observe a biased distribution of elite athletes' birthdates, with an over-representation of those born at the beginning of the competitive year and an under-representation of those born at the end. Using the whole sample of the French male licensed soccer players (n = 1,831,524), our study suggests that there could be an important bias in the statistical test of this effect. This bias could in turn lead to falsely conclude to a systemic discrimination in the recruitment of professional players. Our findings question the accuracy of past results concerning the existence of this effect at the elite level.
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.
Directory of Open Access Journals (Sweden)
Mahmood Yahyazadehfar
2012-11-01
Full Text Available The purpose of this study is investigating the Status Quo Bias (SQB from suggested biases in behavioral finance. People who are subject to a SQB tend to choose an alternative that was chosen previously (i.e., their status quo even if it is not the optimal choice any more. Status quo bias existence was investigated in this study using Ruenzi and Kempf (2005 model among investment companies listed in Tehran's Stock Exchange during 2003-2010. The data is collected quarterly from investment companies. Also, Stata10.0 software package is used for statistical analysis. The result shows the existence of a SQB is not found in Tehran Stock Exchange
Trigger monitoring and rate predictions using Enhanced Bias data from the ATLAS Detector at the LHC
The ATLAS collaboration
2016-01-01
A data-driven method for performing offline rate and CPU usage predictions for any algorithmic selection in the ATLAS High Level Trigger at the Large Hadron Collider is described. To assure statistical sensitivity in the most relevant kinematic regions, a mix of events is selected by the Level 1 trigger system that emphasises higher energies and object multiplicities. This sample, referred to as `enhanced bias', is constructed in such a way that the selection bias is removable with event weights. The use of enhanced bias data to calculate the rates of HLT trigger chains along with complex combinations such as group rates, the total rate and unique rates is described, along with methods for performing extrapolations of rates to different instantaneous luminosities and for performing predictions of trigger CPU usage. The process by which ATLAS collects and processes monitoring data in the High Level Trigger is outlined, this allows for CPU and readout system resource utilisation within the trigger to be studied...
Directory of Open Access Journals (Sweden)
Adam Zaremba
2011-07-01
Full Text Available Managed futures are an alternative asset class which has recently became considerably popular among investment industry. However, due to its characteristics, access to managed futures historical performance statistics is relatively confined. All available information originates from commercial and academic databases, reporting to which is entirely voluntary. This situation results in series of biases which distort the managed futures performance in the eyes of investors. The paper consists of two parts. First, the author reviews and describes various biases that influence the reliability of the managed futures indices and databases. The second section encompasses author’s proposals of potential enhancements, which aim to reduce the impact of the biases in order to derive a benchmark that could better reflect characteristics of managed futures investment from the point of view of a potential investor.
UN Data- Environmental Statistics: Waste
World Wide Human Geography Data Working Group — The Environment Statistics Database contains selected water and waste statistics by country. Statistics on water and waste are based on official statistics supplied...
UN Data: Environment Statistics: Waste
World Wide Human Geography Data Working Group — The Environment Statistics Database contains selected water and waste statistics by country. Statistics on water and waste are based on official statistics supplied...
Testa, Massimo
2015-01-01
Based on the fundamental principles of Relativistic Quantum Mechanics, we give a rigorous, but completely elementary, proof of the relation between fundamental observables of a statistical system when measured relatively to two inertial reference frames, connected by a Lorentz transformation.
Grégoire, G.
2016-05-01
This chapter is devoted to two objectives. The first one is to answer the request expressed by attendees of the first Astrostatistics School (Annecy, October 2013) to be provided with an elementary vademecum of statistics that would facilitate understanding of the given courses. In this spirit we recall very basic notions, that is definitions and properties that we think sufficient to benefit from courses given in the Astrostatistical School. Thus we give briefly definitions and elementary properties on random variables and vectors, distributions, estimation and tests, maximum likelihood methodology. We intend to present basic ideas in a hopefully comprehensible way. We do not try to give a rigorous presentation, and due to the place devoted to this chapter, can cover only a rather limited field of statistics. The second aim is to focus on some statistical tools that are useful in classification: basic introduction to Bayesian statistics, maximum likelihood methodology, Gaussian vectors and Gaussian mixture models.
