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Sample records for irt models fit

  1. A Comparison of Item Fit Statistics for Mixed IRT Models

    Science.gov (United States)

    Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.

    2010-01-01

    In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…

  2. Fitting Diffusion Item Response Theory Models for Responses and Response Times Using the R Package diffIRT

    Directory of Open Access Journals (Sweden)

    Dylan Molenaar

    2015-08-01

    Full Text Available In the psychometric literature, item response theory models have been proposed that explicitly take the decision process underlying the responses of subjects to psychometric test items into account. Application of these models is however hampered by the absence of general and flexible software to fit these models. In this paper, we present diffIRT, an R package that can be used to fit item response theory models that are based on a diffusion process. We discuss parameter estimation and model fit assessment, show the viability of the package in a simulation study, and illustrate the use of the package with two datasets pertaining to extraversion and mental rotation. In addition, we illustrate how the package can be used to fit the traditional diffusion model (as it has been originally developed in experimental psychology to data.

  3. Item level diagnostics and model - data fit in item response theory ...

    African Journals Online (AJOL)

    Item response theory (IRT) is a framework for modeling and analyzing item response data. Item-level modeling gives IRT advantages over classical test theory. The fit of an item score pattern to an item response theory (IRT) models is a necessary condition that must be assessed for further use of item and models that best fit ...

  4. ITEM LEVEL DIAGNOSTICS AND MODEL - DATA FIT IN ITEM ...

    African Journals Online (AJOL)

    Global Journal

    Item response theory (IRT) is a framework for modeling and analyzing item response ... data. Though, there is an argument that the evaluation of fit in IRT modeling has been ... National Council on Measurement in Education ... model data fit should be based on three types of ... prediction should be assessed through the.

  5. Explanatory IRT Analysis Using the SPIRIT Macro in SPSS

    Directory of Open Access Journals (Sweden)

    DiTrapani, Jack

    2018-04-01

    Full Text Available Item Response Theory (IRT is a modeling framework that can be applied to a large variety of research questions spanning several disciplines. To make IRT models more accessible for the general researcher, a free tool has been created that can easily conduct one-parameter logistic IRT (1PL analyses using the convenient point-and-click interface in SPSS without any required downloads or add-ons. This tool, the SPIRIT macro, can fit 1PL models with person and item covariates, DIF analyses, multidimensional models, multigroup models, rating scale models, and several other variations. Example explanatory models are presented with an applied dataset containing responses to an ADHD rating scale. Illustrations of how to fit basic 1PL models as well as two more complicated analyses using SPIRIT are given.

  6. An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models

    Science.gov (United States)

    Ames, Allison J.; Penfield, Randall D.

    2015-01-01

    Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…

  7. Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

    Science.gov (United States)

    Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

    2013-07-01

    Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

  8. Goodness-of-Fit Assessment of Item Response Theory Models

    Science.gov (United States)

    Maydeu-Olivares, Alberto

    2013-01-01

    The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…

  9. A Bayesian Beta-Mixture Model for Nonparametric IRT (BBM-IRT)

    Science.gov (United States)

    Arenson, Ethan A.; Karabatsos, George

    2017-01-01

    Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…

  10. A Model Fit Statistic for Generalized Partial Credit Model

    Science.gov (United States)

    Liang, Tie; Wells, Craig S.

    2009-01-01

    Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…

  11. equateIRT: An R Package for IRT Test Equating

    Directory of Open Access Journals (Sweden)

    Michela Battauz

    2015-12-01

    Full Text Available The R package equateIRT implements item response theory (IRT methods for equating different forms composed of dichotomous items. In particular, the IRT models included are the three-parameter logistic model, the two-parameter logistic model, the one-parameter logistic model and the Rasch model. Forms can be equated when they present common items (direct equating or when they can be linked through a chain of forms that present common items in pairs (indirect or chain equating. When two forms can be equated through different paths, a single conversion can be obtained by averaging the equating coefficients. The package calculates direct and chain equating coefficients. The averaging of direct and chain coefficients that link the same two forms is performed through the bisector method. Furthermore, the package provides analytic standard errors of direct, chain and average equating coefficients.

  12. Comparing of four IRT models when analyzing two tests for inductive reasoning

    NARCIS (Netherlands)

    de Koning, E.; Sijtsma, K.; Hamers, J.H.M.

    2002-01-01

    This article discusses the use of the nonparametric IRT Mokken models of monotone homogeneity and double monotonicity and the parametric Rasch and Verhelst models for the analysis of binary test data. First, the four IRT models are discussed and compared at the theoretical level, and for each model,

  13. The Meaning of Goodness-of-Fit Tests: Commentary on "Goodness-of-Fit Assessment of Item Response Theory Models"

    Science.gov (United States)

    Thissen, David

    2013-01-01

    In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…

  14. A person fit test for IRT models for polytomous items

    NARCIS (Netherlands)

    Glas, Cornelis A.W.; Dagohoy, A.V.

    2007-01-01

    A person fit test based on the Lagrange multiplier test is presented for three item response theory models for polytomous items: the generalized partial credit model, the sequential model, and the graded response model. The test can also be used in the framework of multidimensional ability

  15. Application of multidimensional IRT models to longitudinal data

    NARCIS (Netherlands)

    te Marvelde, J.M.; Glas, Cornelis A.W.; Van Landeghem, Georges; Van Damme, Jan

    2006-01-01

    The application of multidimensional item response theory (IRT) models to longitudinal educational surveys where students are repeatedly measured is discussed and exemplified. A marginal maximum likelihood (MML) method to estimate the parameters of a multidimensional generalized partial credit model

  16. Bayesian Estimation of the Logistic Positive Exponent IRT Model

    Science.gov (United States)

    Bolfarine, Heleno; Bazan, Jorge Luis

    2010-01-01

    A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric…

  17. Loglinear multidimensional IRT models for polytomously scired Items

    NARCIS (Netherlands)

    Kelderman, Henk

    1988-01-01

    A loglinear item response theory (IRT) model is proposed that relates polytomously scored item responses to a multidimensional latent space. Each item may have a different response function where each item response may be explained by one or more latent traits. Item response functions may follow a

  18. Loglinear multidimensional IRT models for polytomously scored items

    NARCIS (Netherlands)

    Kelderman, Henk; Rijkes, Carl P.M.; Rijkes, Carl

    1994-01-01

    A loglinear IRT model is proposed that relates polytomously scored item responses to a multidimensional latent space. The analyst may specify a response function for each response, indicating which latent abilities are necessary to arrive at that response. Each item may have a different number of

  19. IRT i pomiar edukacyjny

    Directory of Open Access Journals (Sweden)

    Bartosz Kondratek

    2013-12-01

    Full Text Available Pod nazwą „item response theory” kryje się rodzina narzędzi statystycznych wykorzystywanych do modelowania odpowiedzi na rozwiązywane zadania oraz umiejętności uczniów. Modele IRT czynią to poprzez wprowadzenie parametryzacji, która określa: właściwości zadań oraz rozkład poziomu umiejętności uczniów. W artykule przedstawiony zostanie ogólny opis jednowymiarowego modelu IRT, przybliżone zostaną najczęściej stosowane modele dla zadań ocenianych dwupunktowo (2PLM, 3PLM, 1PLM oraz wielopunktowo (GPCM, a także zarysowana zostanie problematyka estymacji poziomu umiejętności. Artykuł ma za zadanie wprowadzić czytelnika w techniczne szczegóły związane z modelowaniem IRT oraz przedstawić wybrane zastosowania praktyczne w pomiarze edukacyjnym. Wśród zastosowań praktycznych omówiono wykorzystanie IRT w analizie skomplikowanych schematów badawczych, zrównywaniu/łączeniu wyników testowych, adaptatywnym testowaniu oraz przy tworzeniu map zadań.

  20. A MATLAB Package for Markov Chain Monte Carlo with a Multi-Unidimensional IRT Model

    Directory of Open Access Journals (Sweden)

    Yanyan Sheng

    2008-11-01

    Full Text Available Unidimensional item response theory (IRT models are useful when each item is designed to measure some facet of a unified latent trait. In practical applications, items are not necessarily measuring the same underlying trait, and hence the more general multi-unidimensional model should be considered. This paper provides the requisite information and description of software that implements the Gibbs sampler for such models with two item parameters and a normal ogive form. The software developed is written in the MATLAB package IRTmu2no. The package is flexible enough to allow a user the choice to simulate binary response data with multiple dimensions, set the number of total or burn-in iterations, specify starting values or prior distributions for model parameters, check convergence of the Markov chain, as well as obtain Bayesian fit statistics. Illustrative examples are provided to demonstrate and validate the use of the software package.

  1. Fitting measurement models to vocational interest data: are dominance models ideal?

    Science.gov (United States)

    Tay, Louis; Drasgow, Fritz; Rounds, James; Williams, Bruce A

    2009-09-01

    In this study, the authors examined the item response process underlying 3 vocational interest inventories: the Occupational Preference Inventory (C.-P. Deng, P. I. Armstrong, & J. Rounds, 2007), the Interest Profiler (J. Rounds, T. Smith, L. Hubert, P. Lewis, & D. Rivkin, 1999; J. Rounds, C. M. Walker, et al., 1999), and the Interest Finder (J. E. Wall & H. E. Baker, 1997; J. E. Wall, L. L. Wise, & H. E. Baker, 1996). Item response theory (IRT) dominance models, such as the 2-parameter and 3-parameter logistic models, assume that item response functions (IRFs) are monotonically increasing as the latent trait increases. In contrast, IRT ideal point models, such as the generalized graded unfolding model, have IRFs that peak where the latent trait matches the item. Ideal point models are expected to fit better because vocational interest inventories ask about typical behavior, as opposed to requiring maximal performance. Results show that across all 3 interest inventories, the ideal point model provided better descriptions of the response process. The importance of specifying the correct item response model for precise measurement is discussed. In particular, scores computed by a dominance model were shown to be sometimes illogical: individuals endorsing mostly realistic or mostly social items were given similar scores, whereas scores based on an ideal point model were sensitive to which type of items respondents endorsed.

  2. A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.

    Science.gov (United States)

    Glas, Cees A. W.; Meijer, Rob R.

    A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution…

  3. Using R and WinBUGS to fit a generalized partial credit model for developing and evaluating patient-reported outcomes assessments.

    Science.gov (United States)

    Li, Yuelin; Baser, Ray

    2012-08-15

    The US Food and Drug Administration recently announced the final guidelines on the development and validation of patient-reported outcomes (PROs) assessments in drug labeling and clinical trials. This guidance paper may boost the demand for new PRO survey questionnaires. Henceforth, biostatisticians may encounter psychometric methods more frequently, particularly item response theory (IRT) models to guide the shortening of a PRO assessment instrument. This article aims to provide an introduction on the theory and practical analytic skills in fitting a generalized partial credit model (GPCM) in IRT. GPCM theory is explained first, with special attention to a clearer exposition of the formal mathematics than what is typically available in the psychometric literature. Then, a worked example is presented, using self-reported responses taken from the international personality item pool. The worked example contains step-by-step guides on using the statistical languages r and WinBUGS in fitting the GPCM. Finally, the Fisher information function of the GPCM model is derived and used to evaluate, as an illustrative example, the usefulness of assessment items by their information contents. This article aims to encourage biostatisticians to apply IRT models in the re-analysis of existing data and in future research. Copyright © 2012 John Wiley & Sons, Ltd.

  4. Effect of Item Response Theory (IRT) Model Selection on Testlet-Based Test Equating. Research Report. ETS RR-14-19

    Science.gov (United States)

    Cao, Yi; Lu, Ru; Tao, Wei

    2014-01-01

    The local item independence assumption underlying traditional item response theory (IRT) models is often not met for tests composed of testlets. There are 3 major approaches to addressing this issue: (a) ignore the violation and use a dichotomous IRT model (e.g., the 2-parameter logistic [2PL] model), (b) combine the interdependent items to form a…

  5. Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

    Science.gov (United States)

    Zhu, Xiaoshu

    2013-01-01

    The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

  6. Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

    Science.gov (United States)

    de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

    2010-01-01

    We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

  7. IRT-based test construction

    OpenAIRE

    van der Linden, Willem J.; Theunissen, T.J.J.M.; Boekkooi-Timminga, Ellen; Kelderman, Henk

    1987-01-01

    Four discussions of test construction based on item response theory (IRT) are presented. The first discussion, "Test Design as Model Building in Mathematical Programming" (T.J.J.M. Theunissen), presents test design as a decision process under certainty. A natural way of modeling this process leads to mathematical programming. General models of test construction are discussed, with information about algorithms and heuristics; ideas about the analysis and refinement of test constraints are also...

  8. Using the Item Response Theory (IRT) for Educational Evaluation through Games

    Science.gov (United States)

    Euzébio Batista, Marcelo Henrique; Victória Barbosa, Jorge Luis; da Rosa Tavares, João Elison; Hackenhaar, Jonathan Luis

    2013-01-01

    This article shows the application of Item Response Theory (IRT) for educational evaluation using games. The article proposes a computational model to create user profiles, called Psychometric Profile Generator (PPG). PPG uses the IRT mathematical model for exploring the levels of skills and behaviors in the form of items and/or stimuli. The model…

  9. Methodology review: evaluating person fit

    NARCIS (Netherlands)

    Meijer, R.R.; Sijtsma, Klaas

    2001-01-01

    Person-fit methods based on classical test theory-and item response theory (IRT), and methods investigating particular types of response behavior on tests, are examined. Similarities and differences among person-fit methods and their advantages and disadvantages are discussed. Sound person-fit

  10. IRT - Sofia conversion feasibility study experience 2002-2009

    Energy Technology Data Exchange (ETDEWEB)

    Belousov, S.I.; Apostolov, T.G. [Institute for Nuclear Research and Nuclear Energy of Bulgarian Academy of Science, Tsarigradsko 72, 1784 Sofia (Bulgaria)

    2010-07-01

    A joint conversion feasibility study concerning the IRT - Sofia research reactor between INRNE and the RERTR Program at ANL was initiated in 2002. The initial steps studies (up to 2006) were mainly focused on neutronics properties significant for reactor application and safety analyses. Thermal hydraulic, accident analyses as well as additional neutronics study required were performed after that (up to 2010). The obtained results show that the IRT-4M LEU fuel assemblies (19.75% {sup 235}U enrichment) are appropriate for IRT-Sofia conversion (IRT-Sofia was initially designed for the IRT-2M HEU fuel assemblies with 36% {sup 235}U enrichment). The results obtained in the frames of the joint study show that the IRT-Sofia operation even with usage of only one pump in the primary circuit meets all safety requirements at power level up to 1000 kW and that safety is maintained for accident transients. Presented results of analyses (neutronics, thermal hydraulic, and accident) and accumulated experience for the IRT-Sofia will be useful for other research reactors where conversion from IRT-2M (HEU) to IRT-4M (LEU) fuel is underway and/or foreseen. (authors)

  11. Indium-Gallium Radiation Contour of the IRT Nuclear Reactor; Circuit d'activation d'indium-gallium dans le reacteur nucleaire IRT; Indij-gallievyj radiatsionnyj kontur yadernogo reaktora IRT; Circuito de radiaciones de indio-galio del reactor IRT

    Energy Technology Data Exchange (ETDEWEB)

    Breger, A K; Ryabukin, Y S; Tulkes, S G; Volkov, E N

    1960-07-15

    Following on theoretical work already published, an indium-gallium radiation contour of the IRT nuclear reactor has been prepared, and represents a powerful new source of gamma-radiation. The first contour of this type ''RK-1'' was prepared on the IRT reactor at the Physics Institute of the Academy of Sciences of the Georgian SSR. The paper gives the activation calculations for indium-gallium alloy; the structural components of RK-1 and their arrangement in the reactor tank and the hot cell; the devise for feeding liquid and gaseous substances into the irradiation zone; and the conveyor for solid substances to be irradiated. When the IRT reactor is at a power of 2000 kW, the radiation strength of the contour is equivalent to that of a gamma-emitter having an activity of 20,000 g. Ra equivalent. The prospects for the use of the indium-gallium radiation contour for research and semi-industrial purposes are discussed. (author) [French] A la suite de la publication d'un ouvrage theorique, on a etabli autour du reacteur nucleaire IRT un circuit d'activation d'indium-gallium qui represente une nouvelle source de rayonnements gamma de grande intensite. Le premier circuit de ce type ''RK-1'' a ete etabli sur le reacteur IRT a l'Institut de physique de l'Academie des sciences de la RSS de Georgie. Les auteurs donnent les calculs de l'activation pour l'alliage indium-gallium; ils indiquent les elements structurels du RK-1 et leur disposition dans le reservoir et dans la cellule de haute activite du reacteur; ils decrivent le dispositif permettant d'introduire des substances liquides et gazeuses dans la zone d'irradiation et le systeme qui transporte les substances solides a irradier. Lorsque le reacteur IRT fonctionne a 2 000 kW, la puissance de rayonnement du circuit equivaut a celle d'un emetteur gamma ayant une activite equivalente a 20 000 grammes de radium. Les auteurs examinent les perspectives d'emploi de ce processus pour la recherche et a des fins semi

  12. Pretest-Posttest-Posttest Multilevel IRT Modeling of Competence Growth of Students in Higher Education in Germany

    NARCIS (Netherlands)

    Schmidt, Susanne; Zlatkin-Troitschanskaia, Olga; Fox, Gerardus J.A.

    2016-01-01

    Longitudinal research in higher education faces several challenges. Appropriate methods of analyzing competence growth of students are needed to deal with those challenges and thereby obtain valid results. In this article, a pretest-posttest-posttest multivariate multilevel IRT model for repeated

  13. Clinical Effect of IRT-5 Probiotics on Immune Modulation of Autoimmunity or Alloimmunity in the Eye

    Directory of Open Access Journals (Sweden)

    Jaeyoung Kim

    2017-10-01

    Full Text Available Background: Although the relation of the gut microbiota to a development of autoimmune and inflammatory diseases has been investigated in various animal models, there are limited studies that evaluate the effect of probiotics in the autoimmune eye disease. Therefore, we aimed to investigate the effect of IRT-5 probiotics consisting of Lactobacillus casei, Lactobacillus acidophilus, Lactobacillus reuteri, Bifidobacterium bifidum, and Streptococcus thermophilus on the autoimmunity of uveitis and dry eye and alloimmunity of corneal transplantation. Methods: Experimental autoimmune uveitis was induced by subcutaneous immunization with interphotoreceptor-binding protein and intraperitoneal injection of pertussis toxin in C57BL/6 (B6 mice. For an autoimmune dry eye model, 12-weeks-old NOD.B10.H2b mice were used. Donor cornea of B6 mice was transplanted into BALB/C mice. IRT-5 probiotics or phosphate buffered saline (PBS were administered for three weeks immediately after induction of uveitis or transplantation. The inflammation score of the retinal tissues, dry eye manifestations (corneal staining and tear secretion, and graft survival were measured in each model. The changes of T cells were evaluated in drainage lymph nodes using fluorescence-activated cell sorting. Results: Retinal histology score in IRT-5 group of uveitis was lower than that in PBS group (p = 0.045. Ocular staining score was lower (p < 0.0001 and tear secretion was higher (p < 0.0001 in the IRT-5 group of NOD.B10.H2b mice than that in the PBS group. However, the graft survival in the IRT-5 group was not different from those of PBS group. The percentage of regulatory T cells was increased in the IRT-5-treated dry eye models (p = 0.032. The percentage of CD8+IL-17hi (p = 0.027 and CD8+ interferon gamma (IFNγhi cells (p = 0.022 were significantly decreased in the IRT-5-treated uveitis models and the percentage of CD8+IFNγhi cells was markedly reduced (p = 0.036 in IRT-5-treated dry

  14. The person response function as a tool in person-fit research

    NARCIS (Netherlands)

    Sijtsma, Klaas; Meijer, R.R.

    2001-01-01

    Item responses that do not fit an item response theory (IRT) model may cause the latent trait value to be inaccurately estimated. In the past two decades several statistics have been proposed that can be used to identify nonfitting item score patterns. These statistics all yieldscalar values. Here,

  15. Psychometric properties for the Balanced Inventory of Desirable Responding: dichotomous versus polytomous conventional and IRT scoring.

    Science.gov (United States)

    Vispoel, Walter P; Kim, Han Yi

    2014-09-01

    [Correction Notice: An Erratum for this article was reported in Vol 26(3) of Psychological Assessment (see record 2014-16017-001). The mean, standard deviation and alpha coefficient originally reported in Table 1 should be 74.317, 10.214 and .802, respectively. The validity coefficients in the last column of Table 4 are affected as well. Correcting this error did not change the substantive interpretations of the results, but did increase the mean, standard deviation, alpha coefficient, and validity coefficients reported for the Honesty subscale in the text and in Tables 1 and 4. The corrected versions of Tables 1 and Table 4 are shown in the erratum.] Item response theory (IRT) models were applied to dichotomous and polytomous scoring of the Self-Deceptive Enhancement and Impression Management subscales of the Balanced Inventory of Desirable Responding (Paulhus, 1991, 1999). Two dichotomous scoring methods reflecting exaggerated endorsement and exaggerated denial of socially desirable behaviors were examined. The 1- and 2-parameter logistic models (1PLM, 2PLM, respectively) were applied to dichotomous responses, and the partial credit model (PCM) and graded response model (GRM) were applied to polytomous responses. For both subscales, the 2PLM fit dichotomous responses better than did the 1PLM, and the GRM fit polytomous responses better than did the PCM. Polytomous GRM and raw scores for both subscales yielded higher test-retest and convergent validity coefficients than did PCM, 1PLM, 2PLM, and dichotomous raw scores. Information plots showed that the GRM provided consistently high measurement precision that was superior to that of all other IRT models over the full range of both construct continuums. Dichotomous scores reflecting exaggerated endorsement of socially desirable behaviors provided noticeably weak precision at low levels of the construct continuums, calling into question the use of such scores for detecting instances of "faking bad." Dichotomous

  16. Assessment of health surveys: fitting a multidimensional graded response model.

    Science.gov (United States)

    Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

    The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

  17. Lord-Wingersky Algorithm Version 2.0 for Hierarchical Item Factor Models with Applications in Test Scoring, Scale Alignment, and Model Fit Testing.

    Science.gov (United States)

    Cai, Li

    2015-06-01

    Lord and Wingersky's (Appl Psychol Meas 8:453-461, 1984) recursive algorithm for creating summed score based likelihoods and posteriors has a proven track record in unidimensional item response theory (IRT) applications. Extending the recursive algorithm to handle multidimensionality is relatively simple, especially with fixed quadrature because the recursions can be defined on a grid formed by direct products of quadrature points. However, the increase in computational burden remains exponential in the number of dimensions, making the implementation of the recursive algorithm cumbersome for truly high-dimensional models. In this paper, a dimension reduction method that is specific to the Lord-Wingersky recursions is developed. This method can take advantage of the restrictions implied by hierarchical item factor models, e.g., the bifactor model, the testlet model, or the two-tier model, such that a version of the Lord-Wingersky recursive algorithm can operate on a dramatically reduced set of quadrature points. For instance, in a bifactor model, the dimension of integration is always equal to 2, regardless of the number of factors. The new algorithm not only provides an effective mechanism to produce summed score to IRT scaled score translation tables properly adjusted for residual dependence, but leads to new applications in test scoring, linking, and model fit checking as well. Simulated and empirical examples are used to illustrate the new applications.

  18. Re-evaluating a vision-related quality of life questionnaire with item response theory (IRT and differential item functioning (DIF analyses

    Directory of Open Access Journals (Sweden)

    Knol Dirk L

    2011-09-01

    Full Text Available Abstract Background For the Low Vision Quality Of Life questionnaire (LVQOL it is unknown whether the psychometric properties are satisfactory when an item response theory (IRT perspective is considered. This study evaluates some essential psychometric properties of the LVQOL questionnaire in an IRT model, and investigates differential item functioning (DIF. Methods Cross-sectional data were used from an observational study among visually-impaired patients (n = 296. Calibration was performed for every dimension of the LVQOL in the graded response model. Item goodness-of-fit was assessed with the S-X2-test. DIF was assessed on relevant background variables (i.e. age, gender, visual acuity, eye condition, rehabilitation type and administration type with likelihood-ratio tests for DIF. The magnitude of DIF was interpreted by assessing the largest difference in expected scores between subgroups. Measurement precision was assessed by presenting test information curves; reliability with the index of subject separation. Results All items of the LVQOL dimensions fitted the model. There was significant DIF on several items. For two items the maximum difference between expected scores exceeded one point, and DIF was found on multiple relevant background variables. Item 1 'Vision in general' from the "Adjustment" dimension and item 24 'Using tools' from the "Reading and fine work" dimension were removed. Test information was highest for the "Reading and fine work" dimension. Indices for subject separation ranged from 0.83 to 0.94. Conclusions The items of the LVQOL showed satisfactory item fit to the graded response model; however, two items were removed because of DIF. The adapted LVQOL with 21 items is DIF-free and therefore seems highly appropriate for use in heterogeneous populations of visually impaired patients.

  19. How Often Is the Misfit of Item Response Theory Models Practically Significant?

    Science.gov (United States)

    Sinharay, Sandip; Haberman, Shelby J.

    2014-01-01

    Standard 3.9 of the Standards for Educational and Psychological Testing ([, 1999]) demands evidence of model fit when item response theory (IRT) models are employed to data from tests. Hambleton and Han ([Hambleton, R. K., 2005]) and Sinharay ([Sinharay, S., 2005]) recommended the assessment of practical significance of misfit of IRT models, but…

  20. Detection of Differential Item Functioning with Nonlinear Regression: A Non-IRT Approach Accounting for Guessing

    Science.gov (United States)

    Drabinová, Adéla; Martinková, Patrícia

    2017-01-01

    In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

  1. IRT-Estimated Reliability for Tests Containing Mixed Item Formats

    Science.gov (United States)

    Shu, Lianghua; Schwarz, Richard D.

    2014-01-01

    As a global measure of precision, item response theory (IRT) estimated reliability is derived for four coefficients (Cronbach's a, Feldt-Raju, stratified a, and marginal reliability). Models with different underlying assumptions concerning test-part similarity are discussed. A detailed computational example is presented for the targeted…

  2. Comparing Different Approaches of Bias Correction for Ability Estimation in IRT Models. Research Report. ETS RR-08-13

    Science.gov (United States)

    Lee, Yi-Hsuan; Zhang, Jinming

    2008-01-01

    The method of maximum-likelihood is typically applied to item response theory (IRT) models when the ability parameter is estimated while conditioning on the true item parameters. In practice, the item parameters are unknown and need to be estimated first from a calibration sample. Lewis (1985) and Zhang and Lu (2007) proposed the expected response…

  3. Cognitive psychology meets psychometric theory: on the relation between process models for decision making and latent variable models for individual differences.

    Science.gov (United States)

    van der Maas, Han L J; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A; Borsboom, Denny

    2011-04-01

    This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line of reasoning, we discuss the appropriateness of IRT for measuring abilities and bipolar traits, such as pro versus contra attitudes. Surprisingly, if a diffusion model underlies the response processes, IRT models are appropriate for bipolar traits but not for ability tests. A reconsideration of the concept of ability that is appropriate for such situations leads to a new item response model for accuracy and speed based on the idea that ability has a natural zero point. The model implies fundamentally new ways to think about guessing, response speed, and person fit in IRT. We discuss the relation between this model and existing models as well as implications for psychology and psychometrics. 2011 APA, all rights reserved

  4. Preliminary Analysis on the Management Options of IRT-DPRK Research Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jung-Hyun; Kim, Minsoo; Hwang, Yongsoo [Korea Institute of Nuclear Nonproliferation and Control, Daejeon (Korea, Republic of)

    2015-05-15

    Although IRT-DPRK was upgraded several times, operation lifetime was already exhausted and thus management policy is needed to deal with the aging of IRT-DPRK. For example, IRT- 2000 type nuclear reactors in Georgia and Bulgaria had been shut down to refurbish or decommissioned to establish new low power facilities. However, the existing negotiations and agreements related to the nuclear issues on North Korea have been focused on the 'denuclearization', and thus the issues on the IRTDPRK were not handled. In recent, a group of USA scientists has suggested that IRT-DPRK should be refurbished to establish the 'Scientific cent for excellence' like the Cooperative Threat Reduction program applied in Russia and the former Soviet Union (FSU). In this paper, we examined the several options to manage the IRT-DPRK through the study of similar foreign cases. Due to the lack of the detailed and standardized information, it is impossible to suggest the best option at this moment. In order to do that, the further research on the detailed procedures, radioactive wastes, the standards of safety and security are needed.

  5. IRT Item Parameter Recovery with Marginal Maximum Likelihood Estimation Using Loglinear Smoothing Models

    Science.gov (United States)

    Casabianca, Jodi M.; Lewis, Charles

    2015-01-01

    Loglinear smoothing (LLS) estimates the latent trait distribution while making fewer assumptions about its form and maintaining parsimony, thus leading to more precise item response theory (IRT) item parameter estimates than standard marginal maximum likelihood (MML). This article provides the expectation-maximization algorithm for MML estimation…

  6. Conscientiousness at the workplace: Applying mixture IRT to investigate scalability and predictive validity

    NARCIS (Netherlands)

    Egberink, I.J.L.; Meijer, R.R.; Veldkamp, Bernard P.

    2010-01-01

    Mixture item response theory (IRT) models have been used to assess multidimensionality of the construct being measured and to detect different response styles for different groups. In this study a mixture version of the graded response model was applied to investigate scalability and predictive

  7. Conscientiousness in the workplace : Applying mixture IRT to investigate scalability and predictive validity

    NARCIS (Netherlands)

    Egberink, I.J.L.; Meijer, R.R.; Veldkamp, B.P.

    Mixture item response theory (IRT) models have been used to assess multidimensionality of the construct being measured and to detect different response styles for different groups. In this study a mixture version of the graded response model was applied to investigate scalability and predictive

  8. Detecting DIF in Polytomous Items Using MACS, IRT and Ordinal Logistic Regression

    Science.gov (United States)

    Elosua, Paula; Wells, Craig

    2013-01-01

    The purpose of the present study was to compare the Type I error rate and power of two model-based procedures, the mean and covariance structure model (MACS) and the item response theory (IRT), and an observed-score based procedure, ordinal logistic regression, for detecting differential item functioning (DIF) in polytomous items. A simulation…

  9. Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions

    Directory of Open Access Journals (Sweden)

    Yoon Soo ePark

    2016-02-01

    Full Text Available This study investigates the impact of item parameter drift (IPD on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effect on item parameters and examinee ability.

  10. Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions.

    Science.gov (United States)

    Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

    2016-01-01

    This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability.

  11. A neutron radiography facility on the IRT-2000 reactor

    International Nuclear Information System (INIS)

    Khadduri, I.Y.

    1976-01-01

    A neutron radiography facility has been constructed on the thermal neutron channel of the IRT-2000 reactor. A collimated thermal neutron beam exposure area of 10 cm diameter is obtained with an L/D ratio of 48.8. The film used is cellulose nitrate coated with lithium tetraborate which is insensitive to gamma and beta radiation. Some pictures with good contrast and resolution have been obtained. Pictures of parts of an IRT-2000 reactor fuel pin have also been recorded. (orig) [de

  12. Using item response theory to investigate the structure of anticipated affect: do self-reports about future affective reactions conform to typical or maximal models?

    Science.gov (United States)

    Zampetakis, Leonidas A; Lerakis, Manolis; Kafetsios, Konstantinos; Moustakis, Vassilis

    2015-01-01

    In the present research, we used item response theory (IRT) to examine whether effective predictions (anticipated affect) conforms to a typical (i.e., what people usually do) or a maximal behavior process (i.e., what people can do). The former, correspond to non-monotonic ideal point IRT models, whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N = 1624) was used. Participants were asked to report on anticipated positive and negative affect around a hypothetical event (emotions surrounding the start of a new business). We carried out analysis comparing graded response model (GRM), a dominance IRT model, against generalized graded unfolding model, an unfolding IRT model. We found that the GRM provided a better fit to the data. Findings suggest that the self-report responses to anticipated affect conform to dominance response process (i.e., maximal behavior). The paper also discusses implications for a growing literature on anticipated affect.

  13. Using item response theory to investigate the structure of anticipated affect: Do self-reports about future affective reactions conform to typical or maximal models?

    Directory of Open Access Journals (Sweden)

    Leonidas A Zampetakis

    2015-09-01

    Full Text Available In the present research we used item response theory (IRT to examine whether effective predictions (anticipated affect conforms to a typical (i.e., what people usually do or a maximal behavior process (i.e., what people can do. The former, correspond to non-monotonic ideal point IRT models whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N=1624 was used. Participants were asked to report on anticipated positive and negative affect around a hypothetical event (emotions surrounding the start of a new business. We carried out analysis comparing Graded Response Model (GRM, a dominance IRT model, against Generalized Graded Unfolding Model (GGUM, an unfolding IRT model. We found that the GRM provided a better fit to the data. Findings suggest that the self-report responses to anticipated affect conform to dominance response process (i.e. maximal behavior. The paper also discusses implications for a growing literature on anticipated affect.

  14. Analysis Test of Understanding of Vectors with the Three-Parameter Logistic Model of Item Response Theory and Item Response Curves Technique

    Science.gov (United States)

    Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

    2016-01-01

    This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming…

  15. The Infrared-Optical Telescope (IRT) of the Exist Observatory

    Science.gov (United States)

    Kutyrev, Alexander; Bloom, Joshua; Gehrels, Neil; Golisano, Craig; Gong, Quan; Grindlay, Jonathan; Moseley, Samuel; Woodgate, Bruce

    2010-01-01

    The IRT is a 1.1m visible and infrared passively cooled telescope, which can locate, identify and obtain spectra of GRB afterglows at redshifts up to z 20. It will also acquire optical-IR, imaging and spectroscopy of AGN and transients discovered by the EXIST (The Energetic X-ray Imaging Survey Telescope). The IRT imaging and spectroscopic capabilities cover a broad spectral range from 0.32.2m in four bands. The identical fields of view in the four instrument bands are each split in three subfields: imaging, objective prism slitless for the field and objective prism single object slit low resolution spectroscopy, and high resolution long slit on single object. This allows the instrument, to do simultaneous broadband photometry or spectroscopy of the same object over the full spectral range, thus greatly improving the efficiency of the observatory and its detection limits. A prompt follow up (within three minutes) of the transient discovered by the EXIST makes IRT a unique tool for detection and study of these events, which is particularly valuable at wavelengths unavailable to the ground based observatories.

  16. Fitting PAC spectra with stochastic models: PolyPacFit

    Energy Technology Data Exchange (ETDEWEB)

    Zacate, M. O., E-mail: zacatem1@nku.edu [Northern Kentucky University, Department of Physics and Geology (United States); Evenson, W. E. [Utah Valley University, College of Science and Health (United States); Newhouse, R.; Collins, G. S. [Washington State University, Department of Physics and Astronomy (United States)

    2010-04-15

    PolyPacFit is an advanced fitting program for time-differential perturbed angular correlation (PAC) spectroscopy. It incorporates stochastic models and provides robust options for customization of fits. Notable features of the program include platform independence and support for (1) fits to stochastic models of hyperfine interactions, (2) user-defined constraints among model parameters, (3) fits to multiple spectra simultaneously, and (4) any spin nuclear probe.

  17. Comparing the IRT Pre-equating and Section Pre-equating: A Simulation Study.

    Science.gov (United States)

    Hwang, Chi-en; Cleary, T. Anne

    The results obtained from two basic types of pre-equatings of tests were compared: the item response theory (IRT) pre-equating and section pre-equating (SPE). The simulated data were generated from a modified three-parameter logistic model with a constant guessing parameter. Responses of two replication samples of 3000 examinees on two 72-item…

  18. An Investigation of Invariance Properties of One, Two and Three Parameter Logistic Item Response Theory Models

    Directory of Open Access Journals (Sweden)

    O.A. Awopeju

    2017-12-01

    Full Text Available The study investigated the invariance properties of one, two and three parame-ter logistic item response theory models. It examined the best fit among one parameter logistic (1PL, two-parameter logistic (2PL and three-parameter logistic (3PL IRT models for SSCE, 2008 in Mathematics. It also investigated the degree of invariance of the IRT models based item difficulty parameter estimates in SSCE in Mathematics across different samples of examinees and examined the degree of invariance of the IRT models based item discrimination estimates in SSCE in Mathematics across different samples of examinees. In order to achieve the set objectives, 6000 students (3000 males and 3000 females were drawn from the population of 35262 who wrote the 2008 paper 1 Senior Secondary Certificate Examination (SSCE in Mathematics organized by National Examination Council (NECO. The item difficulty and item discrimination parameter estimates from CTT and IRT were tested for invariance using BLOG MG 3 and correlation analysis was achieved using SPSS version 20. The research findings were that two parameter model IRT item difficulty and discrimination parameter estimates exhibited invariance property consistently across different samples and that 2-parameter model was suitable for all samples of examinees unlike one-parameter model and 3-parameter model.

  19. Radiation monitoring program at nuclear scientific experimental and educational center - IRT-Sofia

    International Nuclear Information System (INIS)

    Mladenov, A.; Stankov, D.; Marinov, K.; Nonova, T.; Krezhov, K.

    2012-01-01

    Ensuring minimal risk of personnel exposure without exceeding the dose limits is the main task of the General Program for Radiation Monitoring of Nuclear Scientific Experimental and Education Centre (NSEEC) with research reactor IRT. Since 2006 the IRT-Sofia is equipped with a new and modern Radiation Monitoring System (RMS). All RMS detectors are connected to the server RAMSYS. They have online (real-time) visualization in two workstations with RAMVISION software. The RMS allows the implementation of technological and environmental monitoring at the nuclear facility site. Environmental monitoring with the RMS external system includes monitoring of dose rate; alpha and beta activity; radon activity; Po-218, Po-214, Po-212 activity; gamma control of vehicles. Technological control of reactor gases includes: Alpha beta particulate monitor; Iodine monitor; Noble gases monitor; Stack flow monitor. The General Program based on the radiation monitoring system allows real-time monitoring and control of radiation parameters in the controlled area and provides for a high level of radiation protection of IRT staff and users of its facilities. This paper presents the technical and functional parameters of the radiation monitoring system and radiation protection activities within the restricted zone in IRT facilities. (authors)

  20. Measuring individual significant change on the Beck Depression Inventory-II through IRT-based statistics.

    NARCIS (Netherlands)

    Brouwer, D.; Meijer, R.R.; Zevalkink, D.J.

    2013-01-01

    Several researchers have emphasized that item response theory (IRT)-based methods should be preferred over classical approaches in measuring change for individual patients. In the present study we discuss and evaluate the use of IRT-based statistics to measure statistical significant individual

  1. Measuring Anxiety in Visually-Impaired People: A Comparison between the Linear and the Nonlinear IRT Approaches

    Science.gov (United States)

    Ferrando, Pere J.; Pallero, Rafael; Anguiano-Carrasco, Cristina

    2013-01-01

    The present study has two main interests. First, some pending issues about the psychometric properties of the CTAC (an anxiety questionnaire for blind and visually-impaired people) are assessed using item response theory (IRT). Second, the linear model is compared to the graded response model (GRM) in terms of measurement precision, sensitivity…

  2. A mixed-binomial model for Likert-type personality measures.

    Science.gov (United States)

    Allik, Jüri

    2014-01-01

    Personality measurement is based on the idea that values on an unobservable latent variable determine the distribution of answers on a manifest response scale. Typically, it is assumed in the Item Response Theory (IRT) that latent variables are related to the observed responses through continuous normal or logistic functions, determining the probability with which one of the ordered response alternatives on a Likert-scale item is chosen. Based on an analysis of 1731 self- and other-rated responses on the 240 NEO PI-3 questionnaire items, it was proposed that a viable alternative is a finite number of latent events which are related to manifest responses through a binomial function which has only one parameter-the probability with which a given statement is approved. For the majority of items, the best fit was obtained with a mixed-binomial distribution, which assumes two different subpopulations who endorse items with two different probabilities. It was shown that the fit of the binomial IRT model can be improved by assuming that about 10% of random noise is contained in the answers and by taking into account response biases toward one of the response categories. It was concluded that the binomial response model for the measurement of personality traits may be a workable alternative to the more habitual normal and logistic IRT models.

  3. Does guessing matter? Differences between ability estimates from 2PL and 3PL IRT models in case of guessing

    Directory of Open Access Journals (Sweden)

    Tomasz Żółtak

    2015-09-01

    Full Text Available Modern approaches to measuring cognitive ability and testing knowledge frequently use multiple-choice items. These can be simply and rapidly scored without problems associated with rater subjectivity. Nevertheless, multiple-choice tests are often criticized owing to their vulnerability to guessing. In this paper the impact of guessing was examined using simulation. Ability estimates were obtained from the two IRT models commonly used for binary-scored items: the two-parameter logistic model and the three-parameter logistic model. The latter approach explicitly models guessing, whilst the former does not. Rather counter-intuitively, little difference was identified for point estimates of ability from the 2PLM and 3PLM. Nevertheless, it should be noted that difficulty and discrimination parameters are severely downwardly biased if a 2PLM is used to calibrate data generated by processes involving guessing. Estimated standard errors for ability estimates also differ considerably between these models.

  4. Further Empirical Results on Parametric Versus Non-Parametric IRT Modeling of Likert-Type Personality Data

    Science.gov (United States)

    Maydeu-Olivares, Albert

    2005-01-01

    Chernyshenko, Stark, Chan, Drasgow, and Williams (2001) investigated the fit of Samejima's logistic graded model and Levine's non-parametric MFS model to the scales of two personality questionnaires and found that the graded model did not fit well. We attribute the poor fit of the graded model to small amounts of multidimensionality present in…

  5. General plan for the partial dismantling of the IRT-Sofia research reactor

    Directory of Open Access Journals (Sweden)

    Apostolov Tihomir G.

    2006-01-01

    Full Text Available After the decision of the Bulgarian Government to reconstruct it, the strategy concerning the IRT-Sofia Research Reactor is to partially dismantle the old systems and equipment. The removal of the reactor core and replacement of old equipment will not pose any significant problems. For a more efficient use of existing resources, there is a need for an engineering project which has been already prepared under the title "General Plan for the Partial Dismantling of Equipment at the IRT-Sofia as a Part of the Reconstruction into a Low Power RR".

  6. Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

    Directory of Open Access Journals (Sweden)

    Suttida Rakkapao

    2016-10-01

    Full Text Available This study investigated the multiple-choice test of understanding of vectors (TUV, by applying item response theory (IRT. The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test’s distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

  7. Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

    Science.gov (United States)

    Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

    2016-12-01

    This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC) that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test's distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

  8. Gibberellic acid alleviates cadmium toxicity by reducing nitric oxide accumulation and expression of IRT1 in Arabidopsis thaliana

    International Nuclear Information System (INIS)

    Zhu, Xiao Fang; Jiang, Tao; Wang, Zhi Wei; Lei, Gui Jie; Shi, Yuan Zhi; Li, Gui Xin; Zheng, Shao Jian

    2012-01-01

    Highlights: ► Cd reduces endogenous GA levels in Arabidopsis. ► GA exogenous applied decreases Cd accumulation in plant. ► GA suppresses the Cd-induced accumulation of NO. ► Decreased NO level downregulates the expression of IRT1. ► Suppressed IRT1 expression reduces Cd transport across plasma membrane. - Abstract: Gibberellic acid (GA) is involved in not only plant growth and development but also plant responses to abiotic stresses. Here it was found that treating the plants with GA concentrations from 0.1 to 5 μM for 24 h had no obvious effect on root elongation in the absence of cadmium (Cd), whereas in the presence of Cd 2+ , GA at 5 μM improved root growth, reduced Cd content and lipid peroxidation in the roots, indicating that GA can partially alleviate Cd toxicity. Cd 2+ increased nitric oxide (NO) accumulation in the roots, but GA remarkably reduced it, and suppressed the up-regulation of the expression of IRT1. In contrary, the beneficial effect of GA on alleviating Cd toxicity was not observed in an IRT1 knock-out mutant irt1, suggesting the involvement of IRT1 in Cd 2+ absorption. Furthermore, the GA-induced reduction of NO and Cd content can also be partially reversed by the application of a NO donor (S-nitrosoglutathione [GSNO]). Taken all these together, the results showed that GA-alleviated Cd toxicity is mediated through the reduction of the Cd-dependent NO accumulation and expression of Cd 2+ uptake related gene-IRT1 in Arabidopsis.

  9. Methodological issues regarding power of classical test theory (CTT and item response theory (IRT-based approaches for the comparison of patient-reported outcomes in two groups of patients - a simulation study

    Directory of Open Access Journals (Sweden)

    Boyer François

    2010-03-01

    Full Text Available Abstract Background Patients-Reported Outcomes (PRO are increasingly used in clinical and epidemiological research. Two main types of analytical strategies can be found for these data: classical test theory (CTT based on the observed scores and models coming from Item Response Theory (IRT. However, whether IRT or CTT would be the most appropriate method to analyse PRO data remains unknown. The statistical properties of CTT and IRT, regarding power and corresponding effect sizes, were compared. Methods Two-group cross-sectional studies were simulated for the comparison of PRO data using IRT or CTT-based analysis. For IRT, different scenarios were investigated according to whether items or person parameters were assumed to be known, to a certain extent for item parameters, from good to poor precision, or unknown and therefore had to be estimated. The powers obtained with IRT or CTT were compared and parameters having the strongest impact on them were identified. Results When person parameters were assumed to be unknown and items parameters to be either known or not, the power achieved using IRT or CTT were similar and always lower than the expected power using the well-known sample size formula for normally distributed endpoints. The number of items had a substantial impact on power for both methods. Conclusion Without any missing data, IRT and CTT seem to provide comparable power. The classical sample size formula for CTT seems to be adequate under some conditions but is not appropriate for IRT. In IRT, it seems important to take account of the number of items to obtain an accurate formula.

  10. Overexpression of ZmIRT1 and ZmZIP3 Enhances Iron and Zinc Accumulation in Transgenic Arabidopsis.

    Directory of Open Access Journals (Sweden)

    Suzhen Li

    Full Text Available Iron and zinc are important micronutrients for both the growth and nutrient availability of crop plants, and their absorption is tightly controlled by a metal uptake system. Zinc-regulated transporters, iron-regulated transporter-like proteins (ZIP, is considered an essential metal transporter for the acquisition of Fe and Zn in graminaceous plants. Several ZIPs have been identified in maize, although their physiological function remains unclear. In this report, ZmIRT1 was shown to be specifically expressed in silk and embryo, whereas ZmZIP3 was a leaf-specific gene. Both ZmIRT1 and ZmZIP3 were shown to be localized to the plasma membrane and endoplasmic reticulum. In addition, transgenic Arabidopsis plants overexpressing ZmIRT1 or ZmZIP3 were generated, and the metal contents in various tissues of transgenic and wild-type plants were examined based on ICP-OES and Zinpyr-1 staining. The Fe and Zn concentration increased in roots and seeds of ZmIRT1-overexpressing plants, while the Fe content in shoots decreased. Overexpressing ZmZIP3 enhanced Zn accumulation in the roots of transgenic plants, while that in shoots was repressed. In addition, the transgenic plants showed altered tolerance to various Fe and Zn conditions compared with wild-type plants. Furthermore, the genes associated with metal uptake were stimulated in ZmIRT1 transgenic plants, while those involved in intra- and inter- cellular translocation were suppressed. In conclusion, ZmIRT1 and ZmZIP3 are functional metal transporters with different ion selectivities. Ectopic overexpression of ZmIRT1 may stimulate endogenous Fe uptake mechanisms, which may facilitate metal uptake and homeostasis. Our results increase our understanding of the functions of ZIP family transporters in maize.

  11. Measurement Invariance in Careers Research: Using IRT to Study Gender Differences in Medical Students' Specialization Decisions

    Science.gov (United States)

    Behrend, Tara S.; Thompson, Lori Foster; Meade, Adam W.; Newton, Dale A.; Grayson, Martha S.

    2008-01-01

    The current study demonstrates the use of item response theory (IRT) to conduct measurement invariance analyses in careers research. A self-report survey was used to assess the importance 1,363 fourth-year medical students placed on opportunities to provide comprehensive patient care when choosing a career specialty. IRT analyses supported…

  12. Gibberellic acid alleviates cadmium toxicity by reducing nitric oxide accumulation and expression of IRT1 in Arabidopsis thaliana

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Xiao Fang [State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058 (China); Jiang, Tao [Key Laboratory of Conservation Biology for Endangered Wildlife of the Ministry of Education, College of Life Sciences, Zhejiang University, Hangzhou 310058 (China); Wang, Zhi Wei [State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058 (China); Lei, Gui Jie [Key Laboratory of Conservation Biology for Endangered Wildlife of the Ministry of Education, College of Life Sciences, Zhejiang University, Hangzhou 310058 (China); Shi, Yuan Zhi [The Key Laboratory of Tea Chemical Engineering, Ministry of Agriculture, Yunqi Road 1, Hangzhou 310008 (China); Li, Gui Xin, E-mail: guixinli@zju.edu.cn [College of Agronomy and Biotechnology, Zhejiang University, Hangzhou 310058 (China); Zheng, Shao Jian [State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058 (China); Key Laboratory of Conservation Biology for Endangered Wildlife of the Ministry of Education, College of Life Sciences, Zhejiang University, Hangzhou 310058 (China)

    2012-11-15

    Highlights: Black-Right-Pointing-Pointer Cd reduces endogenous GA levels in Arabidopsis. Black-Right-Pointing-Pointer GA exogenous applied decreases Cd accumulation in plant. Black-Right-Pointing-Pointer GA suppresses the Cd-induced accumulation of NO. Black-Right-Pointing-Pointer Decreased NO level downregulates the expression of IRT1. Black-Right-Pointing-Pointer Suppressed IRT1 expression reduces Cd transport across plasma membrane. - Abstract: Gibberellic acid (GA) is involved in not only plant growth and development but also plant responses to abiotic stresses. Here it was found that treating the plants with GA concentrations from 0.1 to 5 {mu}M for 24 h had no obvious effect on root elongation in the absence of cadmium (Cd), whereas in the presence of Cd{sup 2+}, GA at 5 {mu}M improved root growth, reduced Cd content and lipid peroxidation in the roots, indicating that GA can partially alleviate Cd toxicity. Cd{sup 2+} increased nitric oxide (NO) accumulation in the roots, but GA remarkably reduced it, and suppressed the up-regulation of the expression of IRT1. In contrary, the beneficial effect of GA on alleviating Cd toxicity was not observed in an IRT1 knock-out mutant irt1, suggesting the involvement of IRT1 in Cd{sup 2+} absorption. Furthermore, the GA-induced reduction of NO and Cd content can also be partially reversed by the application of a NO donor (S-nitrosoglutathione [GSNO]). Taken all these together, the results showed that GA-alleviated Cd toxicity is mediated through the reduction of the Cd-dependent NO accumulation and expression of Cd{sup 2+} uptake related gene-IRT1 in Arabidopsis.

  13. TWO-PARAMETER IRT MODEL APPLICATION TO ASSESS PROBABILISTIC CHARACTERISTICS OF PROHIBITED ITEMS DETECTION BY AVIATION SECURITY SCREENERS

    Directory of Open Access Journals (Sweden)

    Alexander K. Volkov

    2017-01-01

    Full Text Available The modern approaches to the aviation security screeners’ efficiency have been analyzedand, certain drawbacks have been considered. The main drawback is the complexity of ICAO recommendations implementation concerning taking into account of shadow x-ray image complexity factors during preparation and evaluation of prohibited items detection efficiency by aviation security screeners. Х-ray image based factors are the specific properties of the x-ray image that in- fluence the ability to detect prohibited items by aviation security screeners. The most important complexity factors are: geometric characteristics of a prohibited item; view difficulty of prohibited items; superposition of prohibited items byother objects in the bag; bag content complexity; the color similarity of prohibited and usual items in the luggage.The one-dimensional two-parameter IRT model and the related criterion of aviation security screeners’ qualification have been suggested. Within the suggested model the probabilistic detection characteristics of aviation security screeners are considered as functions of such parameters as the difference between level of qualification and level of x-ray images com- plexity, and also between the aviation security screeners’ responsibility and structure of their professional knowledge. On the basis of the given model it is possible to consider two characteristic functions: first of all, characteristic function of qualifica- tion level which describes multi-complexity level of x-ray image interpretation competency of the aviation security screener; secondly, characteristic function of the x-ray image complexity which describes the range of x-ray image interpretation com- petency of the aviation security screeners having various training levels to interpret the x-ray image of a certain level of com- plexity. The suggested complex criterion to assess the level of the aviation security screener qualification allows to evaluate his or

  14. Nuclear Research Center IRT reactor dynamics calculation

    International Nuclear Information System (INIS)

    Aleman Fernandez, J.R.

    1990-01-01

    The main features of the code DIRT, for dynamical calculations are described in the paper. With the results obtained by the program, an analysis of the dynamic behaviour of the Research Reactor IRT of the Nuclear Research Center (CIN) is performed. Different transitories were considered such as variation of the system reactivity, coolant inlet temperature variation and also variations of the coolant velocity through the reactor core. 3 refs

  15. Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction.

    Science.gov (United States)

    Schwabe, Inga; Boomsma, Dorret I; van den Berg, Stéphanie M

    2017-12-01

    Genotype by environment interaction in behavioral traits may be assessed by estimating the proportion of variance that is explained by genetic and environmental influences conditional on a measured moderating variable, such as a known environmental exposure. Behavioral traits of interest are often measured by questionnaires and analyzed as sum scores on the items. However, statistical results on genotype by environment interaction based on sum scores can be biased due to the properties of a scale. This article presents a method that makes it possible to analyze the actually observed (phenotypic) item data rather than a sum score by simultaneously estimating the genetic model and an item response theory (IRT) model. In the proposed model, the estimation of genotype by environment interaction is based on an alternative parametrization that is uniquely identified and therefore to be preferred over standard parametrizations. A simulation study shows good performance of our method compared to analyzing sum scores in terms of bias. Next, we analyzed data of 2,110 12-year-old Dutch twin pairs on mathematical ability. Genetic models were evaluated and genetic and environmental variance components estimated as a function of a family's socio-economic status (SES). Results suggested that common environmental influences are less important in creating individual differences in mathematical ability in families with a high SES than in creating individual differences in mathematical ability in twin pairs with a low or average SES.

  16. A Stepwise Fitting Procedure for automated fitting of Ecopath with Ecosim models

    Directory of Open Access Journals (Sweden)

    Erin Scott

    2016-01-01

    Full Text Available The Stepwise Fitting Procedure automates testing of alternative hypotheses used for fitting Ecopath with Ecosim (EwE models to observation reference data (Mackinson et al. 2009. The calibration of EwE model predictions to observed data is important to evaluate any model that will be used for ecosystem based management. Thus far, the model fitting procedure in EwE has been carried out manually: a repetitive task involving setting >1000 specific individual searches to find the statistically ‘best fit’ model. The novel fitting procedure automates the manual procedure therefore producing accurate results and lets the modeller concentrate on investigating the ‘best fit’ model for ecological accuracy.

  17. Licensing activities for the partial decommissioning of IRT-2000 research reactor in Sofia

    International Nuclear Information System (INIS)

    Apostolov, T.; Ilieva, Kr.; Papukchiev, A.; Kalchev, B.

    2001-01-01

    The project for refurbishment of IRT-2000 research reactor in Sofia into low-power reactor (200 kW) is based on the retention of some IRT-2000 buildings, facilities and equipment. The activities, which determine the partial decommissioning should be realized in accordance with preliminary developed licensing documents as General Plan, Safety Analysis Report and Environment Impact assessment Report. The goal of these documents is to provide and guarantee safe and effective activities with radioactive materials, to define strictly the dismantling procedures, and in the same time to minimize their influence on the environment. The Technical Tasks for General Plan, Safety Analysis Report and Environment Impact Assessment Report have been prepared and will be presented as preliminary licensing documents to the National Regulatory Body for approval before their application. A Quality Management system is being developed nowadays at INRNE. After its certification some requirements of the regulatory body will be completed. This certified QA system is a major part of the licensing procedure for the reconstruction of IRT-2000 research reactor. (author)

  18. The development of the nuclear physics in Latvia II. The building of the Research Nuclear Reactor IRT

    International Nuclear Information System (INIS)

    Ulmanis, U.

    2004-01-01

    Nuclear research reactor IRT of the Academy of Sciences was built near Riga in Salaspils. IRT is pool aqueous - aqueous reactor with nuclear fuel U-235 contained elements, located in the core at a depth of ∼ 7 m under distilled water. Ten horizontal and 10-15 vertical experimental channels are employed in experimental research with the use of neutron fluxes. For the research with gamma rays is constructed radiation loop facility with liquid In-Ga-SN solid solution as intensive gamma-ray sources. Main activities of IRT are to conduct research in nuclear spectroscopy, neutron activation analysis, neutron diffraction and radiation physics, chemistry and biology. (authors)

  19. A new network of faint calibration stars from the near infrared spectrometer (NIRS) on the IRTS

    Science.gov (United States)

    Freund, Minoru M.; Matsuura, Mikako; Murakami, Hiroshi; Cohen, Martin; Noda, Manabu; Matsuura, Shuji; Matsumoto, Toshio

    1997-01-01

    The point source extraction and calibration of the near infrared spectrometer (NIRS) onboard the Infrared Telescope in Space (IRTS) is described. About 7 percent of the sky was observed during a one month mission in the range of 1.4 micrometers to 4 micrometers. The accuracy of the spectral shape and absolute values of calibration stars provided by the NIRS/IRTS were validated.