Müller-Kirsten, Harald J W
2013-01-01
Statistics links microscopic and macroscopic phenomena, and requires for this reason a large number of microscopic elements like atoms. The results are values of maximum probability or of averaging. This introduction to statistical physics concentrates on the basic principles, and attempts to explain these in simple terms supplemented by numerous examples. These basic principles include the difference between classical and quantum statistics, a priori probabilities as related to degeneracies, the vital aspect of indistinguishability as compared with distinguishability in classical physics, the differences between conserved and non-conserved elements, the different ways of counting arrangements in the three statistics (Maxwell-Boltzmann, Fermi-Dirac, Bose-Einstein), the difference between maximization of the number of arrangements of elements, and averaging in the Darwin-Fowler method. Significant applications to solids, radiation and electrons in metals are treated in separate chapters, as well as Bose-Eins...
Gumbel, E J
2012-01-01
This classic text covers order statistics and their exceedances; exact distribution of extremes; the 1st asymptotic distribution; uses of the 1st, 2nd, and 3rd asymptotes; more. 1958 edition. Includes 44 tables and 97 graphs.
... Websites About Us Information For... Media Policy Makers Data & Statistics Recommend on Facebook Tweet Share Compartir Sickle ... Findings Feature Articles Key Findings: CDCâ€™s Sickle Cell Data Collection Program Data Useful in Describing Patterns of ...
Playing at Statistical Mechanics
Clark, Paul M.; And Others
1974-01-01
Discussed are the applications of counting techniques of a sorting game to distributions and concepts in statistical mechanics. Included are the following distributions: Fermi-Dirac, Bose-Einstein, and most probable. (RH)
Ehrlichiosis: Statistics and Epidemiology
... a tick Diseases transmitted by ticks Statistics and Epidemiology Recommend on Facebook Tweet Share Compartir On this ... Holman RC, McQuiston JH, Krebs JW, Swerdlow DL. Epidemiology of human ehrlichiosis and anaplasmosis in the United ...
Anaplasmosis: Statistics and Epidemiology
... a tick Diseases transmitted by ticks Statistics and Epidemiology Recommend on Facebook Tweet Share Compartir On this ... Holman RC, McQuiston JH, Krebs JW, Swerdlow DL. Epidemiology of human ehrlichiosis and anaplasmosis in the United ...
Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...
Medicaid Drug Claims Statistics
U.S. Department of Health & Human Services — The Medicaid Drug Claims Statistics CD is a useful tool that conveniently breaks up Medicaid claim counts and separates them by quarter and includes an annual count.
Richfield, Jon; bookfeller
2016-07-01
In reply to Ralph Kenna and Pádraig Mac Carron's feature article “Maths meets myths” in which they describe how they are using techniques from statistical physics to characterize the societies depicted in ancient Icelandic sagas.
U.S. Department of Health & Human Services — This section contains statistical information and reports related to the percentage of electronic transactions being sent to Medicare contractors in the formats...
CMS Statistics Reference Booklet
U.S. Department of Health & Human Services — The annual CMS Statistics reference booklet provides a quick reference for summary information about health expenditures and the Medicare and Medicaid health...
Information theory and statistics
Kullback, Solomon
1997-01-01
Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.
... gov Disability.gov Freedom of Information Act | Privacy & Security Statement | Disclaimers | Customer Survey | Important Web Site Notices U.S. Bureau of Labor Statistics | Postal Square Building, 2 Massachusetts Avenue, NE Washington, ...