  20. An Introduction to Item Response Theory for Health Behavior Researchers

    Science.gov (United States)

    Warne, Russell T.; McKyer, E. J. Lisako; Smith, Matthew L.

    2012-01-01

    Objective: To introduce item response theory (IRT) to health behavior researchers by contrasting it with classical test theory and providing an example of IRT in health behavior. Method: Demonstrate IRT by fitting the 2PL model to substance-use survey data from the Adolescent Health Risk Behavior questionnaire (n = 1343 adolescents). Results: An…

  1. Bayesian inference in an item response theory model with a generalized student t link function

    Science.gov (United States)

    Azevedo, Caio L. N.; Migon, Helio S.

    2012-10-01

    In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

  2. IRT analyses of the Swedish Dark Triad Dirty Dozen

    Directory of Open Access Journals (Sweden)

    Danilo Garcia

    2018-03-01

    Full Text Available Background: The Dark Triad (i.e., Machiavellianism, narcissism, and psychopathy can be captured quickly with 12 items using the Dark Triad Dirty Dozen (Jonason and Webster, 2010. Previous Item Response Theory (IRT analyses of the original English Dark Triad Dirty Dozen have shown that all three subscales adequately tap into the dark domains of personality. The aim of the present study was to analyze the Swedish version of the Dark Triad Dirty Dozen using IRT. Method: 570 individuals (nmales = 326, nfemales = 242, and 2 unreported, including university students and white-collar workers with an age range between 19 and 65 years, responded to the Swedish version of the Dark Triad Dirty Dozen (Garcia et al., 2017a,b. Results: Contrary to previous research, we found that the narcissism scale provided most information, followed by psychopathy, and finally Machiavellianism. Moreover, the psychopathy scale required a higher level of the latent trait for endorsement of its items than the narcissism and Machiavellianism scales. Overall, all items provided reasonable amounts of information and are thus effective for discriminating between individuals. The mean item discriminations (alphas were 1.92 for Machiavellianism, 2.31 for narcissism, and 1.99 for psychopathy. Conclusion: This is the first study to provide IRT analyses of the Swedish version of the Dark Triad Dirty Dozen. Our findings add to a growing literature on the Dark Triad Dirty Dozen scale in different cultures and highlight psychometric characteristics, which can be used for comparative studies. Items tapping into psychopathy showed higher thresholds for endorsement than the other two scales. Importantly, the narcissism scale seems to provide more information about a lack of narcissism, perhaps mirroring cultural conditions. Keywords: Psychology, Psychiatry, Clinical psychology

  3. Solution of operational problems utilization of an EX-IRT-2000 heat exchanger

    International Nuclear Information System (INIS)

    Razak, Abdu

    1986-01-01

    The Bandung TRIGA Mark II Reactor has been successfully operated for 21 years, especially in low power operation or as neutron sources for various experiments. Most of the operating time, approximately 80% of routine operation, was dedicated for radio-isotope production. During routine operation for radio-isotope production, the reactor could not be operated at full power. The reactor was operated at 60% of the maximum power (1 MWth) due to the inability of the original heat exchanger to operate properly. The reason is that slack deposition was built-up on the secondary side of the heat exchanger. Therefore, it reduced the coefficient of heat transfer considerably. To solve the problems, a set of heat exchanger including the pump was installed In parallel with the original unit. The heat exchanger was an IRT-2000 Reactor Heat exchanger which was collected from the abandoned IRT-2000 Project. The heat exchanger has capacity of 1.25 MW. The new heat exchanger could reduced the outlet temperature of the primary coolant Into 42 deg. C. While the original-heat exchanger at the worst condition and at 600 kW of power reach outlet temperature 49 deg. C. The IRT Heat Exchanger is a counter flow heat exchanger. (author)

  4. Solution of operational problems utilization of an EX-IRT-2000 heat exchanger

    Energy Technology Data Exchange (ETDEWEB)

    Razak, Abdu [Research Centre for Nuclear Techniques, National Atomic Energy Agency (Indonesia)

    1986-07-01

    The Bandung TRIGA Mark II Reactor has been successfully operated for 21 years, especially in low power operation or as neutron sources for various experiments. Most of the operating time, approximately 80% of routine operation, was dedicated for radio-isotope production. During routine operation for radio-isotope production, the reactor could not be operated at full power. The reactor was operated at 60% of the maximum power (1 MWth) due to the inability of the original heat exchanger to operate properly. The reason is that slack deposition was built-up on the secondary side of the heat exchanger. Therefore, it reduced the coefficient of heat transfer considerably. To solve the problems, a set of heat exchanger including the pump was installed In parallel with the original unit. The heat exchanger was an IRT-2000 Reactor Heat exchanger which was collected from the abandoned IRT-2000 Project. The heat exchanger has capacity of 1.25 MW. The new heat exchanger could reduced the outlet temperature of the primary coolant Into 42 deg. C. While the original-heat exchanger at the worst condition and at 600 kW of power reach outlet temperature 49 deg. C. The IRT Heat Exchanger is a counter flow heat exchanger. (author)

  5. Results and Conclusions from the NASA Isokinetic Total Water Content Probe 2009 IRT Test

    Science.gov (United States)

    Reehorst, Andrew; Brinker, David

    2010-01-01

    The NASA Glenn Research Center has developed and tested a Total Water Content Isokinetic Sampling Probe. Since, by its nature, it is not sensitive to cloud water particle phase nor size, it is particularly attractive to support super-cooled large droplet and high ice water content aircraft icing studies. The instrument comprises the Sampling Probe, Sample Flow Control, and Water Vapor Measurement subsystems. Results and conclusions are presented from probe tests in the NASA Glenn Icing Research Tunnel (IRT) during January and February 2009. The use of reference probe heat and the control of air pressure in the water vapor measurement subsystem are discussed. Several run-time error sources were found to produce identifiable signatures that are presented and discussed. Some of the differences between measured Isokinetic Total Water Content Probe and IRT calibration seems to be caused by tunnel humidification and moisture/ice crystal blow around. Droplet size, airspeed, and liquid water content effects also appear to be present in the IRT calibration. Based upon test results, the authors provide recommendations for future Isokinetic Total Water Content Probe development.

  6. The design, construction, and operation of the Integrated Radwaste Treatment System (IRTS) Drum Cell

    International Nuclear Information System (INIS)

    Landau, B.; Russillo, A.; Frank, D.; Garland, D.

    1989-12-01

    This report describes the design, construction, and the operation of the Integrated Radwaste Treatment Systems (IRTS) Drum Cell at the West Valley Demonstration Project (WVDP), West Valley, New York. The IRTS Drum Cell was designed to provide a shielded, secure storage area for the remote handling and placement of low-level Class C radioactive waste produced in the IRTS. The Drum Cell was designed to contain up to approximately 8,804 drums from decontaminated supernatant processing. This waste is to be poured into 0.27m 3 in a temperature controlled environment to ensure the cement will not be subjected to freezing and thawing cycles. A Temporary Weather Structure (TWS), a pre-engineered building, now encloses the Drum Cell and associated equipment so that remote waste-handling and placement operations can continue without regard to weather conditions. The Drum Cell was designed so that this TWS could be removed and the low-level waste entombed in place. Final disposition of this low-level waste is currently being evaluated in an Environmental Impact Statement (EIS). 10 refs., 11 figs., 1 tab

  7. Inoculation with Bacillus subtilis and Azospirillum brasilense produces abscisic acid that reduces IRT1-mediated cadmium uptake of roots.

    Science.gov (United States)

    Xu, Qianru; Pan, Wei; Zhang, Ranran; Lu, Qi; Xue, Wanlei; Wu, Cainan; Song, Bixiu; Du, Shaoting

    2018-05-08

    Cadmium (Cd) contamination of agricultural soils represents a serious risk to crop safety. A new strategy using abscisic acid (ABA)-generating bacteria, Bacillus subtilis or Azospirillum brasilense, was developed to reduce the Cd accumulation in plants grown in Cd-contaminated soil. Inoculation with either bacterium resulted in a pronounced increase in the ABA level in wild-type Arabidopsis Col-0 plants, accompanied by a decrease in Cd levels in plant tissues, which mitigated the Cd toxicity. As a consequence, the growth of plants exposed to Cd was improved. Nevertheless, B. subtilis and A. brasilense inoculation had little effect on Cd levels and toxicity in the ABA-insensitive mutant snrk 2.2/2.3, indicating that the action of ABA is required for these bacteria to reduce Cd accumulation in plants. Furthermore, inoculation with either B. subtilis or A. brasilense down-regulated the expression of IRT1 (IRON-REGULATED TRANSPORTER 1) in the roots of wild-type plants and had little effect on Cd levels in the IRT1-knockout mutants irt1-1 and irt1-2. In summary, we conclude that B. subtilis and A. brasilense can reduce Cd levels in plants via an IRT1-dependent ABA-mediated mechanism.

  8. A signal detection-item response theory model for evaluating neuropsychological measures.

    Science.gov (United States)

    Thomas, Michael L; Brown, Gregory G; Gur, Ruben C; Moore, Tyler M; Patt, Virginie M; Risbrough, Victoria B; Baker, Dewleen G

    2018-02-05

    Models from signal detection theory are commonly used to score neuropsychological test data, especially tests of recognition memory. Here we show that certain item response theory models can be formulated as signal detection theory models, thus linking two complementary but distinct methodologies. We then use the approach to evaluate the validity (construct representation) of commonly used research measures, demonstrate the impact of conditional error on neuropsychological outcomes, and evaluate measurement bias. Signal detection-item response theory (SD-IRT) models were fitted to recognition memory data for words, faces, and objects. The sample consisted of U.S. Infantry Marines and Navy Corpsmen participating in the Marine Resiliency Study. Data comprised item responses to the Penn Face Memory Test (PFMT; N = 1,338), Penn Word Memory Test (PWMT; N = 1,331), and Visual Object Learning Test (VOLT; N = 1,249), and self-report of past head injury with loss of consciousness. SD-IRT models adequately fitted recognition memory item data across all modalities. Error varied systematically with ability estimates, and distributions of residuals from the regression of memory discrimination onto self-report of past head injury were positively skewed towards regions of larger measurement error. Analyses of differential item functioning revealed little evidence of systematic bias by level of education. SD-IRT models benefit from the measurement rigor of item response theory-which permits the modeling of item difficulty and examinee ability-and from signal detection theory-which provides an interpretive framework encompassing the experimentally validated constructs of memory discrimination and response bias. We used this approach to validate the construct representation of commonly used research measures and to demonstrate how nonoptimized item parameters can lead to erroneous conclusions when interpreting neuropsychological test data. Future work might include the

  9. Time evolution of the energy confinement time, internal inductance and effective edge safety factor on IR-T1 tokamak

    International Nuclear Information System (INIS)

    Salar Elahi, A; Ghoranneviss, M

    2010-01-01

    An attempt is made to investigate the time evolution of the energy confinement time, internal inductance and effective edge safety factor on IR-T1 tokamak. For this purpose, four magnetic pickup coils were designed, constructed and installed on the outer surface of the IR-T1 and then the Shafranov parameter (asymmetry factor) was obtained from them. On the other hand, also a diamagnetic loop was designed and installed on IR-T1 and poloidal beta was determined from it. Therefore, the internal inductance and effective edge safety factor were measured. Also, the time evolution of the energy confinement time was measured using the diamagnetic loop. Experimental results on IR-T1 show that the maximum energy confinement time (which corresponds to minimum collisions, minimum microinstabilities and minimum transport) is at low values of the effective edge safety factor (2.5 eff (a) i <0.72). The results obtained are in agreement with those obtained with the theoretical approach [1-5].

  10. Item Response Theory with Covariates (IRT-C): Assessing Item Recovery and Differential Item Functioning for the Three-Parameter Logistic Model

    Science.gov (United States)

    Tay, Louis; Huang, Qiming; Vermunt, Jeroen K.

    2016-01-01

    In large-scale testing, the use of multigroup approaches is limited for assessing differential item functioning (DIF) across multiple variables as DIF is examined for each variable separately. In contrast, the item response theory with covariate (IRT-C) procedure can be used to examine DIF across multiple variables (covariates) simultaneously. To…

  11. Measured, modeled, and causal conceptions of fitness

    Science.gov (United States)

    Abrams, Marshall

    2012-01-01

    This paper proposes partial answers to the following questions: in what senses can fitness differences plausibly be considered causes of evolution?What relationships are there between fitness concepts used in empirical research, modeling, and abstract theoretical proposals? How does the relevance of different fitness concepts depend on research questions and methodological constraints? The paper develops a novel taxonomy of fitness concepts, beginning with type fitness (a property of a genotype or phenotype), token fitness (a property of a particular individual), and purely mathematical fitness. Type fitness includes statistical type fitness, which can be measured from population data, and parametric type fitness, which is an underlying property estimated by statistical type fitnesses. Token fitness includes measurable token fitness, which can be measured on an individual, and tendential token fitness, which is assumed to be an underlying property of the individual in its environmental circumstances. Some of the paper's conclusions can be outlined as follows: claims that fitness differences do not cause evolution are reasonable when fitness is treated as statistical type fitness, measurable token fitness, or purely mathematical fitness. Some of the ways in which statistical methods are used in population genetics suggest that what natural selection involves are differences in parametric type fitnesses. Further, it's reasonable to think that differences in parametric type fitness can cause evolution. Tendential token fitnesses, however, are not themselves sufficient for natural selection. Though parametric type fitnesses are typically not directly measurable, they can be modeled with purely mathematical fitnesses and estimated by statistical type fitnesses, which in turn are defined in terms of measurable token fitnesses. The paper clarifies the ways in which fitnesses depend on pragmatic choices made by researchers. PMID:23112804

  12. Fitting neuron models to spike trains

    Directory of Open Access Journals (Sweden)

    Cyrille eRossant

    2011-02-01

    Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.

  13. Induced subgraph searching for geometric model fitting

    Science.gov (United States)

    Xiao, Fan; Xiao, Guobao; Yan, Yan; Wang, Xing; Wang, Hanzi

    2017-11-01

    In this paper, we propose a novel model fitting method based on graphs to fit and segment multiple-structure data. In the graph constructed on data, each model instance is represented as an induced subgraph. Following the idea of pursuing the maximum consensus, the multiple geometric model fitting problem is formulated as searching for a set of induced subgraphs including the maximum union set of vertices. After the generation and refinement of the induced subgraphs that represent the model hypotheses, the searching process is conducted on the "qualified" subgraphs. Multiple model instances can be simultaneously estimated by solving a converted problem. Then, we introduce the energy evaluation function to determine the number of model instances in data. The proposed method is able to effectively estimate the number and the parameters of model instances in data severely corrupted by outliers and noises. Experimental results on synthetic data and real images validate the favorable performance of the proposed method compared with several state-of-the-art fitting methods.

  14. RIBD-IRT, Isotope Buildup and Isotope Decay from Fission Source

    International Nuclear Information System (INIS)

    1990-01-01

    1 - Description of problem or function: RIBD-IRT calculates isotopic concentrations resulting from two fission sources with normal down- chain decay by beta emission and isomeric transfers and inter-chain coupling resulting from (n,gamma) reactions. Calculations can be made to follow an irradiation history through an unlimited number of step changes of unrestricted duration and variability including shutdown periods, restarts at different power levels and/or any other level changes. In addition, the program permits to track and modify the concentration of individual elements as they decay with time following reactor shutdown. Tracking individual elements enables one to estimate time-dependent source terms for a hypothetical LOCA based on known or postulated fission product release mechanisms. 2 - Method of solution: RIBD-IRT is a grid processor. It organizes the various members described by the fission product library data into a grid with the various linkages established from chain branching data, yield data, and neutron capture cross sections with their branching ratios. Radioactive decay includes not only the simple member-to-member cascade but also the more complex forms where branching may be partially or completely skip one or two intervening members

  15. Marginal Maximum Likelihood Estimation of Item Response Models in R

    Directory of Open Access Journals (Sweden)

    Matthew S. Johnson

    2007-02-01

    Full Text Available Item response theory (IRT models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items. The most common IRT models can be classified as generalized linear fixed- and/or mixed-effect models. Although IRT models appear most often in the psychological testing literature, researchers in other fields have successfully utilized IRT-like models in a wide variety of applications. This paper discusses the three major methods of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit model. The currently available R packages ltm is also discussed.

  16. Analytical fitting model for rough-surface BRDF.

    Science.gov (United States)

    Renhorn, Ingmar G E; Boreman, Glenn D

    2008-08-18

    A physics-based model is developed for rough surface BRDF, taking into account angles of incidence and scattering, effective index, surface autocovariance, and correlation length. Shadowing is introduced on surface correlation length and reflectance. Separate terms are included for surface scatter, bulk scatter and retroreflection. Using the FindFit function in Mathematica, the functional form is fitted to BRDF measurements over a wide range of incident angles. The model has fourteen fitting parameters; once these are fixed, the model accurately describes scattering data over two orders of magnitude in BRDF without further adjustment. The resulting analytical model is convenient for numerical computations.

  17. Curve fitting methods for solar radiation data modeling

    Energy Technology Data Exchange (ETDEWEB)

    Karim, Samsul Ariffin Abdul, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder, E-mail: samsul-ariffin@petronas.com.my, E-mail: balbir@petronas.com.my [Department of Fundamental and Applied Sciences, Faculty of Sciences and Information Technology, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia)

    2014-10-24

    This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

  18. Curve fitting methods for solar radiation data modeling

    Science.gov (United States)

    Karim, Samsul Ariffin Abdul; Singh, Balbir Singh Mahinder

    2014-10-01

    This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R2. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

  19. Curve fitting methods for solar radiation data modeling

    International Nuclear Information System (INIS)

    Karim, Samsul Ariffin Abdul; Singh, Balbir Singh Mahinder

    2014-01-01

    This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R 2 . The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods

  20. Modeling Evolution on Nearly Neutral Network Fitness Landscapes

    Science.gov (United States)

    Yakushkina, Tatiana; Saakian, David B.

    2017-08-01

    To describe virus evolution, it is necessary to define a fitness landscape. In this article, we consider the microscopic models with the advanced version of neutral network fitness landscapes. In this problem setting, we suppose a fitness difference between one-point mutation neighbors to be small. We construct a modification of the Wright-Fisher model, which is related to ordinary infinite population models with nearly neutral network fitness landscape at the large population limit. From the microscopic models in the realistic sequence space, we derive two versions of nearly neutral network models: with sinks and without sinks. We claim that the suggested model describes the evolutionary dynamics of RNA viruses better than the traditional Wright-Fisher model with few sequences.

  1. Fitting Hidden Markov Models to Psychological Data

    Directory of Open Access Journals (Sweden)

    Ingmar Visser

    2002-01-01

    Full Text Available Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.

  2. Random-growth urban model with geographical fitness

    Science.gov (United States)

    Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

    2012-12-01

    This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

  3. Contrast Gain Control Model Fits Masking Data

    Science.gov (United States)

    Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

  4. Comparison of IRT Likelihood Ratio Test and Logistic Regression DIF Detection Procedures

    Science.gov (United States)

    Atar, Burcu; Kamata, Akihito

    2011-01-01

    The Type I error rates and the power of IRT likelihood ratio test and cumulative logit ordinal logistic regression procedures in detecting differential item functioning (DIF) for polytomously scored items were investigated in this Monte Carlo simulation study. For this purpose, 54 simulation conditions (combinations of 3 sample sizes, 2 sample…

  5. Decommissioning of the research nuclear reactor IRT-M and problems connected with radioactive waste

    International Nuclear Information System (INIS)

    Abramidze, S.P.; Katamadze, N.M.; Kiknadze, G.G.; Saralidze, Z.K.

    2000-01-01

    The nuclear research reactor IRT-2000 is described, along with modifications and upgrades made over the past three decades. Considerations are outlined which followed a decision to shut-down the reactor and to dismantle it. (author)

  6. Structural versus electronic distortions of symmetry-broken IrTe$_2$

    OpenAIRE

    Kim, Hyo Sung; Kim, Tae-Hwan; Yang, Junjie; Cheong, Sang-Wook; Yeom, Han Woong

    2014-01-01

    We investigate atomic and electronic structures of the intriguing low temperature phase of IrTe2 using high-resolution scanning tunneling microscopy and spectroscopy. We confirm various stripe superstructures such as $\\times$3, $\\times$5, and $\\times$8. The strong vertical and lateral distortions of the lattice for the stripe structures are observed in agreement with recent calculations. The spatial modulations of electronic density of states are clearly identified as separated from the struc...

  7. Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

    DEFF Research Database (Denmark)

    Bolker, B.M.; Gardner, B.; Maunder, M.

    2013-01-01

    Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. R is convenient and (relatively) easy...... to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield...

  8. Local fit evaluation of structural equation models using graphical criteria.

    Science.gov (United States)

    Thoemmes, Felix; Rosseel, Yves; Textor, Johannes

    2018-03-01

    Evaluation of model fit is critically important for every structural equation model (SEM), and sophisticated methods have been developed for this task. Among them are the χ² goodness-of-fit test, decomposition of the χ², derived measures like the popular root mean square error of approximation (RMSEA) or comparative fit index (CFI), or inspection of residuals or modification indices. Many of these methods provide a global approach to model fit evaluation: A single index is computed that quantifies the fit of the entire SEM to the data. In contrast, graphical criteria like d-separation or trek-separation allow derivation of implications that can be used for local fit evaluation, an approach that is hardly ever applied. We provide an overview of local fit evaluation from the viewpoint of SEM practitioners. In the presence of model misfit, local fit evaluation can potentially help in pinpointing where the problem with the model lies. For models that do fit the data, local tests can identify the parts of the model that are corroborated by the data. Local tests can also be conducted before a model is fitted at all, and they can be used even for models that are globally underidentified. We discuss appropriate statistical local tests, and provide applied examples. We also present novel software in R that automates this type of local fit evaluation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  9. The e-MSWS-12: improving the multiple sclerosis walking scale using item response theory.

    Science.gov (United States)

    Engelhard, Matthew M; Schmidt, Karen M; Engel, Casey E; Brenton, J Nicholas; Patek, Stephen D; Goldman, Myla D

    2016-12-01

    The Multiple Sclerosis Walking Scale (MSWS-12) is the predominant patient-reported measure of multiple sclerosis (MS) -elated walking ability, yet it had not been analyzed using item response theory (IRT), the emerging standard for patient-reported outcome (PRO) validation. This study aims to reduce MSWS-12 measurement error and facilitate computerized adaptive testing by creating an IRT model of the MSWS-12 and distributing it online. MSWS-12 responses from 284 subjects with MS were collected by mail and used to fit and compare several IRT models. Following model selection and assessment, subpopulations based on age and sex were tested for differential item functioning (DIF). Model comparison favored a one-dimensional graded response model (GRM). This model met fit criteria and explained 87 % of response variance. The performance of each MSWS-12 item was characterized using category response curves (CRCs) and item information. IRT-based MSWS-12 scores correlated with traditional MSWS-12 scores (r = 0.99) and timed 25-foot walk (T25FW) speed (r =  -0.70). Item 2 showed DIF based on age (χ 2  = 19.02, df = 5, p Item 11 showed DIF based on sex (χ 2  = 13.76, df = 5, p = 0.02). MSWS-12 measurement error depends on walking ability, but could be lowered by improving or replacing items with low information or DIF. The e-MSWS-12 includes IRT-based scoring, error checking, and an estimated T25FW derived from MSWS-12 responses. It is available at https://ms-irt.shinyapps.io/e-MSWS-12 .

  10. The first critical experiment with a new type of fuel assemblies IRT-3M on the training reactor VR-I

    International Nuclear Information System (INIS)

    Matejka, Karel; Sklenka, Lubomir

    1997-01-01

    The paper 'The first critical experiment with a new type of fuel assemblies IRT-3M on training reactor VR-1 presents basic information about the replacement of fuel on the reactor VR-1 run on FJFI CVUT in Prague. In spring 1997 the IRT-2M fuel type used till then was replaced by the IRT-3M type. When the fuel was replaced, no change in its enrichment was made, i.e. its level remained as 36% 235 U. The replacement itself was carried out in tight co-operation with the Nuclear Research Institute Rez plc., as related to the operation of the research reactor LVR-15. The fuel replacement on the VR-I reactor is a part of the international program RERTR (Reduced Enrichment for Research and Test Reactors) in which the Czech Republic participates. (author)

  11. topicmodels: An R Package for Fitting Topic Models

    Directory of Open Access Journals (Sweden)

    Bettina Grun

    2011-05-01

    Full Text Available Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent variables which are referred to as topics. The R package topicmodels provides basic infrastructure for fitting topic models based on data structures from the text mining package tm. The package includes interfaces to two algorithms for fitting topic models: the variational expectation-maximization algorithm provided by David M. Blei and co-authors and an algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors.

  12. Developing a Screening Inventory Reading Test (IRT for the Isfahanian Students of the First to Fifth Grade

    Directory of Open Access Journals (Sweden)

    Bijan Shafiei

    2009-12-01

    Full Text Available Background and aim: Reading is one of the most essential skills in this century. Reading disorders can cause several problems for the person who has reading disorder. Early assessment and diagnosis play an important role in treatment of this disorder. The main purpose of this study was to develope a screening inventory reading test (IRT for first to fifth grade student in Isfahan in order to early diagnosis of reading disorder.Materials and Methods: The test, consisting of 100 words context and four comprehension questions, named Inventory Reading Test (IRT, was evaluated by several speech therapists. It was standardized by testing on one thousand boys and girls, 200 students in every grade, that were selected through a multi-stage random sampling method. Test was performed on two other groups, a normal and a reading-disordered.Results: Scores of reading accuracy and velocity were highly correlated with the test total score. Test reliability was calculated as 0.77 by Cronbach`s alpha measure. There was significant difference between two groups mean score (p=0.01.Conclusion: IRT seems to be an appropriate tool for screening reading disorder of first to fifth grade students.

  13. Using a Linear Regression Method to Detect Outliers in IRT Common Item Equating

    Science.gov (United States)

    He, Yong; Cui, Zhongmin; Fang, Yu; Chen, Hanwei

    2013-01-01

    Common test items play an important role in equating alternate test forms under the common item nonequivalent groups design. When the item response theory (IRT) method is applied in equating, inconsistent item parameter estimates among common items can lead to large bias in equated scores. It is prudent to evaluate inconsistency in parameter…

  14. Future development of the research nuclear reactor IRT-2000 in Sofia

    International Nuclear Information System (INIS)

    Apostolov, T.G.

    1999-01-01

    The present paper presents a short description of the research reactor IRT-2000 Sofia, started in 1961 and operated for 28 years. Some items are considered, connected to the improvements made in the contemporary safety requirements and the unrealized project for modernization to 5 MW. Proposals are considered for reconstruction of reactor site to a 'reactor of low power' for education purposes and as a basis for the country's nuclear technology development. (author)

  15. Tests to control the power distribution in the IRT-2,000 reactor

    International Nuclear Information System (INIS)

    Filipcuk, E.V.; Potapenko, P.T.; Krjukov, A.P.; Trofimov, A.P.; Kosilov, A.N.; Nebojan, V.T.; Timochin, E.S.

    1976-01-01

    Results of the investigations of a few structures of such control systems carried out with the help of the IRT 2,000 MIFI reactor in the years 1973/74 are presented in the present work. Within the framework of this study, the successful test of using the transmitter of the direct loading in equipment to control the neutron field was carried out. (orig./TK) [de

  16. Automatic fitting of spiking neuron models to electrophysiological recordings

    Directory of Open Access Journals (Sweden)

    Cyrille Rossant

    2010-03-01

    Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

  17. Building an Evaluation Scale using Item Response Theory.

    Science.gov (United States)

    Lalor, John P; Wu, Hao; Yu, Hong

    2016-11-01

    Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.

  18. The FITS model office ergonomics program: a model for best practice.

    Science.gov (United States)

    Chim, Justine M Y

    2014-01-01

    An effective office ergonomics program can predict positive results in reducing musculoskeletal injury rates, enhancing productivity, and improving staff well-being and job satisfaction. Its objective is to provide a systematic solution to manage the potential risk of musculoskeletal disorders among computer users in an office setting. A FITS Model office ergonomics program is developed. The FITS Model Office Ergonomics Program has been developed which draws on the legislative requirements for promoting the health and safety of workers using computers for extended periods as well as previous research findings. The Model is developed according to the practical industrial knowledge in ergonomics, occupational health and safety management, and human resources management in Hong Kong and overseas. This paper proposes a comprehensive office ergonomics program, the FITS Model, which considers (1) Furniture Evaluation and Selection; (2) Individual Workstation Assessment; (3) Training and Education; (4) Stretching Exercises and Rest Break as elements of an effective program. An experienced ergonomics practitioner should be included in the program design and implementation. Through the FITS Model Office Ergonomics Program, the risk of musculoskeletal disorders among computer users can be eliminated or minimized, and workplace health and safety and employees' wellness enhanced.