Statistics For Neuroscientists
Directory of Open Access Journals (Sweden)
Subbakrishna D.K
2000-01-01
Full Text Available The role statistical methods play in medicine in the interpretation of empirical data is well recognized by researchers. With modern computing facilities and software packages there is little need for familiarity with the computational details of statistical calculations. However, for the researcher to understand whether these calculations are valid and appropriate it is necessary that the user is aware of the rudiments of the statistical methodology. Also, it needs to be emphasized that no amount of advanced analysis can be a substitute for a properly planned and executed study. An attempt is made in this communication to discuss some of the theoretical issues that are important for the valid analysis and interpretation of precious date that are gathered. The article summarises some of the basic statistical concepts followed by illustrations from live data generated from various research projects from the department of Neurology of this Institute.
U.S. Department of Health & Human Services — The United States Cancer Statistics (USCS) online databases in WONDER provide cancer incidence and mortality data for the United States for the years since 1999, by...
Statistical mechanics of superconductivity
Kita, Takafumi
2015-01-01
This book provides a theoretical, step-by-step comprehensive explanation of superconductivity for undergraduate and graduate students who have completed elementary courses on thermodynamics and quantum mechanics. To this end, it adopts the unique approach of starting with the statistical mechanics of quantum ideal gases and successively adding and clarifying elements and techniques indispensible for understanding it. They include the spin-statistics theorem, second quantization, density matrices, the Bloch–De Dominicis theorem, the variational principle in statistical mechanics, attractive interaction, and bound states. Ample examples of their usage are also provided in terms of topics from advanced statistical mechanics such as two-particle correlations of quantum ideal gases, derivation of the Hartree–Fock equations, and Landau’s Fermi-liquid theory, among others. With these preliminaries, the fundamental mean-field equations of superconductivity are derived with maximum mathematical clarity based on ...
DEFF Research Database (Denmark)
Lindström, Erik; Madsen, Henrik; Nielsen, Jan Nygaard
Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics...... that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical......, identify interest rate models, value bonds, estimate parameters, and much more. This textbook will help students understand and manage empirical research in financial engineering. It includes examples of how the statistical tools can be used to improve value-at-risk calculations and other issues...
Harrison, JM; Robbins, JM; 10.1098/rspa.2010.0254
2011-01-01
Quantum graphs are commonly used as models of complex quantum systems, for example molecules, networks of wires, and states of condensed matter. We consider quantum statistics for indistinguishable spinless particles on a graph, concentrating on the simplest case of abelian statistics for two particles. In spite of the fact that graphs are locally one-dimensional, anyon statistics emerge in a generalized form. A given graph may support a family of independent anyon phases associated with topologically inequivalent exchange processes. In addition, for sufficiently complex graphs, there appear new discrete-valued phases. Our analysis is simplified by considering combinatorial rather than metric graphs -- equivalently, a many-particle tight-binding model. The results demonstrate that graphs provide an arena in which to study new manifestations of quantum statistics. Possible applications include topological quantum computing, topological insulators, the fractional quantum Hall effect, superconductivity and molec...
Scheck, Florian
2016-01-01
Scheck’s textbook starts with a concise introduction to classical thermodynamics, including geometrical aspects. Then a short introduction to probabilities and statistics lays the basis for the statistical interpretation of thermodynamics. Phase transitions, discrete models and the stability of matter are explained in great detail. Thermodynamics has a special role in theoretical physics. Due to the general approach of thermodynamics the field has a bridging function between several areas like the theory of condensed matter, elementary particle physics, astrophysics and cosmology. The classical thermodynamics describes predominantly averaged properties of matter, reaching from few particle systems and state of matter to stellar objects. Statistical Thermodynamics covers the same fields, but explores them in greater depth and unifies classical statistical mechanics with quantum theory of multiple particle systems. The content is presented as two tracks: the fast track for master students, providing the essen...