  19. Reliability and Model Fit

    Science.gov (United States)

    Stanley, Leanne M.; Edwards, Michael C.

    2016-01-01

    The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…

  20. Future development of the research nuclear reactor IRT-2000 in Sofia

    Energy Technology Data Exchange (ETDEWEB)

    Apostolov, T.G. [Institute for Nuclear Research and Nuclear Energy, BAS, Sofia (Bulgaria)

    1999-07-01

    The present paper presents a short description of the research reactor IRT-2000 Sofia, started in 1961 and operated for 28 years. Some items are considered, connected to the improvements made in the contemporary safety requirements and the unrealized project for modernization to 5 MW. Proposals are considered for reconstruction of reactor site to a 'reactor of low power' for education purposes and as a basis for the country's nuclear technology development. (author)

  1. Experiments in power distribution control on the IRT-2000 reactor

    International Nuclear Information System (INIS)

    Filipchuk, E.V.; Potapenko, P.T.; Trofimov, A.P.; Kosilov, A.N.; Neboyan, V.T.; Timokhin, E.S.

    1975-01-01

    The results from the experimental investigations of a system for regulating the neutron field on a research reactor IRT-2000 are shown. The right of such experiments on a reactor with a little active zone is substantiated. A successful attempt was made in this work to apply primary elements of straight charging in the neutron field regulating system. A system with independent instrumentally local regulators, a system with hard cross connections and a structure with a ''floating'' installation are studied. Serial common industrial regulators BRT-2 were used

  2. Cross-cultural validity of the Spanish version of PHQ-9 among pregnant Peruvian women: a Rasch item response theory analysis.

    Science.gov (United States)

    Zhong, Qiuyue; Gelaye, Bizu; Fann, Jesse R; Sanchez, Sixto E; Williams, Michelle A

    2014-04-01

    We sought to evaluate the validity of the Spanish language version of the patient health questionnaire-9 (PHQ-9) depression scale in a large sample of pregnant Peruvian women using Rasch item response theory (IRT) approaches. We further sought to examine the appropriateness of the response formats, reliability and potential differential item functioning (DIF) by maternal age, educational attainment and employment status. This cross-sectional study was conducted among 1520 pregnant women in Lima, Peru. A structured interview was used to collect information on demographic characteristics and PHQ-9 items. Data from the PHQ-9 were fitted to the Rasch IRT model and tested for appropriate category ordering, the assumptions of unidimensionality and local independence, item fit, reliability and presence of DIF. The Spanish language version of PHQ-9 demonstrated unidimensionality, local independence, and acceptable fit for the Rasch IRT model. However, we detected disordered response categories for the original four response categories. After collapsing "more than half the days" and "nearly every day", the response categories ordered properly and the PHQ-9 fit the Rasch IRT model. The PHQ-9 had moderate internal consistency (person separation index, PSI=0.72). Additionally, the items of PHQ-9 were free of DIF with regard to age, educational attainment, and employment status. The Spanish language version of the PHQ-9 was shown to have item properties of an effective screening instrument. Collapsing rating scale categories and reconstructing three-point Likert scale for all items improved the fit of the instrument. Future studies are warranted to establish new cutoff scores and criterion validity of the three-point Likert scale response options for the Spanish language version of the PHQ-9. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

    Science.gov (United States)

    Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise

    2013-01-01

    1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

  4. Are Physical Education Majors Models for Fitness?

    Science.gov (United States)

    Kamla, James; Snyder, Ben; Tanner, Lori; Wash, Pamela

    2012-01-01

    The National Association of Sport and Physical Education (NASPE) (2002) has taken a firm stance on the importance of adequate fitness levels of physical education teachers stating that they have the responsibility to model an active lifestyle and to promote fitness behaviors. Since the NASPE declaration, national initiatives like Let's Move…

  5. Improved utilization of ADAS-cog assessment data through item response theory based pharmacometric modeling.

    Science.gov (United States)

    Ueckert, Sebastian; Plan, Elodie L; Ito, Kaori; Karlsson, Mats O; Corrigan, Brian; Hooker, Andrew C

    2014-08-01

    This work investigates improved utilization of ADAS-cog data (the primary outcome in Alzheimer's disease (AD) trials of mild and moderate AD) by combining pharmacometric modeling and item response theory (IRT). A baseline IRT model characterizing the ADAS-cog was built based on data from 2,744 individuals. Pharmacometric methods were used to extend the baseline IRT model to describe longitudinal ADAS-cog scores from an 18-month clinical study with 322 patients. Sensitivity of the ADAS-cog items in different patient populations as well as the power to detect a drug effect in relation to total score based methods were assessed with the IRT based model. IRT analysis was able to describe both total and item level baseline ADAS-cog data. Longitudinal data were also well described. Differences in the information content of the item level components could be quantitatively characterized and ranked for mild cognitively impairment and mild AD populations. Based on clinical trial simulations with a theoretical drug effect, the IRT method demonstrated a significantly higher power to detect drug effect compared to the traditional method of analysis. A combined framework of IRT and pharmacometric modeling permits a more effective and precise analysis than total score based methods and therefore increases the value of ADAS-cog data.

  6. IRT-LR-DIF with Estimation of the Focal-Group Density as an Empirical Histogram

    Science.gov (United States)

    Woods, Carol M.

    2008-01-01

    Item response theory-likelihood ratio-differential item functioning (IRT-LR-DIF) is used to evaluate the degree to which items on a test or questionnaire have different measurement properties for one group of people versus another, irrespective of group-mean differences on the construct. Usually, the latent distribution is presumed normal for both…

  7. Effects of eight weeks of aerobic interval training and of isoinertial resistance training on risk factors of cardiometabolic diseases and exercise capacity in healthy elderly subjects

    Science.gov (United States)

    Bruseghini, Paolo; Calabria, Elisa; Tam, Enrico; Milanese, Chiara; Oliboni, Eugenio; Pezzato, Andrea; Pogliaghi, Silvia; Salvagno, Gian Luca; Schena, Federico; Mucelli, Roberto Pozzi; Capelli, Carlo

    2015-01-01

    We investigated the effect of 8 weeks of high intensity interval training (HIT) and isoinertial resistance training (IRT) on cardiovascular fitness, muscle mass-strength and risk factors of metabolic syndrome in 12 healthy older adults (68 yy ± 4). HIT consisted in 7 two-minute repetitions at 80%–90% of V˙O2max, 3 times/w. After 4 months of recovery, subjects were treated with IRT, which included 4 sets of 7 maximal, bilateral knee extensions/flexions 3 times/w on a leg-press flywheel ergometer. HIT elicited significant: i) modifications of selected anthropometrical features; ii) improvements of cardiovascular fitness and; iii) decrease of systolic pressure. HIT and IRT induced hypertrophy of the quadriceps muscle, which, however, was paralleled by significant increases in strength only after IRT. Neither HIT nor IRT induced relevant changes in blood lipid profile, with the exception of a decrease of LDL and CHO after IRT. Physiological parameters related with aerobic fitness and selected body composition values predicting cardiovascular risk remained stable during detraining and, after IRT, they were complemented by substantial increase of muscle strength, leading to further improvements of quality of life of the subjects. PMID:26046575

  8. Assessing fit in Bayesian models for spatial processes

    KAUST Repository

    Jun, M.; Katzfuss, M.; Hu, J.; Johnson, V. E.

    2014-01-01

    © 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

  9. Assessing fit in Bayesian models for spatial processes

    KAUST Repository

    Jun, M.

    2014-09-16

    © 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models\\' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

  10. Measurement model choice influenced randomized controlled trial results.

    Science.gov (United States)

    Gorter, Rosalie; Fox, Jean-Paul; Apeldoorn, Adri; Twisk, Jos

    2016-11-01

    In randomized controlled trials (RCTs), outcome variables are often patient-reported outcomes measured with questionnaires. Ideally, all available item information is used for score construction, which requires an item response theory (IRT) measurement model. However, in practice, the classical test theory measurement model (sum scores) is mostly used, and differences between response patterns leading to the same sum score are ignored. The enhanced differentiation between scores with IRT enables more precise estimation of individual trajectories over time and group effects. The objective of this study was to show the advantages of using IRT scores instead of sum scores when analyzing RCTs. Two studies are presented, a real-life RCT, and a simulation study. Both IRT and sum scores are used to measure the construct and are subsequently used as outcomes for effect calculation. The bias in RCT results is conditional on the measurement model that was used to construct the scores. A bias in estimated trend of around one standard deviation was found when sum scores were used, where IRT showed negligible bias. Accurate statistical inferences are made from an RCT study when using IRT to estimate construct measurements. The use of sum scores leads to incorrect RCT results. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Evaluating the validity of the Work Role Functioning Questionnaire (Canadian French version) using classical test theory and item response theory.

    Science.gov (United States)

    Hong, Quan Nha; Coutu, Marie-France; Berbiche, Djamal

    2017-01-01

    The Work Role Functioning Questionnaire (WRFQ) was developed to assess workers' perceived ability to perform job demands and is used to monitor presenteeism. Still few studies on its validity can be found in the literature. The purpose of this study was to assess the items and factorial composition of the Canadian French version of the WRFQ (WRFQ-CF). Two measurement approaches were used to test the WRFQ-CF: Classical Test Theory (CTT) and non-parametric Item Response Theory (IRT). A total of 352 completed questionnaires were analyzed. A four-factor and three-factor model models were tested and shown respectively good fit with 14 items (Root Mean Square Error of Approximation (RMSEA) = 0.06, Standardized Root Mean Square Residual (SRMR) = 0.04, Bentler Comparative Fit Index (CFI) = 0.98) and with 17 items (RMSEA = 0.059, SRMR = 0.048, CFI = 0.98). Using IRT, 13 problematic items were identified, of which 9 were common with CTT. This study tested different models with fewer problematic items found in a three-factor model. Using a non-parametric IRT and CTT for item purification gave complementary results. IRT is still scarcely used and can be an interesting alternative method to enhance the quality of a measurement instrument. More studies are needed on the WRFQ-CF to refine its items and factorial composition.

  12. Applicability of Item Response Theory to the Korean Nurses' Licensing Examination

    Directory of Open Access Journals (Sweden)

    Geum-Hee Jeong

    2005-06-01

    Full Text Available To test the applicability of item response theory (IRT to the Korean Nurses' Licensing Examination (KNLE, item analysis was performed after testing the unidimensionality and goodness-of-fit. The results were compared with those based on classical test theory. The results of the 330-item KNLE administered to 12,024 examinees in January 2004 were analyzed. Unidimensionality was tested using DETECT and the goodness-of-fit was tested using WINSTEPS for the Rasch model and Bilog-MG for the two-parameter logistic model. Item analysis and ability estimation were done using WINSTEPS. Using DETECT, Dmax ranged from 0.1 to 0.23 for each subject. The mean square value of the infit and outfit values of all items using WINSTEPS ranged from 0.1 to 1.5, except for one item in pediatric nursing, which scored 1.53. Of the 330 items, 218 (42.7% were misfit using the two-parameter logistic model of Bilog-MG. The correlation coefficients between the difficulty parameter using the Rasch model and the difficulty index from classical test theory ranged from 0.9039 to 0.9699. The correlation between the ability parameter using the Rasch model and the total score from classical test theory ranged from 0.9776 to 0.9984. Therefore, the results of the KNLE fit unidimensionality and goodness-of-fit for the Rasch model. The KNLE should be a good sample for analysis according to the IRT Rasch model, so further research using IRT is possible.

  13. Automated Model Fit Method for Diesel Engine Control Development

    NARCIS (Netherlands)

    Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

  14. Automated model fit method for diesel engine control development

    NARCIS (Netherlands)

    Seykens, X.L.J.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.J.H.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

  15. High dose rate (HDR) and low dose rate (LDR) interstitial irradiation (IRT) of the rat spinal cord

    International Nuclear Information System (INIS)

    Pop, Lucas A.M.; Plas, Mirjam van der; Skwarchuk, Mark W.; Hanssen, Alex E.J.; Kogel, Albert J. van der

    1997-01-01

    Purpose: To describe a newly developed technique to study radiation tolerance of rat spinal cord to continuous interstitial irradiation (IRT) at different dose rates. Material and methods: Two parallel catheters are inserted just laterally on each side of the vertebral bodies from the level of Th 10 to L 4 . These catheters are afterloaded with two 192 Ir wires of 4 cm length each (activity 1-2.3 mCi/cm) for the low dose rate (LDR) IRT or connected to the HDR micro-Selectron for the high dose rate (HDR) IRT. Spinal cord target volume is located at the level of Th 12 -L 2 . Due to the rapid dose fall-off around the implanted sources, a dose inhomogeneity across the spinal cord thickness is obtained in the dorso-ventral direction. Using the 100% reference dose (rate) at the ventral side of the spinal cord to prescribe the dose, experiments have been carried out to obtain complete dose response curves at average dose rates of 0.49, 0.96 and 120 Gy/h. Paralysis of the hind-legs after 5-6 months and histopathological examination of the spinal cord of each irradiated rat are used as experimental endpoints. Results: The histopathological damage seen after irradiation is clearly reflected the inhomogeneous dose distribution around the implanted catheters, with the damage predominantly located in the dorsal tract of the cord or dorsal roots. With each reduction in average dose rate, spinal cord radiation tolerance is significantly increased. When the dose is prescribed at the 100% reference dose rate, the ED 50 (induction of paresis in 50% of the animals) for the HDR-IRT is 17.3 Gy. If the average dose rate is reduced from 120 Gy/h to 0.96 or 0.49 Gy/h, a 2.9- or 4.7-fold increase in the ED 50 values to 50.3 Gy and 80.9 Gy is observed; for the dose prescribed at the 150% reference dose rate (dorsal side of cord) ED 50 values are 26.0, 75.5 and 121.4 Gy, respectively. Using different types of analysis and in dependence of the dose prescription and reference dose rate, the

  16. An R package for fitting age, period and cohort models

    Directory of Open Access Journals (Sweden)

    Adriano Decarli

    2014-11-01

    Full Text Available In this paper we present the R implementation of a GLIM macro which fits age-period-cohort model following Osmond and Gardner. In addition to the estimates of the corresponding model, owing to the programming capability of R as an object oriented language, methods for printing, plotting and summarizing the results are provided. Furthermore, the researcher has fully access to the output of the main function (apc which returns all the models fitted within the function. It is so possible to critically evaluate the goodness of fit of the resulting model.

  17. Psychometrics of the Fitness-to-Drive Screening Measure.

    Science.gov (United States)

    Classen, Sherrilene; Velozo, Craig A; Winter, Sandra M; Bédard, Michel; Wang, Yanning

    2015-01-01

    We employed item response theory (IRT), specifically using Rasch modeling, to determine the measurement precision of the Fitness-to-Drive Screening Measure (FTDS), a tool that can be used by caregivers and occupational therapists to help detect at-risk drivers. We examined unidimensionality through the factor structure (how items contribute to the central construct of fitness to drive), rating scale (use of the categories of the rating scale), item/person-level separation (distinguishing between items with different difficulty levels or persons with different ability levels) and reliability, item hierarchy (easier driving items advancing to more difficult driving items), rater reliability, rater effects (severity vs. leniency of a rater), and criterion validity of the FTDS to an on-road assessment, via three rater groups (n = 200 older drivers; n = 200 caregivers; n = 2 evaluators). The FTDS is unidimensional, the rating scale performed well, has good person (> 3.07) and item (> 5.43) separation, good person (> 0.90) and item reliability (> 0.97), with < 10% misfitting items for two rater groups (caregivers and drivers). The intraclass correlation (ICC) coefficient among the three rater groups was significant (.253, p < .001) and the evaluators were the most severe raters. When comparing the caregivers' FTDS rating with the drivers' on-road assessment, the areas under the curve (index of discriminability; caregivers .726, p < .001) suggested concurrent validity between the FTDS and the on-road assessment. Despite limitations, the FTDS is a reliable and accurate screening measure for caregivers to help identify at-risk older drivers and for occupational therapy practitioners to start conversations about driving.

  18. Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

    Directory of Open Access Journals (Sweden)

    Grant B. Morgan

    2015-02-01

    Full Text Available Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.

  19. Robust Scale Transformation Methods in IRT True Score Equating under Common-Item Nonequivalent Groups Design

    Science.gov (United States)

    He, Yong

    2013-01-01

    Common test items play an important role in equating multiple test forms under the common-item nonequivalent groups design. Inconsistent item parameter estimates among common items can lead to large bias in equated scores for IRT true score equating. Current methods extensively focus on detection and elimination of outlying common items, which…

  20. Does model fit decrease the uncertainty of the data in comparison with a general non-model least squares fit?

    International Nuclear Information System (INIS)

    Pronyaev, V.G.

    2003-01-01

    The information entropy is taken as a measure of knowledge about the object and the reduced univariante variance as a common measure of uncertainty. Covariances in the model versus non-model least square fits are discussed

  1. New tests of the common calibration context for ISO, IRTS, and MSX

    Science.gov (United States)

    Cohen, Martin

    1997-01-01

    The work carried out in order to test, verify and validate the accuracy of the calibration spectra provided to the Infrared Space Observatory (ISO), to the Infrared Telescope in Space (IRTS) and to the Midcourse Space Experiment (MSX) for external calibration support of instruments, is reviewed. The techniques, used to vindicate the accuracy of the absolute spectra, are discussed. The work planned for comparing far infrared spectra of Mars and some of the bright stellar calibrators with long wavelength spectrometer data are summarized.

  2. Efficient occupancy model-fitting for extensive citizen-science data

    Science.gov (United States)

    Morgan, Byron J. T.; Freeman, Stephen N.; Ridout, Martin S.; Brereton, Tom M.; Fox, Richard; Powney, Gary D.; Roy, David B.

    2017-01-01

    Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen

  3. Extended Mixed-Efects Item Response Models with the MH-RM Algorithm

    Science.gov (United States)

    Chalmers, R. Philip

    2015-01-01

    A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…

  4. Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

    Science.gov (United States)

    Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

    2014-05-01

    The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on

  5. Landslide Mapping and Characterization through Infrared Thermography (IRT: Suggestions for a Methodological Approach from Some Case Studies

    Directory of Open Access Journals (Sweden)

    William Frodella

    2017-12-01

    Full Text Available In this paper, the potential of Infrared Thermography (IRT as a novel operational tool for landslide surveying, mapping and characterization was tested and demonstrated in different case studies, by analyzing various types of instability processes (rock slide/fall, roto-translational slide-flow. In particular, IRT was applied, both from terrestrial and airborne platforms, in an integrated methodology with other geomatcs methods, such as terrestrial laser scanning (TLS and global positioning systems (GPS, for the detection and mapping of landslides’ potentially hazardous structural and morphological features (structural discontinuities and open fractures, scarps, seepage and moisture zones, landslide drainage network and ponds. Depending on the study areas’ hazard context, the collected remotely sensed data were validated through field inspections, with the purpose of studying and verifying the causes of mass movements. The challenge of this work is to go beyond the current state of the art of IRT in landslide studies, with the aim of improving and extending the investigative capacity of the analyzed technique, in the framework of a growing demand for effective Civil Protection procedures in landslide geo-hydrological disaster managing activities. The proposed methodology proved to be an effective tool for landslide analysis, especially in the field of emergency management, when it is often necessary to gather all the required information in dangerous environments as fast as possible, to be used for the planning of mitigation measures and the evaluation of hazardous scenarios. Advantages and limitations of the proposed method in the field of the explored applications were evaluated, as well as general operative recommendations and future perspectives.

  6. Sensitivity of Fit Indices to Misspecification in Growth Curve Models

    Science.gov (United States)

    Wu, Wei; West, Stephen G.

    2010-01-01

    This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…

  7. Neutron polarizing set-up of the Sofia IRT research reactor

    International Nuclear Information System (INIS)

    Krezhov, K.; Mikhajlova, V.; Okorokov, A.

    1990-01-01

    Neutron polarizing set-up of one of the horizontal beam tubes of the IRT-200 research reactor of the Bulgarian Institute of Nuclear Research and Nuclear Energy is presented. Neutron mirrors are extensively used in an effort to compensate the moderate reactor beam intensity by the high reflected intensity and wide-band transmittance of the mirror neutron guides. Time-to-flight technique using a slotted neutron absorbing chopper with a horizontal rotation axis has been applied to obtain the exit neutron spectra. Beam polarization and flipping ratios have been determined. Cadmium ratio in the polarized beam has been found almost 10 4 and the average polarization has been measured to be higher than 96%. 3 figs, 3 refs

  8. Standard error propagation in R-matrix model fitting for light elements

    International Nuclear Information System (INIS)

    Chen Zhenpeng; Zhang Rui; Sun Yeying; Liu Tingjin

    2003-01-01

    The error propagation features with R-matrix model fitting 7 Li, 11 B and 17 O systems were researched systematically. Some laws of error propagation were revealed, an empirical formula P j = U j c / U j d = K j · S-bar · √m / √N for describing standard error propagation was established, the most likely error ranges for standard cross sections of 6 Li(n,t), 10 B(n,α0) and 10 B(n,α1) were estimated. The problem that the standard error of light nuclei standard cross sections may be too small results mainly from the R-matrix model fitting, which is not perfect. Yet R-matrix model fitting is the most reliable evaluation method for such data. The error propagation features of R-matrix model fitting for compound nucleus system of 7 Li, 11 B and 17 O has been studied systematically, some laws of error propagation are revealed, and these findings are important in solving the problem mentioned above. Furthermore, these conclusions are suitable for similar model fitting in other scientific fields. (author)

  9. Model-fitting approach to kinetic analysis of non-isothermal oxidation of molybdenite

    International Nuclear Information System (INIS)

    Ebrahimi Kahrizsangi, R.; Abbasi, M. H.; Saidi, A.

    2007-01-01

    The kinetics of molybdenite oxidation was studied by non-isothermal TGA-DTA with heating rate 5 d eg C .min -1 . The model-fitting kinetic approach applied to TGA data. The Coats-Redfern method used of model fitting. The popular model-fitting gives excellent fit non-isothermal data in chemically controlled regime. The apparent activation energy was determined to be about 34.2 kcalmol -1 With pre-exponential factor about 10 8 sec -1 for extent of reaction less than 0.5

  10. Design and Preliminary Results of a Feedback Circuit for Plasma Displacement Control in IR-T1 Tokamak

    International Nuclear Information System (INIS)

    TalebiTaher, A.; Ghoranneviss, M.; Tarkeshian, R.; Salem, M. K.; Khorshid, P.

    2008-01-01

    Since displacement is very important for plasma position control, in IR-T1 tokamak a combination of two cosine coils and two saddle sine coils is used for horizontal displacement measurement. According to the multiple moment theory, the output of these coils linearly depends to radial displacement of plasma column. A new circuit for adding these signals to feedback system designed and unwanted effects of other fields in final output compensated. After compensation and calibration of the system, the output of horizontal displacement circuits applied to feedback control system. By considers the required auxiliary vertical field, a proportional amplifier and driver circuit are constructed to drive power transistors these power transistors switch the feedback bank capacitors. In the experiment, a good linear proportionality between displacement and output observed by applying an appropriate feedback field, the linger confinement time in IR-T1 tokamak obtained, applying this system to discharge increased the plasma duration and realizes repetitive discharges

  11. IRT models with relaxed assumptions in eRm: A manual-like instruction

    Directory of Open Access Journals (Sweden)

    REINHOLD HATZINGER

    2009-03-01

    Full Text Available Linear logistic models with relaxed assumptions (LLRA as introduced by Fischer (1974 are a flexible tool for the measurement of change for dichotomous or polytomous responses. As opposed to the Rasch model, assumptions on dimensionality of items, their mutual dependencies and the distribution of the latent trait in the population of subjects are relaxed. Conditional maximum likelihood estimation allows for inference about treatment, covariate or trend effect parameters without taking the subjects' latent trait values into account. In this paper we will show how LLRAs based on the LLTM, LRSM and LPCM can be used to answer various questions about the measurement of change and how they can be fitted in R using the eRm package. A number of small didactic examples is provided that can easily be used as templates for real data sets. All datafiles used in this paper are available from http://eRm.R-Forge.R-project.org/

  12. When the model fits the frame: the impact of regulatory fit on efficacy appraisal and persuasion in health communication.

    Science.gov (United States)

    Bosone, Lucia; Martinez, Frédéric; Kalampalikis, Nikos

    2015-04-01

    In health-promotional campaigns, positive and negative role models can be deployed to illustrate the benefits or costs of certain behaviors. The main purpose of this article is to investigate why, how, and when exposure to role models strengthens the persuasiveness of a message, according to regulatory fit theory. We argue that exposure to a positive versus a negative model activates individuals' goals toward promotion rather than prevention. By means of two experiments, we demonstrate that high levels of persuasion occur when a message advertising healthy dietary habits offers a regulatory fit between its framing and the described role model. Our data also establish that the effects of such internal regulatory fit by vicarious experience depend on individuals' perceptions of response-efficacy and self-efficacy. Our findings constitute a significant theoretical complement to previous research on regulatory fit and contain valuable practical implications for health-promotional campaigns. © 2015 by the Society for Personality and Social Psychology, Inc.

  13. A quantitative comparison of noise reduction across five commercial (hybrid and model-based) iterative reconstruction techniques: an anthropomorphic phantom study.

    Science.gov (United States)

    Patino, Manuel; Fuentes, Jorge M; Hayano, Koichi; Kambadakone, Avinash R; Uyeda, Jennifer W; Sahani, Dushyant V

    2015-02-01

    OBJECTIVE. The objective of our study was to compare the performance of three hybrid iterative reconstruction techniques (IRTs) (ASiR, iDose4, SAFIRE) and their respective strengths for image noise reduction on low-dose CT examinations using filtered back projection (FBP) as the standard reference. Also, we compared the performance of these three hybrid IRTs with two model-based IRTs (Veo and IMR) for image noise reduction on low-dose examinations. MATERIALS AND METHODS. An anthropomorphic abdomen phantom was scanned at 100 and 120 kVp and different tube current-exposure time products (25-100 mAs) on three CT systems (for ASiR and Veo, Discovery CT750 HD; for iDose4 and IMR, Brilliance iCT; and for SAFIRE, Somatom Definition Flash). Images were reconstructed using FBP and using IRTs at various strengths. Nine noise measurements (mean ROI size, 423 mm(2)) on extracolonic fat for the different strengths of IRTs were recorded and compared with FBP using ANOVA. Radiation dose, which was measured as the volume CT dose index and dose-length product, was also compared. RESULTS. There were no significant differences in radiation dose and image noise among the scanners when FBP was used (p > 0.05). Gradual image noise reduction was observed with each increasing increment of hybrid IRT strength, with a maximum noise suppression of approximately 50% (48.2-53.9%). Similar noise reduction was achieved on the scanners by applying specific hybrid IRT strengths. Maximum noise reduction was higher on model-based IRTs (68.3-81.1%) than hybrid IRTs (48.2-53.9%) (p < 0.05). CONCLUSION. When constant scanning parameters are used, radiation dose and image noise on FBP are similar for CT scanners made by different manufacturers. Significant image noise reduction is achieved on low-dose CT examinations rendered with IRTs. The image noise on various scanners can be matched by applying specific hybrid IRT strengths. Model-based IRTs attain substantially higher noise reduction than hybrid

  14. Flexible competing risks regression modeling and goodness-of-fit

    DEFF Research Database (Denmark)

    Scheike, Thomas; Zhang, Mei-Jie

    2008-01-01

    In this paper we consider different approaches for estimation and assessment of covariate effects for the cumulative incidence curve in the competing risks model. The classic approach is to model all cause-specific hazards and then estimate the cumulative incidence curve based on these cause...... models that is easy to fit and contains the Fine-Gray model as a special case. One advantage of this approach is that our regression modeling allows for non-proportional hazards. This leads to a new simple goodness-of-fit procedure for the proportional subdistribution hazards assumption that is very easy...... of the flexible regression models to analyze competing risks data when non-proportionality is present in the data....

  15. Critical elements on fitting the Bayesian multivariate Poisson Lognormal model

    Science.gov (United States)

    Zamzuri, Zamira Hasanah binti

    2015-10-01

    Motivated by a problem on fitting multivariate models to traffic accident data, a detailed discussion of the Multivariate Poisson Lognormal (MPL) model is presented. This paper reveals three critical elements on fitting the MPL model: the setting of initial estimates, hyperparameters and tuning parameters. These issues have not been highlighted in the literature. Based on simulation studies conducted, we have shown that to use the Univariate Poisson Model (UPM) estimates as starting values, at least 20,000 iterations are needed to obtain reliable final estimates. We also illustrated the sensitivity of the specific hyperparameter, which if it is not given extra attention, may affect the final estimates. The last issue is regarding the tuning parameters where they depend on the acceptance rate. Finally, a heuristic algorithm to fit the MPL model is presented. This acts as a guide to ensure that the model works satisfactorily given any data set.

  16. Fitting ARMA Time Series by Structural Equation Models.

    Science.gov (United States)

    van Buuren, Stef

    1997-01-01

    This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

  17. Annual report of the working group 'fuel pin and fuel element mechanics' of the Institut fuer Reaktortechnik (IRT) of the Technische Hochschule Darmstadt for the Fast Breeder Project

    International Nuclear Information System (INIS)

    Fabian, H.; Humbach, W.; Lassmann, K.; Mueller, J.J.; Preusser, T.; Schmelz, K.

    1978-09-01

    This report comprises six single lectures given at an information meeting organized by the Institut fuer Reaktortechnik der Technischen Hochschule Darmstadt (IRT) in Darmstadt on April 24, 1978. The lectures are an account of work performed at IRT on the mechanics of fuel pins and fuel elements and supported by the Fast Breeder Project (PSB) of KfK. These activities can be broken down into studies of the integral fuel pin (URANUS computer code) and into multidimensional studies of the fuel pin using the finite-element method (FINEL and ZIDRIG computer codes). Moreover, a report is presented of the status of the test facility for simulation of out-of-pile cladding tube loads and of the IRT project on the simulation and analysis of radiation damage. (orig./GL) [de

  18. Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.

    Science.gov (United States)

    Enns, Eva A; Cipriano, Lauren E; Simons, Cyrena T; Kong, Chung Yin

    2015-02-01

    To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. © The Author(s) 2014.

  19. Gfitter - Revisiting the global electroweak fit of the Standard Model and beyond

    Energy Technology Data Exchange (ETDEWEB)

    Flaecher, H.; Hoecker, A. [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Goebel, M. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)]|[Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Haller, J. [Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Moenig, K.; Stelzer, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)

    2008-11-15

    The global fit of the Standard Model to electroweak precision data, routinely performed by the LEP electroweak working group and others, demonstrated impressively the predictive power of electroweak unification and quantum loop corrections. We have revisited this fit in view of (i) the development of the new generic fitting package, Gfitter, allowing flexible and efficient model testing in high-energy physics, (ii) the insertion of constraints from direct Higgs searches at LEP and the Tevatron, and (iii) a more thorough statistical interpretation of the results. Gfitter is a modular fitting toolkit, which features predictive theoretical models as independent plugins, and a statistical analysis of the fit results using toy Monte Carlo techniques. The state-of-the-art electroweak Standard Model is fully implemented, as well as generic extensions to it. Theoretical uncertainties are explicitly included in the fit through scale parameters varying within given error ranges. This paper introduces the Gfitter project, and presents state-of-the-art results for the global electroweak fit in the Standard Model, and for a model with an extended Higgs sector (2HDM). Numerical and graphical results for fits with and without including the constraints from the direct Higgs searches at LEP and Tevatron are given. Perspectives for future colliders are analysed and discussed. Including the direct Higgs searches, we find M{sub H}=116.4{sup +18.3}{sub -1.3} GeV, and the 2{sigma} and 3{sigma} allowed regions [114,145] GeV and [[113,168] and [180,225

  20. SPSS macros to compare any two fitted values from a regression model.

    Science.gov (United States)

    Weaver, Bruce; Dubois, Sacha

    2012-12-01

    In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.

  1. LEP asymmetries and fits of the standard model

    International Nuclear Information System (INIS)

    Pietrzyk, B.

    1994-01-01

    The lepton and quark asymmetries measured at LEP are presented. The results of the Standard Model fits to the electroweak data presented at this conference are given. The top mass obtained from the fit to the LEP data is 172 -14-20 +13+18 GeV; it is 177 -11-19 +11+18 when also the collider, ν and A LR data are included. (author). 10 refs., 3 figs., 2 tabs

  2. Management and inspection of integrity of spent fuel from IRT MEPhI research reactor

    International Nuclear Information System (INIS)

    Aden, V.G.; Bulkin, S.Y.; Sokolov, A.V.; Bushuev, A.V.; Redkin, A.F.; Portnov, A.A.

    2002-01-01

    The information on wet storage and dry storage of the spent nuclear fuel (SNF) of the IRT MEPhI reactor and experience from SNF shipment for reprocessing are presented. The procedure and a facility for nondestructive inspection of local power density fields and the burnup of fuel assemblies based on studying the γ-activity of some fission products generated in U 235 and procedure for inspection of the fuel element cladding leak tightness are described. (author)

  3. MCMC estimation of multidimensional IRT models

    NARCIS (Netherlands)

    Beguin, Anton; Glas, Cornelis A.W.

    1998-01-01

    A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization to a model with multidimensional ability parameters are discussed. The procedure is a generalization of a procedure by J. Albert (1992) for estimating the two-parameter normal ogive model. The procedure will

  4. Checking the Adequacy of Fit of Models from Split-Plot Designs

    DEFF Research Database (Denmark)

    Almini, A. A.; Kulahci, Murat; Montgomery, D. C.

    2009-01-01

    models. In this article, we propose the computation of two R-2, R-2-adjusted, prediction error sums of squares (PRESS), and R-2-prediction statistics to measure the adequacy of fit for the WP and the SP submodels in a split-plot design. This is complemented with the graphical analysis of the two types......One of the main features that distinguish split-plot experiments from other experiments is that they involve two types of experimental errors: the whole-plot (WP) error and the subplot (SP) error. Taking this into consideration is very important when computing measures of adequacy of fit for split-plot...... of errors to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. Using examples, we show how computing two measures of model adequacy of fit for each split-plot design model is appropriate and useful as they reveal whether the correct WP and SP effects have...

  5. Evaluation properties of the French version of the OUT-PATSAT35 satisfaction with care questionnaire according to classical and item response theory analyses.

    Science.gov (United States)

    Panouillères, M; Anota, A; Nguyen, T V; Brédart, A; Bosset, J F; Monnier, A; Mercier, M; Hardouin, J B

    2014-09-01

    The present study investigates the properties of the French version of the OUT-PATSAT35 questionnaire, which evaluates the outpatients' satisfaction with care in oncology using classical analysis (CTT) and item response theory (IRT). This cross-sectional multicenter study includes 692 patients who completed the questionnaire at the end of their ambulatory treatment. CTT analyses tested the main psychometric properties (convergent and divergent validity, and internal consistency). IRT analyses were conducted separately for each OUT-PATSAT35 domain (the doctors, the nurses or the radiation therapists and the services/organization) by models from the Rasch family. We examined the fit of the data to the model expectations and tested whether the model assumptions of unidimensionality, monotonicity and local independence were respected. A total of 605 (87.4%) respondents were analyzed with a mean age of 64 years (range 29-88). Internal consistency for all scales separately and for the three main domains was good (Cronbach's α 0.74-0.98). IRT analyses were performed with the partial credit model. No disordered thresholds of polytomous items were found. Each domain showed high reliability but fitted poorly to the Rasch models. Three items in particular, the item about "promptness" in the doctors' domain and the items about "accessibility" and "environment" in the services/organization domain, presented the highest default of fit. A correct fit of the Rasch model can be obtained by dropping these items. Most of the local dependence concerned items about "information provided" in each domain. A major deviation of unidimensionality was found in the nurses' domain. CTT showed good psychometric properties of the OUT-PATSAT35. However, the Rasch analysis revealed some misfitting and redundant items. Taking the above problems into consideration, it could be interesting to refine the questionnaire in a future study.

  6. Repair models of cell survival and corresponding computer program for survival curve fitting

    International Nuclear Information System (INIS)

    Shen Xun; Hu Yiwei

    1992-01-01

    Some basic concepts and formulations of two repair models of survival, the incomplete repair (IR) model and the lethal-potentially lethal (LPL) model, are introduced. An IBM-PC computer program for survival curve fitting with these models was developed and applied to fit the survivals of human melanoma cells HX118 irradiated at different dose rates. Comparison was made between the repair models and two non-repair models, the multitar get-single hit model and the linear-quadratic model, in the fitting and analysis of the survival-dose curves. It was shown that either IR model or LPL model can fit a set of survival curves of different dose rates with same parameters and provide information on the repair capacity of cells. These two mathematical models could be very useful in quantitative study on the radiosensitivity and repair capacity of cells

  7. HDFITS: Porting the FITS data model to HDF5

    Science.gov (United States)

    Price, D. C.; Barsdell, B. R.; Greenhill, L. J.

    2015-09-01

    The FITS (Flexible Image Transport System) data format has been the de facto data format for astronomy-related data products since its inception in the late 1970s. While the FITS file format is widely supported, it lacks many of the features of more modern data serialization, such as the Hierarchical Data Format (HDF5). The HDF5 file format offers considerable advantages over FITS, such as improved I/O speed and compression, but has yet to gain widespread adoption within astronomy. One of the major holdbacks is that HDF5 is not well supported by data reduction software packages and image viewers. Here, we present a comparison of FITS and HDF5 as a format for storage of astronomy datasets. We show that the underlying data model of FITS can be ported to HDF5 in a straightforward manner, and that by doing so the advantages of the HDF5 file format can be leveraged immediately. In addition, we present a software tool, fits2hdf, for converting between FITS and a new 'HDFITS' format, where data are stored in HDF5 in a FITS-like manner. We show that HDFITS allows faster reading of data (up to 100x of FITS in some use cases), and improved compression (higher compression ratios and higher throughput). Finally, we show that by only changing the import lines in Python-based FITS utilities, HDFITS formatted data can be presented transparently as an in-memory FITS equivalent.

  8. Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.

    Science.gov (United States)

    Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

    2018-03-12

    Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.

  9. A Review of the Effects on IRT Item Parameter Estimates with a Focus on Misbehaving Common Items in Test Equating.

    Science.gov (United States)

    Michaelides, Michalis P

    2010-01-01

    Many studies have investigated the topic of change or drift in item parameter estimates in the context of item response theory (IRT). Content effects, such as instructional variation and curricular emphasis, as well as context effects, such as the wording, position, or exposure of an item have been found to impact item parameter estimates. The issue becomes more critical when items with estimates exhibiting differential behavior across test administrations are used as common for deriving equating transformations. This paper reviews the types of effects on IRT item parameter estimates and focuses on the impact of misbehaving or aberrant common items on equating transformations. Implications relating to test validity and the judgmental nature of the decision to keep or discard aberrant common items are discussed, with recommendations for future research into more informed and formal ways of dealing with misbehaving common items.

  10. Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

    Science.gov (United States)

    Clark, D Angus; Bowles, Ryan P

    2018-04-23

    In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

  11. Item selection via Bayesian IRT models.

    Science.gov (United States)

    Arima, Serena

    2015-02-10

    With reference to a questionnaire that aimed to assess the quality of life for dysarthric speakers, we investigate the usefulness of a model-based procedure for reducing the number of items. We propose a mixed cumulative logit model, which is known in the psychometrics literature as the graded response model: responses to different items are modelled as a function of individual latent traits and as a function of item characteristics, such as their difficulty and their discrimination power. We jointly model the discrimination and the difficulty parameters by using a k-component mixture of normal distributions. Mixture components correspond to disjoint groups of items. Items that belong to the same groups can be considered equivalent in terms of both difficulty and discrimination power. According to decision criteria, we select a subset of items such that the reduced questionnaire is able to provide the same information that the complete questionnaire provides. The model is estimated by using a Bayesian approach, and the choice of the number of mixture components is justified according to information criteria. We illustrate the proposed approach on the basis of data that are collected for 104 dysarthric patients by local health authorities in Lecce and in Milan. Copyright © 2014 John Wiley & Sons, Ltd.

  12. Modelling population dynamics model formulation, fitting and assessment using state-space methods

    CERN Document Server

    Newman, K B; Morgan, B J T; King, R; Borchers, D L; Cole, D J; Besbeas, P; Gimenez, O; Thomas, L

    2014-01-01

    This book gives a unifying framework for estimating the abundance of open populations: populations subject to births, deaths and movement, given imperfect measurements or samples of the populations.  The focus is primarily on populations of vertebrates for which dynamics are typically modelled within the framework of an annual cycle, and for which stochastic variability in the demographic processes is usually modest. Discrete-time models are developed in which animals can be assigned to discrete states such as age class, gender, maturity,  population (within a metapopulation), or species (for multi-species models). The book goes well beyond estimation of abundance, allowing inference on underlying population processes such as birth or recruitment, survival and movement. This requires the formulation and fitting of population dynamics models.  The resulting fitted models yield both estimates of abundance and estimates of parameters characterizing the underlying processes.  

  13. Revisiting the Global Electroweak Fit of the Standard Model and Beyond with Gfitter

    CERN Document Server

    Flächer, Henning; Haller, J; Höcker, A; Mönig, K; Stelzer, J

    2009-01-01

    The global fit of the Standard Model to electroweak precision data, routinely performed by the LEP electroweak working group and others, demonstrated impressively the predictive power of electroweak unification and quantum loop corrections. We have revisited this fit in view of (i) the development of the new generic fitting package, Gfitter, allowing flexible and efficient model testing in high-energy physics, (ii) the insertion of constraints from direct Higgs searches at LEP and the Tevatron, and (iii) a more thorough statistical interpretation of the results. Gfitter is a modular fitting toolkit, which features predictive theoretical models as independent plugins, and a statistical analysis of the fit results using toy Monte Carlo techniques. The state-of-the-art electroweak Standard Model is fully implemented, as well as generic extensions to it. Theoretical uncertainties are explicitly included in the fit through scale parameters varying within given error ranges. This paper introduces the Gfitter projec...

  14. Modern psychometrics applied in rheumatology--a systematic review.

    Science.gov (United States)

    Siemons, Liseth; Ten Klooster, Peter M; Taal, Erik; Glas, Cees Aw; Van de Laar, Mart Afj

    2012-10-31

    Although item response theory (IRT) appears to be increasingly used within health care research in general, a comprehensive overview of the frequency and characteristics of IRT analyses within the rheumatic field is lacking. An overview of the use and application of IRT in rheumatology to date may give insight into future research directions and highlight new possibilities for the improvement of outcome assessment in rheumatic conditions. Therefore, this study systematically reviewed the application of IRT to patient-reported and clinical outcome measures in rheumatology. Literature searches in PubMed, Scopus and Web of Science resulted in 99 original English-language articles which used some form of IRT-based analysis of patient-reported or clinical outcome data in patients with a rheumatic condition. Both general study information and IRT-specific information were assessed. Most studies used Rasch modeling for developing or evaluating new or existing patient-reported outcomes in rheumatoid arthritis or osteoarthritis patients. Outcomes of principle interest were physical functioning and quality of life. Since the last decade, IRT has also been applied to clinical measures more frequently. IRT was mostly used for evaluating model fit, unidimensionality and differential item functioning, the distribution of items and persons along the underlying scale, and reliability. Less frequently used IRT applications were the evaluation of local independence, the threshold ordering of items, and the measurement precision along the scale. IRT applications have markedly increased within rheumatology over the past decades. To date, IRT has primarily been applied to patient-reported outcomes, however, applications to clinical measures are gaining interest. Useful IRT applications not yet widely used within rheumatology include the cross-calibration of instrument scores and the development of computerized adaptive tests which may reduce the measurement burden for both the patient

  15. Tests of fit of historically-informed models of African American Admixture.

    Science.gov (United States)

    Gross, Jessica M

    2018-02-01

    African American populations in the U.S. formed primarily by mating between Africans and Europeans over the last 500 years. To date, studies of admixture have focused on either a one-time admixture event or continuous input into the African American population from Europeans only. Our goal is to gain a better understanding of the admixture process by examining models that take into account (a) assortative mating by ancestry in the African American population, (b) continuous input from both Europeans and Africans, and (c) historically informed variation in the rate of African migration over time. We used a model-based clustering method to generate distributions of African ancestry in three samples comprised of 147 African Americans from two published sources. We used a log-likelihood method to examine the fit of four models to these distributions and used a log-likelihood ratio test to compare the relative fit of each model. The mean ancestry estimates for our datasets of 77% African/23% European to 83% African/17% European ancestry are consistent with previous studies. We find admixture models that incorporate continuous gene flow from Europeans fit significantly better than one-time event models, and that a model involving continuous gene flow from Africans and Europeans fits better than one with continuous gene flow from Europeans only for two samples. Importantly, models that involve continuous input from Africans necessitate a higher level of gene flow from Europeans than previously reported. We demonstrate that models that take into account information about the rate of African migration over the past 500 years fit observed patterns of African ancestry better than alternative models. Our approach will enrich our understanding of the admixture process in extant and past populations. © 2017 Wiley Periodicals, Inc.

  16. [How to fit and interpret multilevel models using SPSS].

    Science.gov (United States)

    Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

    2007-05-01

    Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

  17. A Comparison between Linear IRT Observed-Score Equating and Levine Observed-Score Equating under the Generalized Kernel Equating Framework

    Science.gov (United States)

    Chen, Haiwen

    2012-01-01

    In this article, linear item response theory (IRT) observed-score equating is compared under a generalized kernel equating framework with Levine observed-score equating for nonequivalent groups with anchor test design. Interestingly, these two equating methods are closely related despite being based on different methodologies. Specifically, when…

  18. A versatile curve-fit model for linear to deeply concave rank abundance curves

    NARCIS (Netherlands)

    Neuteboom, J.H.; Struik, P.C.

    2005-01-01

    A new, flexible curve-fit model for linear to concave rank abundance curves was conceptualized and validated using observational data. The model links the geometric-series model and log-series model and can also fit deeply concave rank abundance curves. The model is based ¿ in an unconventional way

  19. Possible use of dual purpose dry storage casks for transportation and future storage of spent nuclear fuel from IRT-Sofia

    International Nuclear Information System (INIS)

    Manev, L.; Baltiyski, M.

    2003-01-01

    Objectives: The main objective of the present paper is related to one of the priority goals stipulated in Bulgarian Governmental Decision No.332 from May 17, 1999 - removal of SNF from IRT-Sofia site and its exporting for reprocessing and/or for temporary storage at Kozloduy NPP site. The variant of using dual purpose dry storage casks for transportation and future temporary storage of SNF from IRT-Sofia aims to find out a reasonable alternative of the existing till now variant for temporary SNF storage under water in the existing Kozloduy NPP Spent Fuel Storage Facility until its export for reprocessing. Results: Based on the given data for the condition of 73 Spent Nuclear Fuel Assemblies (SNFA) stored in the storage pool and technical data as well as data for available equipment and IRT-Sofia layout the following framework are specified: draft technical features of dual purpose dry storage casks and their overall dimensions; the suitability of the available equipment for safety and reliable performance of transportation and handling operations of assemblies from storage pool to dual purpose dry storage casks; the necessity of new equipment for performance of the above mentioned operations; Assemblies' transportation and handling operations are described; requirements to and conditions for future safety and reliable storage of SNFA loaded casks are determined. When selecting the technical solutions for safety assurance during performance of site handling operations of IRT-Sofia and for description of the exemplary casks the Effective Bulgarian Regulations are considered. The experience of other countries in performance of transfer and transportation of SNFA from such types of research reactors is taken into account. Also, Kozloduy NPP experience in SNF handling operations is taken into account. Conclusions: The Decision of Council of Minister for refurbishment of research reactor into a low power one and its future utilization for experimental and training

  20. Quality of life in the Danish general population--normative data and validity of WHOQOL-BREF using Rasch and item response theory models

    DEFF Research Database (Denmark)

    Noerholm, V; Groenvold, M; Watt, T

    2004-01-01

    BACKGROUND: The main objective of this study was to investigate the construct validity of the WHOQOL-BREF by use of Rasch and Item Response Theory models and to examine the stability of the model across high/low scoring individuals, gender, education, and depressive illness. Furthermore......, the objective of the study was to estimate the reference data for the quality of life questionnaire WHOQOL-BREF in the general Danish population and in subgroups defined by age, gender, and education. METHODS: Mail-out-mail-back questionnaires were sent to a randomly selected sample of the Danish general...... population. The response rate was 68.5%, and the sample reported here contained 1101 respondents: 578 women and 519 men (four respondents did not indicate their genders). RESULTS: Each of the four domains of the WHOQOL-BREF scale fitted a two-parameter IRT model, but did not fit the Rasch model. Due...

  1. Fitting Equilibrium Search Models to Labour Market Data

    DEFF Research Database (Denmark)

    Bowlus, Audra J.; Kiefer, Nicholas M.; Neumann, George R.

    1996-01-01

    Specification and estimation of a Burdett-Mortensen type equilibrium search model is considered. The estimation is nonstandard. An estimation strategy asymptotically equivalent to maximum likelihood is proposed and applied. The results indicate that specifications with a small number of productiv...... of productivity types fit the data well compared to the homogeneous model....

  2. Fast Algorithms for Fitting Active Appearance Models to Unconstrained Images

    NARCIS (Netherlands)

    Tzimiropoulos, Georgios; Pantic, Maja

    2016-01-01

    Fitting algorithms for Active Appearance Models (AAMs) are usually considered to be robust but slow or fast but less able to generalize well to unseen variations. In this paper, we look into AAM fitting algorithms and make the following orthogonal contributions: We present a simple “project-out‿

  3. Radiation conditions at the training IRT-2000 and IR-100 reactors

    International Nuclear Information System (INIS)

    Fedorin, Eh.V.; Bronshtejn, I.Eh; Martynov, Yu.N.; Chistyakov, N.I.

    1978-01-01

    The experience is reviewed of radiation hygiene surveys and radiation safety provision during instructional processes on two training and research nuclear reactors of the IRT-2000 type (No. 1 and No. 2) and on an IR-200 reactor. From an analysis of individual dosimetry data the conclusion is made that the trainees and personnel are exposed mainly to external gamma-radiation and also, to a minor degree, to thermal neutrons and beta-radiation. It has been found that a high level of radiation safety is ensured on the training and research so that research and instruction activities are conducted at annual levels of exposure substantially lower than 0.5 rem in the case of trainees and 5 rem in the case of personnel

  4. A dynamic Thurstonian item response theory of motive expression in the picture story exercise: solving the internal consistency paradox of the PSE.

    Science.gov (United States)

    Lang, Jonas W B

    2014-07-01

    The measurement of implicit or unconscious motives using the picture story exercise (PSE) has long been a target of debate in the psychological literature. Most debates have centered on the apparent paradox that PSE measures of implicit motives typically show low internal consistency reliability on common indices like Cronbach's alpha but nevertheless predict behavioral outcomes. I describe a dynamic Thurstonian item response theory (IRT) model that builds on dynamic system theories of motivation, theorizing on the PSE response process, and recent advancements in Thurstonian IRT modeling of choice data. To assess the models' capability to explain the internal consistency paradox, I first fitted the model to archival data (Gurin, Veroff, & Feld, 1957) and then simulated data based on bias-corrected model estimates from the real data. Simulation results revealed that the average squared correlation reliability for the motives in the Thurstonian IRT model was .74 and that Cronbach's alpha values were similar to the real data (value of extant evidence from motivational research using PSE motive measures. (c) 2014 APA, all rights reserved.

  5. Fast and exact Newton and Bidirectional fitting of Active Appearance Models.

    Science.gov (United States)

    Kossaifi, Jean; Tzimiropoulos, Yorgos; Pantic, Maja

    2016-12-21

    Active Appearance Models (AAMs) are generative models of shape and appearance that have proven very attractive for their ability to handle wide changes in illumination, pose and occlusion when trained in the wild, while not requiring large training dataset like regression-based or deep learning methods. The problem of fitting an AAM is usually formulated as a non-linear least squares one and the main way of solving it is a standard Gauss-Newton algorithm. In this paper we extend Active Appearance Models in two ways: we first extend the Gauss-Newton framework by formulating a bidirectional fitting method that deforms both the image and the template to fit a new instance. We then formulate a second order method by deriving an efficient Newton method for AAMs fitting. We derive both methods in a unified framework for two types of Active Appearance Models, holistic and part-based, and additionally show how to exploit the structure in the problem to derive fast yet exact solutions. We perform a thorough evaluation of all algorithms on three challenging and recently annotated inthe- wild datasets, and investigate fitting accuracy, convergence properties and the influence of noise in the initialisation. We compare our proposed methods to other algorithms and show that they yield state-of-the-art results, out-performing other methods while having superior convergence properties.

  6. The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

    Science.gov (United States)

    Tendeiro, Jorge N

    2017-01-01

    Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.

  7. Application of Item Response Theory to Tests of Substance-related Associative Memory

    Science.gov (United States)

    Shono, Yusuke; Grenard, Jerry L.; Ames, Susan L.; Stacy, Alan W.

    2015-01-01

    A substance-related word association test (WAT) is one of the commonly used indirect tests of substance-related implicit associative memory and has been shown to predict substance use. This study applied an item response theory (IRT) modeling approach to evaluate psychometric properties of the alcohol- and marijuana-related WATs and their items among 775 ethnically diverse at-risk adolescents. After examining the IRT assumptions, item fit, and differential item functioning (DIF) across gender and age groups, the original 18 WAT items were reduced to 14- and 15-items in the alcohol- and marijuana-related WAT, respectively. Thereafter, unidimensional one- and two-parameter logistic models (1PL and 2PL models) were fitted to the revised WAT items. The results demonstrated that both alcohol- and marijuana-related WATs have good psychometric properties. These results were discussed in light of the framework of a unified concept of construct validity (Messick, 1975, 1989, 1995). PMID:25134051

  8. Fit Gap Analysis – The Role of Business Process Reference Models

    Directory of Open Access Journals (Sweden)

    Dejan Pajk

    2013-12-01

    Full Text Available Enterprise resource planning (ERP systems support solutions for standard business processes such as financial, sales, procurement and warehouse. In order to improve the understandability and efficiency of their implementation, ERP vendors have introduced reference models that describe the processes and underlying structure of an ERP system. To select and successfully implement an ERP system, the capabilities of that system have to be compared with a company’s business needs. Based on a comparison, all of the fits and gaps must be identified and further analysed. This step usually forms part of ERP implementation methodologies and is called fit gap analysis. The paper theoretically overviews methods for applying reference models and describes fit gap analysis processes in detail. The paper’s first contribution is its presentation of a fit gap analysis using standard business process modelling notation. The second contribution is the demonstration of a process-based comparison approach between a supply chain process and an ERP system process reference model. In addition to its theoretical contributions, the results can also be practically applied to projects involving the selection and implementation of ERP systems.

  9. The effect of person misfit on classification decisions

    NARCIS (Netherlands)

    Hendrawan, I.; Glas, Cornelis A.W.; Meijer, R.R.

    2001-01-01

    The effect of person misfit to an item response theory (IRT) model on a mastery/nonmastery decision was investigated. Also investigated was whether the classification precision can be improved by identifying misfitting respondents using person-fit statistics. A simulation study was conducted to

  10. www.common-metrics.org: a web application to estimate scores from different patient-reported outcome measures on a common scale.

    Science.gov (United States)

    Fischer, H Felix; Rose, Matthias

    2016-10-19

    Recently, a growing number of Item-Response Theory (IRT) models has been published, which allow estimation of a common latent variable from data derived by different Patient Reported Outcomes (PROs). When using data from different PROs, direct estimation of the latent variable has some advantages over the use of sum score conversion tables. It requires substantial proficiency in the field of psychometrics to fit such models using contemporary IRT software. We developed a web application ( http://www.common-metrics.org ), which allows estimation of latent variable scores more easily using IRT models calibrating different measures on instrument independent scales. Currently, the application allows estimation using six different IRT models for Depression, Anxiety, and Physical Function. Based on published item parameters, users of the application can directly estimate latent trait estimates using expected a posteriori (EAP) for sum scores as well as for specific response patterns, Bayes modal (MAP), Weighted likelihood estimation (WLE) and Maximum likelihood (ML) methods and under three different prior distributions. The obtained estimates can be downloaded and analyzed using standard statistical software. This application enhances the usability of IRT modeling for researchers by allowing comparison of the latent trait estimates over different PROs, such as the Patient Health Questionnaire Depression (PHQ-9) and Anxiety (GAD-7) scales, the Center of Epidemiologic Studies Depression Scale (CES-D), the Beck Depression Inventory (BDI), PROMIS Anxiety and Depression Short Forms and others. Advantages of this approach include comparability of data derived with different measures and tolerance against missing values. The validity of the underlying models needs to be investigated in the future.