LBVs and Statistical Inference
Davidson, Kris; Weis, Kerstin
2016-01-01
Smith and Tombleson (2015) asserted that statistical tests disprove the standard view of LBVs, and proposed a far more complex scenario to replace it. But Humphreys et al. (2016) showed that Smith and Tombleson's Magellanic "LBV" sample was a mixture of physically different classes of stars, and genuine LBVs are in fact statistically consistent with the standard view. Smith (2016) recently objected at great length to this result. Here we note that he misrepresented some of the arguments, altered the test criteria, ignored some long-recognized observational facts, and employed inadequate statistical procedures. This case illustrates the dangers of uncareful statistical sampling, as well as the need to be wary of unstated assumptions.
Probability and Statistical Inference
Prosper, Harrison B.
2006-01-01
These lectures introduce key concepts in probability and statistical inference at a level suitable for graduate students in particle physics. Our goal is to paint as vivid a picture as possible of the concepts covered.
Directory of Open Access Journals (Sweden)
Gerben ter Riet
Full Text Available CONTEXT: Publication bias jeopardizes evidence-based medicine, mainly through biased literature syntheses. Publication bias may also affect laboratory animal research, but evidence is scarce. OBJECTIVES: To assess the opinion of laboratory animal researchers on the magnitude, drivers, consequences and potential solutions for publication bias. And to explore the impact of size of the animals used, seniority of the respondent, working in a for-profit organization and type of research (fundamental, pre-clinical, or both on those opinions. DESIGN: Internet-based survey. SETTING: All animal laboratories in The Netherlands. PARTICIPANTS: Laboratory animal researchers. MAIN OUTCOME MEASURE(S: Median (interquartile ranges strengths of beliefs on 5 and 10-point scales (1: totally unimportant to 5 or 10: extremely important. RESULTS: Overall, 454 researchers participated. They considered publication bias a problem in animal research (7 (5 to 8 and thought that about 50% (32-70 of animal experiments are published. Employees (n = 21 of for-profit organizations estimated that 10% (5 to 50 are published. Lack of statistical significance (4 (4 to 5, technical problems (4 (3 to 4, supervisors (4 (3 to 5 and peer reviewers (4 (3 to 5 were considered important reasons for non-publication (all on 5-point scales. Respondents thought that mandatory publication of study protocols and results, or the reasons why no results were obtained, may increase scientific progress but expected increased bureaucracy. These opinions did not depend on size of the animal used, seniority of the respondent or type of research. CONCLUSIONS: Non-publication of "negative" results appears to be prevalent in laboratory animal research. If statistical significance is indeed a main driver of publication, the collective literature on animal experimentation will be biased. This will impede the performance of valid literature syntheses. Effective, yet efficient systems should be explored to
Introductory statistical inference
Mukhopadhyay, Nitis
2014-01-01
This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques.Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of dist
Business statistics I essentials
Clark, Louise
2014-01-01
REA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Business Statistics I includes descriptive statistics, introduction to probability, probability distributions, sampling and sampling distributions, interval estimation, and hypothesis t
Dominican Republic; Statistical Appendix
International Monetary Fund
2003-01-01
In this paper, statistical data for the Dominican Republic were presented as real, public, financial, and external sectors. In real sector, GDP by sector at constant prices, savings, investment, consumer price index, petroleum statistics, and so on, were outlined. The public sector summarizes operations of the consolidated public sector, central government, and revenues. A summary of the banking system, claims, interest rates, financial indicators, and reserve requirements were described in t...
2010-01-01
Abstract Background For years the Robert Koch Institute (RKI) has been annually pooling and reviewing the data from the German population-based cancer registries and evaluating them together with the cause-of-death statistics provided by the statistical offices. Traditionally, the RKI periodically estimates the number of new cancer cases in Germany on the basis of the available data from the regional cancer registries in which registration is complete; this figure, in turn, forms the basis fo...