  11. Soil physical properties influencing the fitting parameters in Philip and Kostiakov infiltration models

    International Nuclear Information System (INIS)

    Mbagwu, J.S.C.

    1994-05-01

    Among the many models developed for monitoring the infiltration process those of Philip and Kostiakov have been studied in detail because of their simplicity and the ease of estimating their fitting parameters. The important soil physical factors influencing the fitting parameters in these infiltration models are reported in this study. The results of the study show that the single most important soil property affecting the fitting parameters in these models is the effective porosity. 36 refs, 2 figs, 5 tabs

  12. The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing.

    Directory of Open Access Journals (Sweden)

    Jaclyn K Mann

    2014-08-01

    Full Text Available Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model, generalizing our previous approach (Ising model that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = -0.74, p = 3.6×10-6 are strongly correlated, and this was further strengthened in the regularized Ising model (r = -0.83, p = 3.7×10-12. Performance of the Potts model (r = -0.73, p = 9.7×10-9 was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

  13. Calibrating the Medical Council of Canada's Qualifying Examination Part I using an integrated item response theory framework: a comparison of models and designs.

    Science.gov (United States)

    De Champlain, Andre F; Boulais, Andre-Philippe; Dallas, Andrew

    2016-01-01

    The aim of this research was to compare different methods of calibrating multiple choice question (MCQ) and clinical decision making (CDM) components for the Medical Council of Canada's Qualifying Examination Part I (MCCQEI) based on item response theory. Our data consisted of test results from 8,213 first time applicants to MCCQEI in spring and fall 2010 and 2011 test administrations. The data set contained several thousand multiple choice items and several hundred CDM cases. Four dichotomous calibrations were run using BILOG-MG 3.0. All 3 mixed item format (dichotomous MCQ responses and polytomous CDM case scores) calibrations were conducted using PARSCALE 4. The 2-PL model had identical numbers of items with chi-square values at or below a Type I error rate of 0.01 (83/3,499 or 0.02). In all 3 polytomous models, whether the MCQs were either anchored or concurrently run with the CDM cases, results suggest very poor fit. All IRT abilities estimated from dichotomous calibration designs correlated very highly with each other. IRT-based pass-fail rates were extremely similar, not only across calibration designs and methods, but also with regard to the actual reported decision to candidates. The largest difference noted in pass rates was 4.78%, which occurred between the mixed format concurrent 2-PL graded response model (pass rate= 80.43%) and the dichotomous anchored 1-PL calibrations (pass rate= 85.21%). Simpler calibration designs with dichotomized items should be implemented. The dichotomous calibrations provided better fit of the item response matrix than more complex, polytomous calibrations.

  14. Correcting Model Fit Criteria for Small Sample Latent Growth Models with Incomplete Data

    Science.gov (United States)

    McNeish, Daniel; Harring, Jeffrey R.

    2017-01-01

    To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data-model fit. However, previous studies have demonstrated poor…

  15. Supersymmetry with prejudice: Fitting the wrong model to LHC data

    Science.gov (United States)

    Allanach, B. C.; Dolan, Matthew J.

    2012-09-01

    We critically examine interpretations of hypothetical supersymmetric LHC signals, fitting to alternative wrong models of supersymmetry breaking. The signals we consider are some of the most constraining on the sparticle spectrum: invariant mass distributions with edges and endpoints from the golden decay chain q˜→qχ20(→l˜±l∓q)→χ10l+l-q. We assume a constrained minimal supersymmetric standard model (CMSSM) point to be the ‘correct’ one, but fit the signals instead with minimal gauge mediated supersymmetry breaking models (mGMSB) with a neutralino quasistable lightest supersymmetric particle, minimal anomaly mediation and large volume string compactification models. Minimal anomaly mediation and large volume scenario can be unambiguously discriminated against the CMSSM for the assumed signal and 1fb-1 of LHC data at s=14TeV. However, mGMSB would not be discriminated on the basis of the kinematic endpoints alone. The best-fit point spectra of mGMSB and CMSSM look remarkably similar, making experimental discrimination at the LHC based on the edges or Higgs properties difficult. However, using rate information for the golden chain should provide the additional separation required.

  16. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

    Science.gov (United States)

    Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

    2017-01-04

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

  17. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

    Science.gov (United States)

    Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

    2017-01-01

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

  18. The lz(p)* Person-Fit Statistic in an Unfolding Model Context

    NARCIS (Netherlands)

    Tendeiro, Jorge N.

    2017-01-01

    Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded

  19. Limited information estimation of the diffusion-based item response theory model for responses and response times.

    Science.gov (United States)

    Ranger, Jochen; Kuhn, Jörg-Tobias; Szardenings, Carsten

    2016-05-01

    Psychological tests are usually analysed with item response models. Recently, some alternative measurement models have been proposed that were derived from cognitive process models developed in experimental psychology. These models consider the responses but also the response times of the test takers. Two such models are the Q-diffusion model and the D-diffusion model. Both models can be calibrated with the diffIRT package of the R statistical environment via marginal maximum likelihood (MML) estimation. In this manuscript, an alternative approach to model calibration is proposed. The approach is based on weighted least squares estimation and parallels the standard estimation approach in structural equation modelling. Estimates are determined by minimizing the discrepancy between the observed and the implied covariance matrix. The estimator is simple to implement, consistent, and asymptotically normally distributed. Least squares estimation also provides a test of model fit by comparing the observed and implied covariance matrix. The estimator and the test of model fit are evaluated in a simulation study. Although parameter recovery is good, the estimator is less efficient than the MML estimator. © 2016 The British Psychological Society.

  20. Using item response theory to investigate the structure of anticipated affect: do self-reports about future affective reactions conform to typical or maximal models?

    OpenAIRE

    Zampetakis, Leonidas A.; Lerakis, Manolis; Kafetsios, Konstantinos; Moustakis, Vassilis

    2015-01-01

    In the present research we used item response theory (IRT) to examine whether effective predictions (anticipated affect) conforms to a typical (i.e., what people usually do) or a maximal behavior process (i.e., what people can do). The former, correspond to non-monotonic ideal point IRT models whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N=1624) was used. Participants were asked to report on anticipated positive and negative a...

  1. Potential application of thermography (IRT in animal production and for animal welfare. A case report of working dogs

    Directory of Open Access Journals (Sweden)

    Veronica Redaelli

    2014-06-01

    Full Text Available INTRODUCTION. The authors describe the thermography technique in animal production and in veterinary medicine applications. The thermographic technique lends itself to countless applications in biology, thanks to its characteristics of versatility, lack of invasiveness and high sensitivity. Probably the major limitation to most important aspects for its application in the animal lies in the ease of use and in its extreme sensitivity. Materials and methods. This review provides an overview of the possible applications of the technique of thermo visual inspection, but it is clear that every phenomenon connected to temperature variations can be identified with this technique. Then the operator has to identify the best experimental context to obtain as much information as possible, concerning the physiopathological problems considered. Furthermore, we reported an experimental study about the thermography (IRT as a noninvasive technique to assess the state of wellbeing in working dogs. RESULTS. The first results showed the relationship between superficial temperatures and scores obtained by the animal during the behavioral test. This result suggests an interesting application of infrared thermography (IRT to measure the state of wellbeing of animals in a noninvasive way.

  2. Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

    KAUST Repository

    Zhang, Saijuan; Krebs-Smith, Susan M.; Midthune, Douglas; Perez, Adriana; Buckman, Dennis W.; Kipnis, Victor; Freedman, Laurence S.; Dodd, Kevin W.; Carroll, Raymond J

    2011-01-01

    There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole

  3. Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

    KAUST Repository

    Zhang, Saijuan

    2011-01-06

    There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole

  4. Investigation of radial propagation of electrostatic fluctuations in the IR-T1 tokamak plasma edge

    Energy Technology Data Exchange (ETDEWEB)

    Shariatzadeh, R; Ghoranneviss, M; Salem, M K [Plasma Physics Research Center, Science and Research Branch, Islamic Azad University (IAU), PO Box 14665-678, Tehran (Iran, Islamic Republic of); Emami, M, E-mail: rezashariatzadeh@gmail.com [Laser and Optics Research School, NSTRI, AEOI, PO Box 14155-1339, Tehran (Iran, Islamic Republic of)

    2011-01-15

    The radial propagation of electrostatic fluctuation is considered extremely important for understanding cross-field anomalous transport. In this paper, two arrays of Langmuir probes are used to analyze electrostatic fluctuations in the edge of IR-T1 tokamak plasma in both the radial and the poloidal directions. The propagation characteristics of the floating potential fluctuations are analyzed by the two-point correlation technique. The wavenumber spectrum shows that there is a net radially outward propagation of turbulent fluctuations in the edge and scrape-off layer (SOL) regions. Hence, edge turbulence presumably originates from core fluctuations.

  5. Investigation of radial propagation of electrostatic fluctuations in the IR-T1 tokamak plasma edge

    International Nuclear Information System (INIS)

    Shariatzadeh, R; Ghoranneviss, M; Salem, M K; Emami, M

    2011-01-01

    The radial propagation of electrostatic fluctuation is considered extremely important for understanding cross-field anomalous transport. In this paper, two arrays of Langmuir probes are used to analyze electrostatic fluctuations in the edge of IR-T1 tokamak plasma in both the radial and the poloidal directions. The propagation characteristics of the floating potential fluctuations are analyzed by the two-point correlation technique. The wavenumber spectrum shows that there is a net radially outward propagation of turbulent fluctuations in the edge and scrape-off layer (SOL) regions. Hence, edge turbulence presumably originates from core fluctuations.

  6. Experimental study on infrared radiation temperature field of concrete under uniaxial compression

    Science.gov (United States)

    Lou, Quan; He, Xueqiu

    2018-05-01

    Infrared thermography, as a nondestructive, non-contact and real-time monitoring method, has great significance in assessing the stability of concrete structure and monitoring its failure. It is necessary to conduct in depth study on the mechanism and application of infrared radiation (IR) of concrete failure under loading. In this paper, the concrete specimens with size of 100 × 100 × 100 mm were adopted to carry out the uniaxial compressions for the IR tests. The distribution of IR temperatures (IRTs), surface topography of IRT field and the reconstructed IR images were studied. The results show that the IRT distribution follows the Gaussian distribution, and the R2 of Gaussian fitting changes along with the loading time. The abnormities of R2 and AE counts display the opposite variation trends. The surface topography of IRT field is similar to the hyperbolic paraboloid, which is related to the stress distribution in the sample. The R2 of hyperbolic paraboloid fitting presents an upward trend prior to the fracture which enables to change the IRT field significantly. This R2 has a sharp drop in response to this large destruction. The normalization images of IRT field, including the row and column normalization images, were proposed as auxiliary means to analyze the IRT field. The row and column normalization images respectively show the transverse and longitudinal distribution of the IRT field, and they have clear responses to the destruction occurring on the sample surface. In this paper, the new methods and quantitative index were proposed for the analysis of IRT field, which have some theoretical and instructive significance for the analysis of the characteristics of IRT field, as well as the monitoring of instability and failure for concrete structure.

  7. Nonlinear models for fitting growth curves of Nellore cows reared in the Amazon Biome

    Directory of Open Access Journals (Sweden)

    Kedma Nayra da Silva Marinho

    2013-09-01

    Full Text Available Growth curves of Nellore cows were estimated by comparing six nonlinear models: Brody, Logistic, two alternatives by Gompertz, Richards and Von Bertalanffy. The models were fitted to weight-age data, from birth to 750 days of age of 29,221 cows, born between 1976 and 2006 in the Brazilian states of Acre, Amapá, Amazonas, Pará, Rondônia, Roraima and Tocantins. The models were fitted by the Gauss-Newton method. The goodness of fit of the models was evaluated by using mean square error, adjusted coefficient of determination, prediction error and mean absolute error. Biological interpretation of parameters was accomplished by plotting estimated weights versus the observed weight means, instantaneous growth rate, absolute maturity rate, relative instantaneous growth rate, inflection point and magnitude of the parameters A (asymptotic weight and K (maturing rate. The Brody and Von Bertalanffy models fitted the weight-age data but the other models did not. The average weight (A and growth rate (K were: 384.6±1.63 kg and 0.0022±0.00002 (Brody and 313.40±0.70 kg and 0.0045±0.00002 (Von Bertalanffy. The Brody model provides better goodness of fit than the Von Bertalanffy model.

  8. Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

    International Nuclear Information System (INIS)

    Liang, Zhong Wei; Wang, Yi Jun; Ye, Bang Yan; Brauwer, Richard Kars

    2012-01-01

    In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process

  9. Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Zhong Wei; Wang, Yi Jun [Guangzhou Univ., Guangzhou (China); Ye, Bang Yan [South China Univ. of Technology, Guangzhou (China); Brauwer, Richard Kars [Indian Institute of Technology, Kanpur (India)

    2012-10-15

    In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process.

  10. Criteria for eliminating items of a Test of Figural Analogies

    Directory of Open Access Journals (Sweden)

    Diego Blum

    2013-12-01

    Full Text Available This paper describes the steps taken to eliminate two of the items in a Test of Figural Analogies (TFA. The main guidelines of psychometric analysis concerning Classical Test Theory (CTT and Item Response Theory (IRT are explained. The item elimination process was based on both the study of the CTT difficulty and discrimination index, and the unidimensionality analysis. The a, b, and c parameters of the Three Parameter Logistic Model of IRT were also considered for this purpose, as well as the assessment of each item fitting this model. The unfavourable characteristics of a group of TFA items are detailed, and decisions leading to their possible elimination are discussed.

  11. Efficient Constrained Local Model Fitting for Non-Rigid Face Alignment.

    Science.gov (United States)

    Lucey, Simon; Wang, Yang; Cox, Mark; Sridharan, Sridha; Cohn, Jeffery F

    2009-11-01

    Active appearance models (AAMs) have demonstrated great utility when being employed for non-rigid face alignment/tracking. The "simultaneous" algorithm for fitting an AAM achieves good non-rigid face registration performance, but has poor real time performance (2-3 fps). The "project-out" algorithm for fitting an AAM achieves faster than real time performance (> 200 fps) but suffers from poor generic alignment performance. In this paper we introduce an extension to a discriminative method for non-rigid face registration/tracking referred to as a constrained local model (CLM). Our proposed method is able to achieve superior performance to the "simultaneous" AAM algorithm along with real time fitting speeds (35 fps). We improve upon the canonical CLM formulation, to gain this performance, in a number of ways by employing: (i) linear SVMs as patch-experts, (ii) a simplified optimization criteria, and (iii) a composite rather than additive warp update step. Most notably, our simplified optimization criteria for fitting the CLM divides the problem of finding a single complex registration/warp displacement into that of finding N simple warp displacements. From these N simple warp displacements, a single complex warp displacement is estimated using a weighted least-squares constraint. Another major advantage of this simplified optimization lends from its ability to be parallelized, a step which we also theoretically explore in this paper. We refer to our approach for fitting the CLM as the "exhaustive local search" (ELS) algorithm. Experiments were conducted on the CMU Multi-PIE database.

  12. Multi-binding site model-based curve-fitting program for the computation of RIA data

    International Nuclear Information System (INIS)

    Malan, P.G.; Ekins, R.P.; Cox, M.G.; Long, E.M.R.

    1977-01-01

    In this paper, a comparison will be made of model-based and empirical curve-fitting procedures. The implementation of a multiple binding-site curve-fitting model which will successfully fit a wide range of assay data, and which can be run on a mini-computer is described. The latter sophisticated model also provides estimates of binding site concentrations and the values of the respective equilibrium constants present: the latter have been used for refining assay conditions using computer optimisation techniques. (orig./AJ) [de

  13. Effectiveness of Item Response Theory (IRT) Proficiency Estimation Methods under Adaptive Multistage Testing. Research Report. ETS RR-15-11

    Science.gov (United States)

    Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry

    2015-01-01

    The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…

  14. Using the Flipchem Photochemistry Model When Fitting Incoherent Scatter Radar Data

    Science.gov (United States)

    Reimer, A. S.; Varney, R. H.

    2017-12-01

    The North face Resolute Bay Incoherent Scatter Radar (RISR-N) routinely images the dynamics of the polar ionosphere, providing measurements of the plasma density, electron temperature, ion temperature, and line of sight velocity with seconds to minutes time resolution. RISR-N does not directly measure ionospheric parameters, but backscattered signals, recording them as voltage samples. Using signal processing techniques, radar autocorrelation functions (ACF) are estimated from the voltage samples. A model of the signal ACF is then fitted to the ACF using non-linear least-squares techniques to obtain the best-fit ionospheric parameters. The signal model, and therefore the fitted parameters, depend on the ionospheric ion composition that is used [e.g. Zettergren et. al. (2010), Zou et. al. (2017)].The software used to process RISR-N ACF data includes the "flipchem" model, which is an ion photochemistry model developed by Richards [2011] that was adapted from the Field LineInterhemispheric Plasma (FLIP) model. Flipchem requires neutral densities, neutral temperatures, electron density, ion temperature, electron temperature, solar zenith angle, and F10.7 as inputs to compute ion densities, which are input to the signal model. A description of how the flipchem model is used in RISR-N fitting software will be presented. Additionally, a statistical comparison of the fitted electron density, ion temperature, electron temperature, and velocity obtained using a flipchem ionosphere, a pure O+ ionosphere, and a Chapman O+ ionosphere will be presented. The comparison covers nearly two years of RISR-N data (April 2015 - December 2016). Richards, P. G. (2011), Reexamination of ionospheric photochemistry, J. Geophys. Res., 116, A08307, doi:10.1029/2011JA016613.Zettergren, M., Semeter, J., Burnett, B., Oliver, W., Heinselman, C., Blelly, P.-L., and Diaz, M.: Dynamic variability in F-region ionospheric composition at auroral arc boundaries, Ann. Geophys., 28, 651-664, https

  15. Fitting Latent Cluster Models for Networks with latentnet

    Directory of Open Access Journals (Sweden)

    Pavel N. Krivitsky

    2007-12-01

    Full Text Available latentnet is a package to fit and evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002 suggested an approach to modeling networks based on positing the existence of an latent space of characteristics of the actors. Relationships form as a function of distances between these characteristics as well as functions of observed dyadic level covariates. In latentnet social distances are represented in a Euclidean space. It also includes a variant of the extension of the latent position model to allow for clustering of the positions developed in Handcock, Raftery, and Tantrum (2007.The package implements Bayesian inference for the models based on an Markov chain Monte Carlo algorithm. It can also compute maximum likelihood estimates for the latent position model and a two-stage maximum likelihood method for the latent position cluster model. For latent position cluster models, the package provides a Bayesian way of assessing how many groups there are, and thus whether or not there is any clustering (since if the preferred number of groups is 1, there is little evidence for clustering. It also estimates which cluster each actor belongs to. These estimates are probabilistic, and provide the probability of each actor belonging to each cluster. It computes four types of point estimates for the coefficients and positions: maximum likelihood estimate, posterior mean, posterior mode and the estimator which minimizes Kullback-Leibler divergence from the posterior. You can assess the goodness-of-fit of the model via posterior predictive checks. It has a function to simulate networks from a latent position or latent position cluster model.

  16. Twitter classification model: the ABC of two million fitness tweets.

    Science.gov (United States)

    Vickey, Theodore A; Ginis, Kathleen Martin; Dabrowski, Maciej

    2013-09-01

    The purpose of this project was to design and test data collection and management tools that can be used to study the use of mobile fitness applications and social networking within the context of physical activity. This project was conducted over a 6-month period and involved collecting publically shared Twitter data from five mobile fitness apps (Nike+, RunKeeper, MyFitnessPal, Endomondo, and dailymile). During that time, over 2.8 million tweets were collected, processed, and categorized using an online tweet collection application and a customized JavaScript. Using the grounded theory, a classification model was developed to categorize and understand the types of information being shared by application users. Our data show that by tracking mobile fitness app hashtags, a wealth of information can be gathered to include but not limited to daily use patterns, exercise frequency, location-based workouts, and overall workout sentiment.

  17. Brief communication: human cranial variation fits iterative founder effect model with African origin.

    Science.gov (United States)

    von Cramon-Taubadel, Noreen; Lycett, Stephen J

    2008-05-01

    Recent studies comparing craniometric and neutral genetic affinity matrices have concluded that, on average, human cranial variation fits a model of neutral expectation. While human craniometric and genetic data fit a model of isolation by geographic distance, it is not yet clear whether this is due to geographically mediated gene flow or human dispersal events. Recently, human genetic data have been shown to fit an iterative founder effect model of dispersal with an African origin, in line with the out-of-Africa replacement model for modern human origins, and Manica et al. (Nature 448 (2007) 346-349) have demonstrated that human craniometric data also fit this model. However, in contrast with the neutral model of cranial evolution suggested by previous studies, Manica et al. (2007) made the a priori assumption that cranial form has been subject to climatically driven natural selection and therefore correct for climate prior to conducting their analyses. Here we employ a modified theoretical and methodological approach to test whether human cranial variability fits the iterative founder effect model. In contrast with Manica et al. (2007) we employ size-adjusted craniometric variables, since climatic factors such as temperature have been shown to correlate with aspects of cranial size. Despite these differences, we obtain similar results to those of Manica et al. (2007), with up to 26% of global within-population craniometric variation being explained by geographic distance from sub-Saharan Africa. Comparative analyses using non-African origins do not yield significant results. The implications of these results are discussed in the light of the modern human origins debate. (c) 2007 Wiley-Liss, Inc.

  18. Calibrating the Medical Council of Canada’s Qualifying Examination Part I using an integrated item response theory framework: a comparison of models and designs

    Directory of Open Access Journals (Sweden)

    Andre F. De Champlain

    2016-01-01

    Full Text Available Purpose: The aim of this research was to compare different methods of calibrating multiple choice question (MCQ and clinical decision making (CDM components for the Medical Council of Canada’s Qualifying Examination Part I (MCCQEI based on item response theory. Methods: Our data consisted of test results from 8,213 first time applicants to MCCQEI in spring and fall 2010 and 2011 test administrations. The data set contained several thousand multiple choice items and several hundred CDM cases. Four dichotomous calibrations were run using BILOG-MG 3.0. All 3 mixed item format (dichotomous MCQ responses and polytomous CDM case scores calibrations were conducted using PARSCALE 4. Results: The 2-PL model had identical numbers of items with chi-square values at or below a Type I error rate of 0.01 (83/3,499 or 0.02. In all 3 polytomous models, whether the MCQs were either anchored or concurrently run with the CDM cases, results suggest very poor fit. All IRT abilities estimated from dichotomous calibration designs correlated very highly with each other. IRT-based pass-fail rates were extremely similar, not only across calibration designs and methods, but also with regard to the actual reported decision to candidates. The largest difference noted in pass rates was 4.78%, which occurred between the mixed format concurrent 2-PL graded response model (pass rate= 80.43% and the dichotomous anchored 1-PL calibrations (pass rate= 85.21%. Conclusion: Simpler calibration designs with dichotomized items should be implemented. The dichotomous calibrations provided better fit of the item response matrix than more complex, polytomous calibrations.

  19. Rapid world modeling: Fitting range data to geometric primitives

    International Nuclear Information System (INIS)

    Feddema, J.; Little, C.

    1996-01-01

    For the past seven years, Sandia National Laboratories has been active in the development of robotic systems to help remediate DOE's waste sites and decommissioned facilities. Some of these facilities have high levels of radioactivity which prevent manual clean-up. Tele-operated and autonomous robotic systems have been envisioned as the only suitable means of removing the radioactive elements. World modeling is defined as the process of creating a numerical geometric model of a real world environment or workspace. This model is often used in robotics to plan robot motions which perform a task while avoiding obstacles. In many applications where the world model does not exist ahead of time, structured lighting, laser range finders, and even acoustical sensors have been used to create three dimensional maps of the environment. These maps consist of thousands of range points which are difficult to handle and interpret. This paper presents a least squares technique for fitting range data to planar and quadric surfaces, including cylinders and ellipsoids. Once fit to these primitive surfaces, the amount of data associated with a surface is greatly reduced up to three orders of magnitude, thus allowing for more rapid handling and analysis of world data

  20. A scale purification procedure for evaluation of differential item functioning

    NARCIS (Netherlands)

    Khalid, Muhammad Naveed; Glas, Cornelis A.W.

    2014-01-01

    Item bias or differential item functioning (DIF) has an important impact on the fairness of psychological and educational testing. In this paper, DIF is seen as a lack of fit to an item response (IRT) model. Inferences about the presence and importance of DIF require a process of so-called test

  1. Kernel-density estimation and approximate Bayesian computation for flexible epidemiological model fitting in Python.

    Science.gov (United States)

    Irvine, Michael A; Hollingsworth, T Déirdre

    2018-05-26

    Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  2. Model-independent partial wave analysis using a massively-parallel fitting framework

    Science.gov (United States)

    Sun, L.; Aoude, R.; dos Reis, A. C.; Sokoloff, M.

    2017-10-01

    The functionality of GooFit, a GPU-friendly framework for doing maximum-likelihood fits, has been extended to extract model-independent {\\mathscr{S}}-wave amplitudes in three-body decays such as D + → h + h + h -. A full amplitude analysis is done where the magnitudes and phases of the {\\mathscr{S}}-wave amplitudes are anchored at a finite number of m 2(h + h -) control points, and a cubic spline is used to interpolate between these points. The amplitudes for {\\mathscr{P}}-wave and {\\mathscr{D}}-wave intermediate states are modeled as spin-dependent Breit-Wigner resonances. GooFit uses the Thrust library, with a CUDA backend for NVIDIA GPUs and an OpenMP backend for threads with conventional CPUs. Performance on a variety of platforms is compared. Executing on systems with GPUs is typically a few hundred times faster than executing the same algorithm on a single CPU.

  3. The issue of statistical power for overall model fit in evaluating structural equation models

    Directory of Open Access Journals (Sweden)

    Richard HERMIDA

    2015-06-01

    Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.

  4. Fitting and comparing competing models of the species abundance distribution: assessment and prospect

    Directory of Open Access Journals (Sweden)

    Thomas J Matthews

    2014-06-01

    Full Text Available A species abundance distribution (SAD characterises patterns in the commonness and rarity of all species within an ecological community. As such, the SAD provides the theoretical foundation for a number of other biogeographical and macroecological patterns, such as the species–area relationship, as well as being an interesting pattern in its own right. While there has been resurgence in the study of SADs in the last decade, less focus has been placed on methodology in SAD research, and few attempts have been made to synthesise the vast array of methods which have been employed in SAD model evaluation. As such, our review has two aims. First, we provide a general overview of SADs, including descriptions of the commonly used distributions, plotting methods and issues with evaluating SAD models. Second, we review a number of recent advances in SAD model fitting and comparison. We conclude by providing a list of recommendations for fitting and evaluating SAD models. We argue that it is time for SAD studies to move away from many of the traditional methods available for fitting and evaluating models, such as sole reliance on the visual examination of plots, and embrace statistically rigorous techniques. In particular, we recommend the use of both goodness-of-fit tests and model-comparison analyses because each provides unique information which one can use to draw inferences.

  5. Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure.

    Science.gov (United States)

    Yung, Yiu-Fai; Browne, Michael W; Zhang, Wei

    2015-02-01

    This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple-group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy-to-use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large. © 2014 The British Psychological Society.

  6. A goodness-of-fit test for occupancy models with correlated within-season revisits

    Science.gov (United States)

    Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.

    2016-01-01

    Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and

  7. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

    OpenAIRE

    Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

    2017-01-01

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

  8. Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

    Science.gov (United States)

    Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

    2014-05-20

    Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

  9. Modeling Math Growth Trajectory--An Application of Conventional Growth Curve Model and Growth Mixture Model to ECLS K-5 Data

    Science.gov (United States)

    Lu, Yi

    2016-01-01

    To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…

  10. Efficient parallel implementation of active appearance model fitting algorithm on GPU.

    Science.gov (United States)

    Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

    2014-01-01

    The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

  11. ARA and ARI imperfect repair models: Estimation, goodness-of-fit and reliability prediction

    International Nuclear Information System (INIS)

    Toledo, Maria Luíza Guerra de; Freitas, Marta A.; Colosimo, Enrico A.; Gilardoni, Gustavo L.