Addressing mathematics & statistics anxiety
Kotecha, Meena
2015-01-01
This paper should be of interest to mathematics and statistics educators ranging from pre-university to university education sectors. It will discuss some features of the author’s teaching model developed over her longitudinal study conducted to understand and address mathematics and statistics anxiety, which is one of the main barriers to engaging with these subjects especially in non-specialist undergraduates. It will demonstrate how a range of formative assessments are used to kindle, as w...
Johnson, Norman
This is author-approved bcc: This is the third volume of a collection of seminal papers in the statistical sciences written during the past 110 years. These papers have each had an outstanding influence on the development of statistical theory and practice over the last century. Each paper is preceded by an introduction written by an authority in the field providing background information and assessing its influence. Volume III concerntrates on articles from the 1980's while including some earlier articles not included in Volume I and II. Samuel Kotz is Professor of Statistics in the College of Business and Management at the University of Maryland. Norman L. Johnson is Professor Emeritus of Statistics at the University of North Carolina. Also available: Breakthroughs in Statistics Volume I: Foundations and Basic Theory Samuel Kotz and Norman L. Johnson, Editors 1993. 631 pp. Softcover. ISBN 0-387-94037-5 Breakthroughs in Statistics Volume II: Methodology and Distribution Samuel Kotz and Norman L. Johnson, Edi...
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.
Zhang, Xuefeng; Zhang, Shaoqing; Liu, Zhengyu; Wu, Xinrong; Han, Guijun
2016-09-01
Imperfect physical parameterization schemes are an important source of model bias in a coupled model and adversely impact the performance of model simulation. With a coupled ocean-atmosphere-land model of intermediate complexity, the impact of imperfect parameter estimation on model simulation with biased physics has been studied. Here, the biased physics is induced by using different outgoing longwave radiation schemes in the assimilation and "truth" models. To mitigate model bias, the parameters employed in the biased longwave radiation scheme are optimized using three different methods: least-squares parameter fitting (LSPF), single-valued parameter estimation and geography-dependent parameter optimization (GPO), the last two of which belong to the coupled model parameter estimation (CMPE) method. While the traditional LSPF method is able to improve the performance of coupled model simulations, the optimized parameter values from the CMPE, which uses the coupled model dynamics to project observational information onto the parameters, further reduce the bias of the simulated climate arising from biased physics. Further, parameters estimated by the GPO method can properly capture the climate-scale signal to improve the simulation of climate variability. These results suggest that the physical parameter estimation via the CMPE scheme is an effective approach to restrain the model climate drift during decadal climate predictions using coupled general circulation models.
Assessing Projection Bias in Consumers' Food Preferences.
Directory of Open Access Journals (Sweden)
Tiziana de-Magistris
Full Text Available The aim of this study is to test whether projection bias exists in consumers' purchasing decisions for food products. To achieve our aim, we used a non-hypothetical experiment (i.e., experimental auction, where hungry and non-hungry participants were incentivized to reveal their willingness to pay (WTP. The results confirm the existence of projection bias when consumers made their decisions on food products. In particular, projection bias existed because currently hungry participants were willing to pay a higher price premium for cheeses than satiated ones, both in hungry and satiated future states. Moreover, participants overvalued the food product more when they were delivered in the future hungry condition than in the satiated one. Our study provides clear, quantitative and meaningful evidence of projection bias because our findings are based on economic valuation of food preferences. Indeed, the strength of this study is that findings are expressed in terms of willingness to pay which is an interpretable amount of money.
Biased Language: The Urge to Purge.
Maculaitis, Jean D'Arcy
Issues of social discrimination of all kinds and in all forms in teaching are discussed. Sexism, racism, ageism, bias by commission versus omission, other objectionable stereotypes, and the difference between accurate portrayal and the ideal are defined. Sixteen suggestions are given for choosing or developing language arts instructional materials…
Intergroup Bias in Parliamentary Rule Enforcement
DEFF Research Database (Denmark)
Hjorth, Frederik Georg
2016-01-01
Parliament chairmen drawn from parliamentary parties enforce speaking time. Analyzing 5,756 speeches scraped from online transcripts, I provide evidence that speech lengths are biased in favor of the presiding chairman’s party. On average, speakers of the same party as the presiding chairman give 5 percent...