    2015-01-01

    An appropriate maintenance policy is essential to reduce expenses and risks related to equipment failures. A fundamental aspect to be considered when specifying such policies is to be able to predict the reliability of the systems under study, based on a well fitted model. In this paper, the classes of models Arithmetic Reduction of Age and Arithmetic Reduction of Intensity are explored. Likelihood functions for such models are derived, and a graphical method is proposed for model selection. A real data set involving failures in trucks used by a Brazilian mining is analyzed considering models with different memories. Parameters, namely, shape and scale for Power Law Process, and the efficiency of repair were estimated for the best fitted model. Estimation of model parameters allowed us to derive reliability estimators to predict the behavior of the failure process. These results are a valuable information for the mining company and can be used to support decision making regarding preventive maintenance policy. - Highlights: • Likelihood functions for imperfect repair models are derived. • A goodness-of-fit technique is proposed as a tool for model selection. • Failures in trucks owned by a Brazilian mining are modeled. • Estimation allowed deriving reliability predictors to forecast the future failure process of the trucks

  12. Person-fit to the Five Factor Model of personality

    Czech Academy of Sciences Publication Activity Database

    Allik, J.; Realo, A.; Mõttus, R.; Borkenau, P.; Kuppens, P.; Hřebíčková, Martina

    2012-01-01

    Roč. 71, č. 1 (2012), s. 35-45 ISSN 1421-0185 R&D Projects: GA ČR GAP407/10/2394 Institutional research plan: CEZ:AV0Z70250504 Keywords : Five Factor Model * cross - cultural comparison * person-fit Subject RIV: AN - Psychology Impact factor: 0.638, year: 2012

  13. Study on fitness functions of genetic algorithm for dynamically correcting nuclide atmospheric diffusion model

    International Nuclear Information System (INIS)

    Ji Zhilong; Ma Yuanwei; Wang Dezhong

    2014-01-01

    Background: In radioactive nuclides atmospheric diffusion models, the empirical dispersion coefficients were deduced under certain experiment conditions, whose difference with nuclear accident conditions is a source of deviation. A better estimation of the radioactive nuclide's actual dispersion process could be done by correcting dispersion coefficients with observation data, and Genetic Algorithm (GA) is an appropriate method for this correction procedure. Purpose: This study is to analyze the fitness functions' influence on the correction procedure and the forecast ability of diffusion model. Methods: GA, coupled with Lagrange dispersion model, was used in a numerical simulation to compare 4 fitness functions' impact on the correction result. Results: In the numerical simulation, the fitness function with observation deviation taken into consideration stands out when significant deviation exists in the observed data. After performing the correction procedure on the Kincaid experiment data, a significant boost was observed in the diffusion model's forecast ability. Conclusion: As the result shows, in order to improve dispersion models' forecast ability using GA, observation data should be given different weight in the fitness function corresponding to their error. (authors)

  14. Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice

    Science.gov (United States)

    Farmer, Jim

    2010-01-01

    In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days.…

  15. Development and assessment of the Quality of Life in Childhood Epilepsy Questionnaire (QOLCE-16).

    Science.gov (United States)

    Goodwin, Shane W; Ferro, Mark A; Speechley, Kathy N

    2018-03-01

    The aim of this study was to develop and validate a brief version of the Quality of Life in Childhood Epilepsy Questionnaire (QOLCE). A secondary aim was to compare the results described in previously published studies using the QOLCE-55 with those obtained using the new brief version. Data come from 373 children involved in the Health-related Quality of Life in Children with Epilepsy Study, a multicenter prospective cohort study. Item response theory (IRT) methods were used to assess dimensionality and item properties and to guide the selection of items. Replication of results using the brief measure was conducted with multiple regression, multinomial regression, and latent mixture modeling techniques. IRT methods identified a bi-factor graded response model that best fits the data. Thirty-nine items were removed, resulting in a 16-item QOLCE (QOLCE-16) with an equal number of items in all 4 domains of functioning (Cognitive, Emotional, Social, and Physical). Model fit was excellent: Comparative Fit Index = 0.99; Tucker-Lewis Index = 0.99; root mean square error of approximation = 0.052 (90% confidence interval [CI] 0.041-0.064); weighted root mean square = 0.76. Results that were reported previously using the QOLCE-55 and QOLCE-76 were comparable to those generated using the QOLCE-16. The QOLCE-16 is a multidimensional measure of health-related quality of life (HRQoL) with good psychometric properties and a short-estimated completion time. It is notable that the items were calibrated using multidimensional IRT methods to create a measure that conforms to conventional definitions of HRQoL. The QOLCE-16 is an appropriate measure for both clinicians and researchers wanting to record HRQoL information in children with epilepsy. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

  16. Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.

    Science.gov (United States)

    Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria

    2017-10-01

    Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

  17. Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

    Directory of Open Access Journals (Sweden)

    Jinwei Wang

    2014-01-01

    Full Text Available The active appearance model (AAM is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA on the Nvidia’s GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

  18. Local and omnibus goodness-of-fit tests in classical measurement error models

    KAUST Repository

    Ma, Yanyuan

    2010-09-14

    We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.

  19. Calibration and Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients with Chronic Pain.

    Science.gov (United States)

    Crins, Martine H P; Roorda, Leo D; Smits, Niels; de Vet, Henrica C W; Westhovens, Rene; Cella, David; Cook, Karon F; Revicki, Dennis; van Leeuwen, Jaap; Boers, Maarten; Dekker, Joost; Terwee, Caroline B

    2015-01-01

    The Dutch-Flemish PROMIS Group translated the adult PROMIS Pain Interference item bank into Dutch-Flemish. The aims of the current study were to calibrate the parameters of these items using an item response theory (IRT) model, to evaluate the cross-cultural validity of the Dutch-Flemish translations compared to the original English items, and to evaluate their reliability and construct validity. The 40 items in the bank were completed by 1085 Dutch chronic pain patients. Before calibrating the items, IRT model assumptions were evaluated using confirmatory factor analysis (CFA). Items were calibrated using the graded response model (GRM), an IRT model appropriate for items with more than two response options. To evaluate cross-cultural validity, differential item functioning (DIF) for language (Dutch vs. English) was examined. Reliability was evaluated based on standard errors and Cronbach's alpha. To evaluate construct validity correlations with scores on legacy instruments (e.g., the Disabilities of the Arm, Shoulder and Hand Questionnaire) were calculated. Unidimensionality of the Dutch-Flemish PROMIS Pain Interference item bank was supported by CFA tests of model fit (CFI = 0.986, TLI = 0.986). Furthermore, the data fit the GRM and showed good coverage across the pain interference continuum (threshold-parameters range: -3.04 to 3.44). The Dutch-Flemish PROMIS Pain Interference item bank has good cross-cultural validity (only two out of 40 items showing DIF), good reliability (Cronbach's alpha = 0.98), and good construct validity (Pearson correlations between 0.62 and 0.75). A computer adaptive test (CAT) and Dutch-Flemish PROMIS short forms of the Dutch-Flemish PROMIS Pain Interference item bank can now be developed.

  20. Calibration and Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients with Chronic Pain.

    Directory of Open Access Journals (Sweden)

    Martine H P Crins

    Full Text Available The Dutch-Flemish PROMIS Group translated the adult PROMIS Pain Interference item bank into Dutch-Flemish. The aims of the current study were to calibrate the parameters of these items using an item response theory (IRT model, to evaluate the cross-cultural validity of the Dutch-Flemish translations compared to the original English items, and to evaluate their reliability and construct validity. The 40 items in the bank were completed by 1085 Dutch chronic pain patients. Before calibrating the items, IRT model assumptions were evaluated using confirmatory factor analysis (CFA. Items were calibrated using the graded response model (GRM, an IRT model appropriate for items with more than two response options. To evaluate cross-cultural validity, differential item functioning (DIF for language (Dutch vs. English was examined. Reliability was evaluated based on standard errors and Cronbach's alpha. To evaluate construct validity correlations with scores on legacy instruments (e.g., the Disabilities of the Arm, Shoulder and Hand Questionnaire were calculated. Unidimensionality of the Dutch-Flemish PROMIS Pain Interference item bank was supported by CFA tests of model fit (CFI = 0.986, TLI = 0.986. Furthermore, the data fit the GRM and showed good coverage across the pain interference continuum (threshold-parameters range: -3.04 to 3.44. The Dutch-Flemish PROMIS Pain Interference item bank has good cross-cultural validity (only two out of 40 items showing DIF, good reliability (Cronbach's alpha = 0.98, and good construct validity (Pearson correlations between 0.62 and 0.75. A computer adaptive test (CAT and Dutch-Flemish PROMIS short forms of the Dutch-Flemish PROMIS Pain Interference item bank can now be developed.

  1. Universal Rate Model Selector: A Method to Quickly Find the Best-Fit Kinetic Rate Model for an Experimental Rate Profile

    Science.gov (United States)

    2017-08-01

    k2 – k1) 3.3 Universal Kinetic Rate Platform Development Kinetic rate models range from pure chemical reactions to mass transfer...14 8. The rate model that best fits the experimental data is a first-order or homogeneous catalytic reaction ...Avrami (7), and intraparticle diffusion (6) rate equations to name a few. A single fitting algorithm (kinetic rate model ) for a reaction does not

  2. The global electroweak Standard Model fit after the Higgs discovery

    CERN Document Server

    Baak, Max

    2013-01-01

    We present an update of the global Standard Model (SM) fit to electroweak precision data under the assumption that the new particle discovered at the LHC is the SM Higgs boson. In this scenario all parameters entering the calculations of electroweak precision observalbes are known, allowing, for the first time, to over-constrain the SM at the electroweak scale and assert its validity. Within the SM the W boson mass and the effective weak mixing angle can be accurately predicted from the global fit. The results are compatible with, and exceed in precision, the direct measurements. An updated determination of the S, T and U parameters, which parametrize the oblique vacuum corrections, is given. The obtained values show good consistency with the SM expectation and no direct signs of new physics are seen. We conclude with an outlook to the global electroweak fit for a future e+e- collider.

  3. An Item Response Theory–Based, Computerized Adaptive Testing Version of the MacArthur–Bates Communicative Development Inventory: Words & Sentences (CDI:WS)

    DEFF Research Database (Denmark)

    Makransky, Guido; Dale, Philip S.; Havmose, Philip

    2016-01-01

    precision. Method: Parent-reported vocabulary for the American CDI:WS norming sample consisting 1461 children between the ages of 16 and 30 months was used to investigate the fit of the items to the 2 parameter logistic (2-PL) IRT model, and to simulate CDI-CAT versions with 400, 200, 100, 50, 25, 10 and 5...

  4. Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models

    Science.gov (United States)

    Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning

    2012-01-01

    The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…

  5. Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

    Science.gov (United States)

    DeCarlo, Lawrence T

    2003-02-01

    The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

  6. Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

    Science.gov (United States)

    Leventhal, Brian C.; Stone, Clement A.

    2018-01-01

    Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

  7. Developing an African youth psychosocial assessment: an application of item response theory.

    Science.gov (United States)

    Betancourt, Theresa S; Yang, Frances; Bolton, Paul; Normand, Sharon-Lise

    2014-06-01

    This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. Copyright © 2014 John Wiley & Sons, Ltd.

  8. Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with Escherichia coli

    Science.gov (United States)

    Lenski, Richard E.; Wiser, Michael J.; Ribeck, Noah; Blount, Zachary D.; Nahum, Joshua R.; Morris, J. Jeffrey; Zaman, Luis; Turner, Caroline B.; Wade, Brian D.; Maddamsetti, Rohan; Burmeister, Alita R.; Baird, Elizabeth J.; Bundy, Jay; Grant, Nkrumah A.; Card, Kyle J.; Rowles, Maia; Weatherspoon, Kiyana; Papoulis, Spiridon E.; Sullivan, Rachel; Clark, Colleen; Mulka, Joseph S.; Hajela, Neerja

    2015-01-01

    Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving population's mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50 000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10 000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely—or at least for a long time—even in a constant environment. PMID:26674951

  9. A flexible, interactive software tool for fitting the parameters of neuronal models.

    Science.gov (United States)

    Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

    2014-01-01

    The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.

  10. A flexible, interactive software tool for fitting the parameters of neuronal models

    Directory of Open Access Journals (Sweden)

    Péter eFriedrich

    2014-07-01

    Full Text Available The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problem of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting

  11. Analysing model fit of psychometric process models: An overview, a new test and an application to the diffusion model.

    Science.gov (United States)

    Ranger, Jochen; Kuhn, Jörg-Tobias; Szardenings, Carsten

    2017-05-01

    Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey (Econometrica, 53, 1985, 1047) and Tauchen (J. Econometrics, 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica, 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q-diffusion model and the D-diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M 2 test (Molenaar et al., J. Stat. Softw., 66, 2015, 1), the moment test (Ranger et al., Br. J. Math. Stat. Psychol., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. , 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions. © 2017 The British Psychological Society.

  12. Use of a Scale Model in the Design of Modifications to the NASA Glenn Icing Research Tunnel

    Science.gov (United States)

    Canacci, Victor A.; Gonsalez, Jose C.; Spera, David A.; Burke, Thomas (Technical Monitor)

    2001-01-01

    Major modifications were made in 1999 to the 6- by 9-Foot (1.8- by 2.7-m) Icing Research tunnel (IRT) at the NASA Glenn Research Center, including replacement of its heat exchanger and associated ducts and turning vanes, and the addition of fan outlet guide vanes (OGV's). A one-tenth scale model of the IRT (designated as the SMIRT) was constructed with and without these modifications and tested to increase confidence in obtaining expected improvements in flow quality around the tunnel loop. The SMIRT is itself an aerodynamic test facility whose flow patterns without modifications have been shown to be accurate, scaled representations of those measured in the IRT prior to the 1999 upgrade program. In addition, tests in the SMIRT equipped with simulated OGV's indicated that these devices in the IRT might reduce flow distortions immediately downstream of the fan by two thirds. Flow quality parameters measured in the SMIRT were projected to the full-size modified IRT, and quantitative estimates of improvements in flow quality were given prior to construction. In this paper, the results of extensive flow quality studies conducted in the SMIRT are documented. Samples of these are then compared with equivalent measurements made in the full-scale IRT, both before and after its configuration was upgraded. Airspeed, turbulence intensity, and flow angularity distributions are presented for cross sections downstream of the drive fan, both upstream and downstream of the replacement flat heat exchanger, in the stilling chamber, in the test section, and in the wakes of the new comer turning vanes with their unique expanding and contracting designs. Lessons learned from these scale-model studies are discussed.

  13. The universal Higgs fit

    DEFF Research Database (Denmark)

    Giardino, P. P.; Kannike, K.; Masina, I.

    2014-01-01

    We perform a state-of-the-art global fit to all Higgs data. We synthesise them into a 'universal' form, which allows to easily test any desired model. We apply the proposed methodology to extract from data the Higgs branching ratios, production cross sections, couplings and to analyse composite...... Higgs models, models with extra Higgs doublets, supersymmetry, extra particles in the loops, anomalous top couplings, and invisible Higgs decays into Dark Matter. Best fit regions lie around the Standard Model predictions and are well approximated by our 'universal' fit. Latest data exclude the dilaton...... as an alternative to the Higgs, and disfavour fits with negative Yukawa couplings. We derive for the first time the SM Higgs boson mass from the measured rates, rather than from the peak positions, obtaining M-h = 124.4 +/- 1.6 GeV....

  14. Kinetic modeling and fitting software for interconnected reaction schemes: VisKin.

    Science.gov (United States)

    Zhang, Xuan; Andrews, Jared N; Pedersen, Steen E

    2007-02-15

    Reaction kinetics for complex, highly interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. To determine rate constants from experimental data, fitting algorithms that adjust rate constants to fit the model to imported data were implemented using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno methods. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs.

  15. Feature extraction through least squares fit to a simple model

    International Nuclear Information System (INIS)

    Demuth, H.B.

    1976-01-01

    The Oak Ridge National Laboratory (ORNL) presented the Los Alamos Scientific Laboratory (LASL) with 18 radiographs of fuel rod test bundles. The problem is to estimate the thickness of the gap between some cylindrical rods and a flat wall surface. The edges of the gaps are poorly defined due to finite source size, x-ray scatter, parallax, film grain noise, and other degrading effects. The radiographs were scanned and the scan-line data were averaged to reduce noise and to convert the problem to one dimension. A model of the ideal gap, convolved with an appropriate point-spread function, was fit to the averaged data with a least squares program; and the gap width was determined from the final fitted-model parameters. The least squares routine did converge and the gaps obtained are of reasonable size. The method is remarkably insensitive to noise. This report describes the problem, the techniques used to solve it, and the results and conclusions. Suggestions for future work are also given

  16. Fitness cost

    DEFF Research Database (Denmark)

    Nielsen, Karen L.; Pedersen, Thomas M.; Udekwu, Klas I.

    2012-01-01

    phage types, predominantly only penicillin resistant. We investigated whether isolates of this epidemic were associated with a fitness cost, and we employed a mathematical model to ask whether these fitness costs could have led to the observed reduction in frequency. Bacteraemia isolates of S. aureus...... from Denmark have been stored since 1957. We chose 40 S. aureus isolates belonging to phage complex 83A, clonal complex 8 based on spa type, ranging in time of isolation from 1957 to 1980 and with varyous antibiograms, including both methicillin-resistant and -susceptible isolates. The relative fitness...... of each isolate was determined in a growth competition assay with a reference isolate. Significant fitness costs of 215 were determined for the MRSA isolates studied. There was a significant negative correlation between number of antibiotic resistances and relative fitness. Multiple regression analysis...

  17. GOODNESS-OF-FIT TEST FOR THE ACCELERATED FAILURE TIME MODEL BASED ON MARTINGALE RESIDUALS

    Czech Academy of Sciences Publication Activity Database

    Novák, Petr

    2013-01-01

    Roč. 49, č. 1 (2013), s. 40-59 ISSN 0023-5954 R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:GA MŠk(CZ) SVV 261315/2011 Keywords : accelerated failure time model * survival analysis * goodness-of-fit Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/SI/novak-goodness-of-fit test for the aft model based on martingale residuals.pdf

  18. Improving ability measurement in surveys by following the principles of IRT: The Wordsum vocabulary test in the General Social Survey.

    Science.gov (United States)

    Cor, M Ken; Haertel, Edward; Krosnick, Jon A; Malhotra, Neil

    2012-09-01

    Survey researchers often administer batteries of questions to measure respondents' abilities, but these batteries are not always designed in keeping with the principles of optimal test construction. This paper illustrates one instance in which following these principles can improve a measurement tool used widely in the social and behavioral sciences: the GSS's vocabulary test called "Wordsum". This ten-item test is composed of very difficult items and very easy items, and item response theory (IRT) suggests that the omission of moderately difficult items is likely to have handicapped Wordsum's effectiveness. Analyses of data from national samples of thousands of American adults show that after adding four moderately difficult items to create a 14-item battery, "Wordsumplus" (1) outperformed the original battery in terms of quality indicators suggested by classical test theory; (2) reduced the standard error of IRT ability estimates in the middle of the latent ability dimension; and (3) exhibited higher concurrent validity. These findings show how to improve Wordsum and suggest that analysts should use a score based on all 14 items instead of using the summary score provided by the GSS, which is based on only the original 10 items. These results also show more generally how surveys measuring abilities (and other constructs) can benefit from careful application of insights from the contemporary educational testing literature. Copyright © 2012 Elsevier Inc. All rights reserved.

  19. Assessing model fit in latent class analysis when asymptotics do not hold

    NARCIS (Netherlands)

    van Kollenburg, Geert H.; Mulder, Joris; Vermunt, Jeroen K.

    2015-01-01

    The application of latent class (LC) analysis involves evaluating the LC model using goodness-of-fit statistics. To assess the misfit of a specified model, say with the Pearson chi-squared statistic, a p-value can be obtained using an asymptotic reference distribution. However, asymptotic p-values

  20. Item response theory analyses of the Delis-Kaplan Executive Function System card sorting subtest.

    Science.gov (United States)

    Spencer, Mercedes; Cho, Sun-Joo; Cutting, Laurie E

    2018-02-02

    In the current study, we examined the dimensionality of the 16-item Card Sorting subtest of the Delis-Kaplan Executive Functioning System assessment in a sample of 264 native English-speaking children between the ages of 9 and 15 years. We also tested for measurement invariance for these items across age and gender groups using item response theory (IRT). Results of the exploratory factor analysis indicated that a two-factor model that distinguished between verbal and perceptual items provided the best fit to the data. Although the items demonstrated measurement invariance across age groups, measurement invariance was violated for gender groups, with two items demonstrating differential item functioning for males and females. Multigroup analysis using all 16 items indicated that the items were more effective for individuals whose IRT scale scores were relatively high. A single-group explanatory IRT model using 14 non-differential item functioning items showed that for perceptual ability, females scored higher than males and that scores increased with age for both males and females; for verbal ability, the observed increase in scores across age differed for males and females. The implications of these findings are discussed.

  1. Cognitive psychology meets psychometric theory: on the relation between process models for decision making and latent variable models for individual differences

    NARCIS (Netherlands)

    van der Maas, H.L.J.; Molenaar, D.; Maris, G.; Kievit, R.A.; Borsboom, D.

    2011-01-01

    This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual

  2. An emotional functioning item bank of 24 items for computerized adaptive testing (CAT) was established

    DEFF Research Database (Denmark)

    Petersen, Morten Aa.; Gamper, Eva-Maria; Costantini, Anna

    2016-01-01

    of the widely used EORTC Quality of Life questionnaire (QLQ-C30). STUDY DESIGN AND SETTING: On the basis of literature search and evaluations by international samples of experts and cancer patients, 38 candidate items were developed. The psychometric properties of the items were evaluated in a large...... international sample of cancer patients. This included evaluations of dimensionality, item response theory (IRT) model fit, differential item functioning (DIF), and of measurement precision/statistical power. RESULTS: Responses were obtained from 1,023 cancer patients from four countries. The evaluations showed...... that 24 items could be included in a unidimensional IRT model. DIF did not seem to have any significant impact on the estimation of EF. Evaluations indicated that the CAT measure may reduce sample size requirements by up to 50% compared to the QLQ-C30 EF scale without reducing power. CONCLUSION...

  3. The effect of measurement quality on targeted structural model fit indices: A comment on Lance, Beck, Fan, and Carter (2016).

    Science.gov (United States)

    McNeish, Daniel; Hancock, Gregory R

    2018-03-01

    Lance, Beck, Fan, and Carter (2016) recently advanced 6 new fit indices and associated cutoff values for assessing data-model fit in the structural portion of traditional latent variable path models. The authors appropriately argued that, although most researchers' theoretical interest rests with the latent structure, they still rely on indices of global model fit that simultaneously assess both the measurement and structural portions of the model. As such, Lance et al. proposed indices intended to assess the structural portion of the model in isolation of the measurement model. Unfortunately, although these strategies separate the assessment of the structure from the fit of the measurement model, they do not isolate the structure's assessment from the quality of the measurement model. That is, even with a perfectly fitting measurement model, poorer quality (i.e., less reliable) measurements will yield a more favorable verdict regarding structural fit, whereas better quality (i.e., more reliable) measurements will yield a less favorable structural assessment. This phenomenon, referred to by Hancock and Mueller (2011) as the reliability paradox, affects not only traditional global fit indices but also those structural indices proposed by Lance et al. as well. Fortunately, as this comment will clarify, indices proposed by Hancock and Mueller help to mitigate this problem and allow the structural portion of the model to be assessed independently of both the fit of the measurement model as well as the quality of indicator variables contained therein. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  4. Designing a Sine-Coil for Measurement of Plasma Displacements in IR-T1 Tokamak

    International Nuclear Information System (INIS)

    Khorshid, Pejman; Razavi, M.; Molaii, M.; Ghoranneviss, M.; TalebiTaher, A.; Arvin, R.; Mohammadi, S.; NikMohammadi, A.

    2008-01-01

    A method for the measurement of the plasma position in the IR-T1 tokamak in toroidal coordinates is developed. A sine-coil, which is a Rogowski coil with a variable wiring density is designed and fabricated for this purpose. An analytic solution of the Biot-Savart law, which is used to calculate magnetic fields created by toroidal plasma current, is presented. Results of calculations are compared with the experimental data obtained in no-plasma shots with a toroidal current-carrying coil positioned inside the vessel to simulate the plasma movements. The results are shown a good linear behavior of plasma position measurements. The error is less than 2.5% and it is compared with other methods of measurements of the plasma position. This method will be used in the feedback position control system and tests of feedback controller parameters are ongoing

  5. General mixture item response models with different item response structures: Exposition with an application to Likert scales.

    Science.gov (United States)

    Tijmstra, Jesper; Bolsinova, Maria; Jeon, Minjeong

    2018-01-10

    This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person's responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category ("neither agree nor disagree") is taken to be qualitatively similar to the other categories, and is taken to provide information about the person's endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person's willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.

  6. FitSKIRT: genetic algorithms to automatically fit dusty galaxies with a Monte Carlo radiative transfer code

    Science.gov (United States)

    De Geyter, G.; Baes, M.; Fritz, J.; Camps, P.

    2013-02-01

    We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi- dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.

  7. Non-ignorable missingness item response theory models for choice effects in examinee-selected items.

    Science.gov (United States)

    Liu, Chen-Wei; Wang, Wen-Chung

    2017-11-01

    Examinee-selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non-ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two-dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non-ignorable and to determine how to apply the new model to the data collected. Two follow-up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non-ignorable missing data were mistakenly treated as ignorable. © 2017 The British Psychological Society.

  8. A scaled Lagrangian method for performing a least squares fit of a model to plant data

    International Nuclear Information System (INIS)

    Crisp, K.E.

    1988-01-01

    Due to measurement errors, even a perfect mathematical model will not be able to match all the corresponding plant measurements simultaneously. A further discrepancy may be introduced if an un-modelled change in conditions occurs within the plant which should have required a corresponding change in model parameters - e.g. a gradual deterioration in the performance of some component(s). Taking both these factors into account, what is required is that the overall discrepancy between the model predictions and the plant data is kept to a minimum. This process is known as 'model fitting', A method is presented for minimising any function which consists of the sum of squared terms, subject to any constraints. Its most obvious application is in the process of model fitting, where a weighted sum of squares of the differences between model predictions and plant data is the function to be minimised. When implemented within existing Central Electricity Generating Board computer models, it will perform a least squares fit of a model to plant data within a single job submission. (author)

  9. Robustness of the charge-ordered phases in IrTe2 against photoexcitation

    Science.gov (United States)

    Monney, C.; Schuler, A.; Jaouen, T.; Mottas, M.-L.; Wolf, Th.; Merz, M.; Muntwiler, M.; Castiglioni, L.; Aebi, P.; Weber, F.; Hengsberger, M.

    2018-02-01

    We present a time-resolved angle-resolved photoelectron spectroscopy study of IrTe2, which undergoes two first-order structural and charge-ordered phase transitions on cooling below 270 K and below 180 K. The possibility of inducing a phase transition by photoexcitation with near-infrared femtosecond pulses is investigated in the charge-ordered phases. We observe changes of the spectral function occurring within a few hundreds of femtoseconds and persisting up to several picoseconds, which we interpret as a partial photoinduced phase transition (PIPT). The necessary time for photoinducing these spectral changes increases with increasing photoexcitation density and reaches time scales longer than the rise time of the transient electronic temperature. We conclude that the PIPT is driven by a transient increase of the lattice temperature following the energy transfer from the electrons. However, the photoinduced changes of the spectral function are small, which indicates that the low-temperature phase is particularly robust against photoexcitation. We suggest that the system might be trapped in an out-of-equilibrium state, for which only a partial structural transition is achieved.

  10. Toward DSM-V: mapping the alcohol use disorder continuum in college students.

    Science.gov (United States)

    Hagman, Brett T; Cohn, Amy M

    2011-11-01

    The present study examined the dimensionality of DSM-IV Alcohol Use Disorder (AUD) criteria using Item Response Theory (IRT) methods and tested the validity of the proposed DSM-V AUD guidelines in a sample of college students. Participants were 396 college students who reported any alcohol use in the past 90 days and were aged 18 years or older. We conducted factor analyses to determine whether a one- or two-factor model provided a better fit to the AUD criteria. IRT analyses estimated item severity and discrimination parameters for each criterion. Multivariate analyses examined differences among the DSM-V diagnostic cut-off (AUD vs. No AUD) and severity qualifiers (no diagnosis, moderate, severe) across several validating measures of alcohol use. A dominant single-factor model provided the best fit to the AUD criteria. IRT analyses indicated that abuse and dependence criteria were intermixed along the latent continuum. The "legal problems" criterion had the highest severity parameter and the tolerance criterion had the lowest severity parameter. The abuse criterion "social/interpersonal problems" and dependence criterion "activities to obtain alcohol" had the highest discrimination parameter estimates. Multivariate analysis indicated that the DSM-V cut-off point, and severity qualifier groups were distinguishable on several measures of alcohol consumption, drinking consequences, and drinking restraint. Findings suggest that the AUD criteria reflect a latent variable that represents a primary disorder and provide support for the proposed DSM-V AUD criteria in a sample of college students. Continued research in other high-risk samples of college students is needed. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  11. The disconnected values model improves mental well-being and fitness in an employee wellness program.