Accounting for discovery bias in genomic prediction
Our objective was to evaluate an approach to mitigating discovery bias in genomic prediction. Accuracy may be improved by placing greater emphasis on regions of the genome expected to be more influential on a trait. Methods emphasizing regions result in a phenomenon known as “discovery bias” if info...
Bias in emerging biomarkers for bipolar disorder
DEFF Research Database (Denmark)
Carvalho, A F; Köhler, C A; Fernandes, B S
2016-01-01
BACKGROUND: To date no comprehensive evaluation has appraised the likelihood of bias or the strength of the evidence of peripheral biomarkers for bipolar disorder (BD). Here we performed an umbrella review of meta-analyses of peripheral non-genetic biomarkers for BD. METHOD: The Pubmed...
Very Massive Tracers and Higher Derivative Biases
Fujita, Tomohiro; Senatore, Leonardo; Vlah, Zvonimir; Angulo, Raul
2016-01-01
Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior with exquisite precision. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a consistent framework to make predictions for LSS observables in the mildly non-linear regime. In this paper we focus on biased tracers. We argue that in calculations at a given order in the dark matter perturbations, highly biased tracers will underperform because of their larger higher derivative biases. A natural prediction of the EFTofLSS is therefore that by simply adding higher derivative biases, all tracers should perform comparably well. We implement this prediction for the halo-halo and the halo-matter power spectra at one loop, and the halo-halo-halo, halo-halo-matter, and halo-matter-matter bispectra at tree-level, and compare with simulations. We find good agreement ...
Minimum Bias and Underlying Event at CMS
Fano, Livio
2006-01-01
The prospects of measuring minimum bias collisions (MB) and studying the underlying event (UE) at CMS are discussed. Two methods are described. The first is based on the measurement of charged tracks in the transverse region with respect to a charge-particle jet. The second technique relies on the selection of muon-pair events from Drell-Yan process.
Uncovering Racial Bias in Nursing Fundamentals Textbooks.
Byrne, Michelle M.
2001-01-01
The portrayal of African Americans in nursing fundamentals textbooks was analyzed, resulting in 11 themes in the areas of history, culture, and physical assessment. Few African American leaders were included, and racial bias and stereotyping were apparent. Differences were often discussed using Eurocentric norms, and language tended to minimize…
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.
The Psychological Price of Media Bias
Babad, Elisha
2005-01-01
Media bias was investigated through the effects of a TV interviewer's preferential behavior on the image of the interviewee in the eyes of the viewers. Judges viewed a political interview with either a friendly or a hostile interviewer then rated their impressions of the interviewed politician, whose behavior was identical in all conditions. The…
Countering Gender Bias in the Media.
Lightbody, Mary
2002-01-01
Discusses gender bias created by media favoring males in science, mathematics, and technology and how female academic achievement and attitudes are effected negatively. Introduces an inquiry-based activity using media clippings in which students analyze the images in mass media and discuss their ideas on those images. (YDS)
Arratia, Richard; Goldstein, Larry; Kochman, Fred
2013-01-01
Size bias occurs famously in waiting-time paradoxes, undesirably in sampling schemes, and unexpectedly in connection with Stein's method, tightness, analysis of the lognormal distribution, Skorohod embedding, infinite divisibility, and number theory. In this paper we review the basics and survey some of these unexpected connections.
Avoiding bias in safety testing design
DEFF Research Database (Denmark)
Calow, Peter
2011-01-01
All scientists are biased, no matter what their backgrounds or affiliations, so what is it about the scientific method that overcomes this and which makes science so successful? Key features are transparency and critical peer scrutiny. These general issues will be will be considered in terms...