    Science.gov (United States)

    Anshel, Mark H; Brinthaupt, Thomas M; Kang, Minsoo

    2010-01-01

    This study examined the effect of a 10-week wellness program on changes in physical fitness and mental well-being. The conceptual framework for this study was the Disconnected Values Model (DVM). According to the DVM, detecting the inconsistencies between negative habits and values (e.g., health, family, faith, character) and concluding that these "disconnects" are unacceptable promotes the need for health behavior change. Participants were 164 full-time employees at a university in the southeastern U.S. The program included fitness coaching and a 90-minute orientation based on the DVM. Multivariate Mixed Model analyses indicated significantly improved scores from pre- to post-intervention on selected measures of physical fitness and mental well-being. The results suggest that the Disconnected Values Model provides an effective cognitive-behavioral approach to generating health behavior change in a 10-week workplace wellness program.

  12. GOSSIP: SED fitting code

    Science.gov (United States)

    Franzetti, Paolo; Scodeggio, Marco

    2012-10-01

    GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.

  13. Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

    Science.gov (United States)

    W. Hasan, W. Z.

    2018-01-01

    The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554

  14. Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

    Science.gov (United States)

    Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S

    2018-01-01

    The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

  15. Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

    Directory of Open Access Journals (Sweden)

    A H Sabry

    Full Text Available The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

  16. Approaching the Type-II Dirac Point and Concomitant Superconductivity in Pt-doping Stabilized Metastable 1T-phase IrTe2

    OpenAIRE

    Fei, Fucong; Bo, Xiangyan; Wang, Pengdong; Ying, Jianghua; Chen, Bo; Liu, Qianqian; Zhang, Yong; Sun, Zhe; Qu, Fanming; Zhang, Yi; Li, Jian; Song, Fengqi; Wan, Xiangang; Wang, Baigeng; Wang, Guanghou

    2017-01-01

    Topological semimetal is a topic of general interest in material science. Recently, a new kind of topological semimetal called type-II Dirac semimetal with tilted Dirac cones is discovered in PtSe2 family. However, the further investigation is hindered due to the huge energy difference from Dirac points to Fermi level and the irrelevant conducting pockets at Fermi surface. Here we characterize the optimized type-II Dirac dispersions in a metastable 1T phase of IrTe2. Our strategy of Pt doping...

  17. Bayesian modeling of measurement error in predictor variables

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; Glas, Cornelis A.W.

    2003-01-01

    It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between

  18. An empirical comparison of Item Response Theory and Classical Test Theory

    Directory of Open Access Journals (Sweden)

    Špela Progar

    2008-11-01

    Full Text Available Based on nonlinear models between the measured latent variable and the item response, item response theory (IRT enables independent estimation of item and person parameters and local estimation of measurement error. These properties of IRT are also the main theoretical advantages of IRT over classical test theory (CTT. Empirical evidence, however, often failed to discover consistent differences between IRT and CTT parameters and between invariance measures of CTT and IRT parameter estimates. In this empirical study a real data set from the Third International Mathematics and Science Study (TIMSS 1995 was used to address the following questions: (1 How comparable are CTT and IRT based item and person parameters? (2 How invariant are CTT and IRT based item parameters across different participant groups? (3 How invariant are CTT and IRT based item and person parameters across different item sets? The findings indicate that the CTT and the IRT item/person parameters are very comparable, that the CTT and the IRT item parameters show similar invariance property when estimated across different groups of participants, that the IRT person parameters are more invariant across different item sets, and that the CTT item parameters are at least as much invariant in different item sets as the IRT item parameters. The results furthermore demonstrate that, with regards to the invariance property, IRT item/person parameters are in general empirically superior to CTT parameters, but only if the appropriate IRT model is used for modelling the data.

  19. An Introduction to the DA-T Gibbs Sampler for the Two-Parameter Logistic (2PL Model and Beyond

    Directory of Open Access Journals (Sweden)

    Gunter Maris

    2005-01-01

    Full Text Available The DA-T Gibbs sampler is proposed by Maris and Maris (2002 as a Bayesian estimation method for a wide variety of Item Response Theory (IRT models. The present paper provides an expository account of the DAT Gibbs sampler for the 2PL model. However, the scope is not limited to the 2PL model. It is demonstrated how the DA-T Gibbs sampler for the 2PL may be used to build, quite easily, Gibbs samplers for other IRT models. Furthermore, the paper contains a novel, intuitive derivation of the Gibbs sampler and could be read for a graduate course on sampling.

  20. Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

    Science.gov (United States)

    Hagell, Peter; Westergren, Albert

    Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

  1. Structure of chaotic magnetic field lines in IR-T1 tokamak due to ergodic magnetic limiter

    Science.gov (United States)

    Ahmadi, S.; Salar Elahi, A.; Ghorannevis, M.

    2018-03-01

    In this paper we have studied an Ergodic Magnetic Limiter (EML) based chaotic magnetic field for transport control in the edge plasma of IR-T1 tokamak. The resonance created by the EML causes perturbation of the equilibrium field line in tokamak and as a result, the field lines are chaotic in the vicinity of the dimerized island chains. Transport barriers are formed in the chaotic field line and actually observe in tokamak with reverse magnetic shear. We used area-preserving non-twist (and twist) Poincaré maps to describe the formation of transport barriers, which are actually features of Hamiltonian systems. This transport barrier is useful in reducing radial diffusion of the field line and thus improving the plasma confinement.

  2. Structure of chaotic magnetic field lines in IR-T1 tokamak due to ergodic magnetic limiter

    Directory of Open Access Journals (Sweden)

    S. Ahmadi

    2018-03-01

    Full Text Available In this paper we have studied an Ergodic Magnetic Limiter (EML based chaotic magnetic field for transport control in the edge plasma of IR-T1 tokamak. The resonance created by the EML causes perturbation of the equilibrium field line in tokamak and as a result, the field lines are chaotic in the vicinity of the dimerized island chains. Transport barriers are formed in the chaotic field line and actually observe in tokamak with reverse magnetic shear. We used area-preserving non-twist (and twist Poincaré maps to describe the formation of transport barriers, which are actually features of Hamiltonian systems. This transport barrier is useful in reducing radial diffusion of the field line and thus improving the plasma confinement.

  3. The bystander effect model of Brenner and Sachs fitted to lung cancer data in 11 cohorts of underground miners, and equivalence of fit of a linear relative risk model with adjustment for attained age and age at exposure

    International Nuclear Information System (INIS)

    Little, M P

    2004-01-01

    Bystander effects following exposure to α-particles have been observed in many experimental systems, and imply that linearly extrapolating low dose risks from high dose data might materially underestimate risk. Brenner and Sachs (2002 Int. J. Radiat. Biol. 78 593-604; 2003 Health Phys. 85 103-8) have recently proposed a model of the bystander effect which they use to explain the inverse dose rate effect observed for lung cancer in underground miners exposed to radon daughters. In this paper we fit the model of the bystander effect proposed by Brenner and Sachs to 11 cohorts of underground miners, taking account of the covariance structure of the data and the period of latency between the development of the first pre-malignant cell and clinically overt cancer. We also fitted a simple linear relative risk model, with adjustment for age at exposure and attained age. The methods that we use for fitting both models are different from those used by Brenner and Sachs, in particular taking account of the covariance structure, which they did not, and omitting certain unjustifiable adjustments to the miner data. The fit of the original model of Brenner and Sachs (with 0 y period of latency) is generally poor, although it is much improved by assuming a 5 or 6 y period of latency from the first appearance of a pre-malignant cell to cancer. The fit of this latter model is equivalent to that of a linear relative risk model with adjustment for age at exposure and attained age. In particular, both models are capable of describing the observed inverse dose rate effect in this data set

  4. Plasma column displacement measurements by modified Rogowski sine-coil and Biot-Savart/magnetic flux equation solution on IR-T1 tokamak

    International Nuclear Information System (INIS)

    Razavi, M.; Mollai, M.; Khorshid, P.; Nedzelskiy, I.; Ghoranneviss, M.

    2010-01-01

    The modified Rogowski sine-coil (MRSC) has been designed and implemented for the plasma column horizontal displacement measurements on small IR-T1 tokamak. MRSC operation has been examined on test assembly and tokamak. Obtained results show high sensitivity to the plasma column horizontal displacement and negligible sensitivity to the vertical displacement; linearity in wide, ±0.1 m, range of the displacements; and excellent, 1.5%, agreement with the results of numerical solution of Biot-Savart and magnetic flux equations.

  5. Fitted HBT radii versus space-time variances in flow-dominated models

    International Nuclear Information System (INIS)

    Lisa, Mike; Frodermann, Evan; Heinz, Ulrich

    2007-01-01

    The inability of otherwise successful dynamical models to reproduce the 'HBT radii' extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the 'RHIC HBT Puzzle'. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source which can be directly computed from the emission function, without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models some of which exhibit significant deviations from simple Gaussian behaviour. By Fourier transforming the emission function we compute the 2-particle correlation function and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and measured HBT radii remain, we show that a more 'apples-to-apples' comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data. (author)

  6. Better assessment of physical function: item improvement is neglected but essential.

    Science.gov (United States)

    Bruce, Bonnie; Fries, James F; Ambrosini, Debbie; Lingala, Bharathi; Gandek, Barbara; Rose, Matthias; Ware, John E

    2009-01-01

    Physical function is a key component of patient-reported outcome (PRO) assessment in rheumatology. Modern psychometric methods, such as Item Response Theory (IRT) and Computerized Adaptive Testing, can materially improve measurement precision at the item level. We present the qualitative and quantitative item-evaluation process for developing the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function item bank. The process was stepwise: we searched extensively to identify extant Physical Function items and then classified and selectively reduced the item pool. We evaluated retained items for content, clarity, relevance and comprehension, reading level, and translation ease by experts and patient surveys, focus groups, and cognitive interviews. We then assessed items by using classic test theory and IRT, used confirmatory factor analyses to estimate item parameters, and graded response modeling for parameter estimation. We retained the 20 Legacy (original) Health Assessment Questionnaire Disability Index (HAQ-DI) and the 10 SF-36's PF-10 items for comparison. Subjects were from rheumatoid arthritis, osteoarthritis, and healthy aging cohorts (n = 1,100) and a national Internet sample of 21,133 subjects. We identified 1,860 items. After qualitative and quantitative evaluation, 124 newly developed PROMIS items composed the PROMIS item bank, which included revised Legacy items with good fit that met IRT model assumptions. Results showed that the clearest and best-understood items were simple, in the present tense, and straightforward. Basic tasks (like dressing) were more relevant and important versus complex ones (like dancing). Revised HAQ-DI and PF-10 items with five response options had higher item-information content than did comparable original Legacy items with fewer response options. IRT analyses showed that the Physical Function domain satisfied general criteria for unidimensionality with one-, two-, three-, and four-factor models

  7. Determination of a Differential Item Functioning Procedure Using the Hierarchical Generalized Linear Model

    Directory of Open Access Journals (Sweden)

    Tülin Acar

    2012-01-01

    Full Text Available The aim of this research is to compare the result of the differential item functioning (DIF determining with hierarchical generalized linear model (HGLM technique and the results of the DIF determining with logistic regression (LR and item response theory–likelihood ratio (IRT-LR techniques on the test items. For this reason, first in this research, it is determined whether the students encounter DIF with HGLM, LR, and IRT-LR techniques according to socioeconomic status (SES, in the Turkish, Social Sciences, and Science subtest items of the Secondary School Institutions Examination. When inspecting the correlations among the techniques in terms of determining the items having DIF, it was discovered that there was significant correlation between the results of IRT-LR and LR techniques in all subtests; merely in Science subtest, the results of the correlation between HGLM and IRT-LR techniques were found significant. DIF applications can be made on test items with other DIF analysis techniques that were not taken to the scope of this research. The analysis results, which were determined by using the DIF techniques in different sample sizes, can be compared.

  8. Reconstructing the Roman Site “Aquis Querquennis” (Bande, Spain from GPR, T-LiDAR and IRT Data Fusion

    Directory of Open Access Journals (Sweden)

    Iván Puente

    2018-03-01

    Full Text Available This work presents the three-dimensional (3D reconstruction of one of the most important archaeological sites in Galicia: “Aquis Querquennis” (Bande, Spain using in-situ non-invasive ground-penetrating radar (GPR and Terrestrial Light Detection and Ranging (T-LiDAR techniques, complemented with infrared thermography. T-LiDAR is used for the recording of the 3D surface of this particular case and provides high resolution 3D digital models. GPR data processing is performed through the novel software tool “toGPRi”, developed by the authors, which allows the creation of a 3D model of the sub-surface and the subsequent XY images or time-slices at different depths. All these products are georeferenced, in such a way that the GPR orthoimages can be combined with the orthoimages from the T-LiDAR for a complete interpretation of the site. In this way, the GPR technique allows for the detection of the structures of the barracks that are buried, and their distribution is completed with the structure measured by the T-LiDAR on the surface. In addition, the detection of buried elements made possible the identification and labelling of the structures of the surface and their uses. These structures are additionally inspected with infrared thermography (IRT to determine their conservation condition and distinguish between original and subsequent constructions.

  9. The possibility of creating a new low power nuclear facility with slightly enriched nuclear fuel on the basis of the decommissioned IRT-M reactor intended for applied purposes

    International Nuclear Information System (INIS)

    Abramidze, Sh.P.; Katamadze, N.M.; Kiknadze, G.G.; Rostomashvili, Z.I.; Saralidze, Z.K.

    2002-01-01

    Nearly 50 years have passed since the appearance of the first nuclear research reactors. Most of them have completed their operating life and must be dismantled. But it is known that the dismantling of permanently shut down nuclear reactors is a very complex process, full realization that it generates a lot of radioactive waste (both solid and liquid), it is connected with high financial expenditures, and its solution is apparently beyond the possibilities of many countries, including Georgia In the given paper we consider a radiologically safe, ecologically clean and economically beneficial version of the decommissioning of the IRT-M nuclear research reactor and the stages of its implementation that are not connected with the dismantling of its highly radioactive technological components. We justify the possibility of creating a new Low Power Nuclear Facility on the basis of the decommissioned IRT-M reactor to solve the problems of applied nature in different fields of science and technology being very important for Georgia. (author)

  10. A cautionary note on the use of information fit indexes in covariance structure modeling with means

    NARCIS (Netherlands)

    Wicherts, J.M.; Dolan, C.V.

    2004-01-01

    Information fit indexes such as Akaike Information Criterion, Consistent Akaike Information Criterion, Bayesian Information Criterion, and the expected cross validation index can be valuable in assessing the relative fit of structural equation models that differ regarding restrictiveness. In cases

  11. Assessing performance of Bayesian state-space models fit to Argos satellite telemetry locations processed with Kalman filtering.

    Directory of Open Access Journals (Sweden)

    Mónica A Silva

    Full Text Available Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF. The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km was nearly half that of LS estimates (11.6 ± 8.4 km. Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.

  12. Cognitive Psychology Meets Psychometric Theory: On the Relation between Process Models for Decision Making and Latent Variable Models for Individual Differences

    Science.gov (United States)

    van der Maas, Han L. J.; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A.; Borsboom, Denny

    2011-01-01

    This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line…

  13. The FIT Model - Fuel-cycle Integration and Tradeoffs

    International Nuclear Information System (INIS)

    Piet, Steven J.; Soelberg, Nick R.; Bays, Samuel E.; Pereira, Candido; Pincock, Layne F.; Shaber, Eric L.; Teague, Melissa C.; Teske, Gregory M.; Vedros, Kurt G.

    2010-01-01

    All mass streams from fuel separation and fabrication are products that must meet some set of product criteria - fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the 'system losses study' team that developed it (Shropshire2009, Piet2010) are an initial step by the FCR and D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R and D needs and set longer-term goals. The question originally posed to the 'system losses study' was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for 'minimum fuel treatment' approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.

  14. Measuring parental stress in mothers of infants: A Rasch-based construct validity study

    DEFF Research Database (Denmark)

    Nielsen, Tine; Pontoppidan, Maiken; Kristensen, Ingeborg Hedegaard

    of the Danish language version of the PSS in a community sample of 1110 mothers of children aged 0 to 12 months employing the Rasch family of IRT models, and emphasizing the issues of unidimensionality and equal item functioning (no DIF) relative to the age and educational levels of the mothers. No adequate fit......) were found each to fit so-called graphical loglinear Rasch models: The parental stress subscale fit a model adjusted for local response dependence between some item pairs, as well as DIF for one item relative to mothers’ level of education and DIF for another item relative to age and educational level...... of the mothers. The parental satisfaction subscale fit a model adjusted only for local response dependence. The findings are in line with the original interpretation of the PSS. We recommend that the scoring of the PSS is changed to reflect the two subscales and the dichotomization of response categories...

  15. An Improved Cognitive Model of the Iowa and Soochow Gambling Tasks With Regard to Model Fitting Performance and Tests of Parameter Consistency

    Directory of Open Access Journals (Sweden)

    Junyi eDai

    2015-03-01

    Full Text Available The Iowa Gambling Task (IGT and the Soochow Gambling Task (SGT are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning model (EVL and the prospect valence learning model (PVL, have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL models and, in addition, produce more consistent parameter estimates across the IGT and SGT. Twenty-six opiate users (mean age 34.23; SD 8.79 and 27 control participants (mean age 35; SD 10.44 completed both tasks. Eighteen cognitive models varying in evaluation, updating, and choice rules were fit to individual data and their performances were compared to that of a statistical baseline model to find a best fitting model. The results showed that the model combining the prospect utility function treating gains and losses separately, the decay-reinforcement updating rule, and the trial-independent choice rule performed the best in both tasks. Furthermore, the winning model produced more consistent individual parameter estimates across the two tasks than any of the other models.

  16. Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes

    Science.gov (United States)

    Leite, Walter L.; Stapleton, Laura M.

    2011-01-01

    In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…

  17. Fitting the Fractional Polynomial Model to Non-Gaussian Longitudinal Data

    Directory of Open Access Journals (Sweden)

    Ji Hoon Ryoo

    2017-08-01

    Full Text Available As in cross sectional studies, longitudinal studies involve non-Gaussian data such as binomial, Poisson, gamma, and inverse-Gaussian distributions, and multivariate exponential families. A number of statistical tools have thus been developed to deal with non-Gaussian longitudinal data, including analytic techniques to estimate parameters in both fixed and random effects models. However, as yet growth modeling with non-Gaussian data is somewhat limited when considering the transformed expectation of the response via a linear predictor as a functional form of explanatory variables. In this study, we introduce a fractional polynomial model (FPM that can be applied to model non-linear growth with non-Gaussian longitudinal data and demonstrate its use by fitting two empirical binary and count data models. The results clearly show the efficiency and flexibility of the FPM for such applications.

  18. Tanning Shade Gradations of Models in Mainstream Fitness and Muscle Enthusiast Magazines: Implications for Skin Cancer Prevention in Men.

    Science.gov (United States)

    Basch, Corey H; Hillyer, Grace Clarke; Ethan, Danna; Berdnik, Alyssa; Basch, Charles E

    2015-07-01

    Tanned skin has been associated with perceptions of fitness and social desirability. Portrayal of models in magazines may reflect and perpetuate these perceptions. Limited research has investigated tanning shade gradations of models in men's versus women's fitness and muscle enthusiast magazines. Such findings are relevant in light of increased incidence and prevalence of melanoma in the United States. This study evaluated and compared tanning shade gradations of adult Caucasian male and female model images in mainstream fitness and muscle enthusiast magazines. Sixty-nine U.S. magazine issues (spring and summer, 2013) were utilized. Two independent reviewers rated tanning shade gradations of adult Caucasian male and female model images on magazines' covers, advertisements, and feature articles. Shade gradations were assessed using stock photographs of Caucasian models with varying levels of tanned skin on an 8-shade scale. A total of 4,683 images were evaluated. Darkest tanning shades were found among males in muscle enthusiast magazines and lightest among females in women's mainstream fitness magazines. By gender, male model images were 54% more likely to portray a darker tanning shade. In this study, images in men's (vs. women's) fitness and muscle enthusiast magazines portrayed Caucasian models with darker skin shades. Despite these magazines' fitness-related messages, pro-tanning images may promote attitudes and behaviors associated with higher skin cancer risk. To date, this is the first study to explore tanning shades in men's magazines of these genres. Further research is necessary to identify effects of exposure to these images among male readers. © The Author(s) 2014.

  19. Source Localization with Acoustic Sensor Arrays Using Generative Model Based Fitting with Sparse Constraints

    Directory of Open Access Journals (Sweden)

    Javier Macias-Guarasa

    2012-10-01

    Full Text Available This paper presents a novel approach for indoor acoustic source localization using sensor arrays. The proposed solution starts by defining a generative model, designed to explain the acoustic power maps obtained by Steered Response Power (SRP strategies. An optimization approach is then proposed to fit the model to real input SRP data and estimate the position of the acoustic source. Adequately fitting the model to real SRP data, where noise and other unmodelled effects distort the ideal signal, is the core contribution of the paper. Two basic strategies in the optimization are proposed. First, sparse constraints in the parameters of the model are included, enforcing the number of simultaneous active sources to be limited. Second, subspace analysis is used to filter out portions of the input signal that cannot be explained by the model. Experimental results on a realistic speech database show statistically significant localization error reductions of up to 30% when compared with the SRP-PHAT strategies.

  20. An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data

    Directory of Open Access Journals (Sweden)

    Loreen eHertäg

    2012-09-01

    Full Text Available For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ('in-vivo-like' input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a 'high-throughput' model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

  1. A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

    DEFF Research Database (Denmark)

    Ding, Tao; Li, Cheng; Huang, Can

    2018-01-01

    –slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

  2. A Data-Driven Method for Selecting Optimal Models Based on Graphical Visualisation of Differences in Sequentially Fitted ROC Model Parameters

    Directory of Open Access Journals (Sweden)

    K S Mwitondi

    2013-05-01

    Full Text Available Differences in modelling techniques and model performance assessments typically impinge on the quality of knowledge extraction from data. We propose an algorithm for determining optimal patterns in data by separately training and testing three decision tree models in the Pima Indians Diabetes and the Bupa Liver Disorders datasets. Model performance is assessed using ROC curves and the Youden Index. Moving differences between sequential fitted parameters are then extracted, and their respective probability density estimations are used to track their variability using an iterative graphical data visualisation technique developed for this purpose. Our results show that the proposed strategy separates the groups more robustly than the plain ROC/Youden approach, eliminates obscurity, and minimizes over-fitting. Further, the algorithm can easily be understood by non-specialists and demonstrates multi-disciplinary compliance.

  3. Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder

    DEFF Research Database (Denmark)

    Albertsen, Christoffer Moesgaard; Whoriskey, Kim; Yurkowski, David

    2015-01-01

    recommend using the Laplace approximation combined with automatic differentiation (as implemented in the novel R package Template Model Builder; TMB) for the fast fitting of continuous-time multivariate non-Gaussian SSMs. Through Argos satellite tracking data, we demonstrate that the use of continuous...... are able to estimate additional parameters compared to previous methods, all without requiring a substantial increase in computational time. The model implementation is made available through the R package argosTrack....

  4. Log-normal frailty models fitted as Poisson generalized linear mixed models.

    Science.gov (United States)

    Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

    2016-12-01

    The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. IRTPRO 2.1 for Windows (Item Response Theory for Patient-Reported Outcomes)

    Science.gov (United States)

    Paek, Insu; Han, Kyung T.

    2013-01-01

    This article reviews a new item response theory (IRT) model estimation program, IRTPRO 2.1, for Windows that is capable of unidimensional and multidimensional IRT model estimation for existing and user-specified constrained IRT models for dichotomously and polytomously scored item response data. (Contains 1 figure and 2 notes.)

  6. Multiple organ definition in CT using a Bayesian approach for 3D model fitting

    Science.gov (United States)

    Boes, Jennifer L.; Weymouth, Terry E.; Meyer, Charles R.

    1995-08-01

    Organ definition in computed tomography (CT) is of interest for treatment planning and response monitoring. We present a method for organ definition using a priori information about shape encoded in a set of biometric organ models--specifically for the liver and kidney-- that accurately represents patient population shape information. Each model is generated by averaging surfaces from a learning set of organ shapes previously registered into a standard space defined by a small set of landmarks. The model is placed in a specific patient's data set by identifying these landmarks and using them as the basis for model deformation; this preliminary representation is then iteratively fit to the patient's data based on a Bayesian formulation of the model's priors and CT edge information, yielding a complete organ surface. We demonstrate this technique using a set of fifteen abdominal CT data sets for liver surface definition both before and after the addition of a kidney model to the fitting; we demonstrate the effectiveness of this tool for organ surface definition in this low-contrast domain.

  7. The 'fitting problem' in cosmology

    International Nuclear Information System (INIS)

    Ellis, G.F.R.; Stoeger, W.

    1987-01-01

    The paper considers the best way to fit an idealised exactly homogeneous and isotropic universe model to a realistic ('lumpy') universe; whether made explicit or not, some such approach of necessity underlies the use of the standard Robertson-Walker models as models of the real universe. Approaches based on averaging, normal coordinates and null data are presented, the latter offering the best opportunity to relate the fitting procedure to data obtainable by astronomical observations. (author)

  8. A fitting LEGACY – modelling Kepler's best stars

    Directory of Open Access Journals (Sweden)

    Aarslev Magnus J.

    2017-01-01

    Full Text Available The LEGACY sample represents the best solar-like stars observed in the Kepler mission[5, 8]. The 66 stars in the sample are all on the main sequence or only slightly more evolved. They each have more than one year's observation data in short cadence, allowing for precise extraction of individual frequencies. Here we present model fits using a modified ASTFIT procedure employing two different near-surface-effect corrections, one by Christensen-Dalsgaard[4] and a newer correction proposed by Ball & Gizon[1]. We then compare the results obtained using the different corrections. We find that using the latter correction yields lower masses and significantly lower χ2 values for a large part of the sample.

  9. Fitting the CDO correlation skew: a tractable structural jump-diffusion model

    DEFF Research Database (Denmark)

    Willemann, Søren

    2007-01-01

    We extend a well-known structural jump-diffusion model for credit risk to handle both correlations through diffusion of asset values and common jumps in asset value. Through a simplifying assumption on the default timing and efficient numerical techniques, we develop a semi-analytic framework...... allowing for instantaneous calibration to heterogeneous CDS curves and fast computation of CDO tranche spreads. We calibrate the model to CDX and iTraxx data from February 2007 and achieve a satisfactory fit. To price the senior tranches for both indices, we require a risk-neutral probability of a market...

  10. Development and design of a late-model fitness test instrument based on LabView

    Science.gov (United States)

    Xie, Ying; Wu, Feiqing

    2010-12-01

    Undergraduates are pioneers of China's modernization program and undertake the historic mission of rejuvenating our nation in the 21st century, whose physical fitness is vital. A smart fitness test system can well help them understand their fitness and health conditions, thus they can choose more suitable approaches and make practical plans for exercising according to their own situation. following the future trends, a Late-model fitness test Instrument based on LabView has been designed to remedy defects of today's instruments. The system hardware consists of fives types of sensors with their peripheral circuits, an acquisition card of NI USB-6251 and a computer, while the system software, on the basis of LabView, includes modules of user register, data acquisition, data process and display, and data storage. The system, featured by modularization and an open structure, is able to be revised according to actual needs. Tests results have verified the system's stability and reliability.

  11. Invited commentary: Lost in estimation--searching for alternatives to markov chains to fit complex Bayesian models.

    Science.gov (United States)

    Molitor, John

    2012-03-01

    Bayesian methods have seen an increase in popularity in a wide variety of scientific fields, including epidemiology. One of the main reasons for their widespread application is the power of the Markov chain Monte Carlo (MCMC) techniques generally used to fit these models. As a result, researchers often implicitly associate Bayesian models with MCMC estimation procedures. However, Bayesian models do not always require Markov-chain-based methods for parameter estimation. This is important, as MCMC estimation methods, while generally quite powerful, are complex and computationally expensive and suffer from convergence problems related to the manner in which they generate correlated samples used to estimate probability distributions for parameters of interest. In this issue of the Journal, Cole et al. (Am J Epidemiol. 2012;175(5):368-375) present an interesting paper that discusses non-Markov-chain-based approaches to fitting Bayesian models. These methods, though limited, can overcome some of the problems associated with MCMC techniques and promise to provide simpler approaches to fitting Bayesian models. Applied researchers will find these estimation approaches intuitively appealing and will gain a deeper understanding of Bayesian models through their use. However, readers should be aware that other non-Markov-chain-based methods are currently in active development and have been widely published in other fields.

  12. Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

    Science.gov (United States)

    Duarte, Adam; Adams, Michael J.; Peterson, James T.

    2018-01-01

    Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision

  13. Decision making on fitness landscapes

    Science.gov (United States)

    Arthur, R.; Sibani, P.

    2017-04-01

    We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et al. that we call the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures.

  14. Decision Making on Fitness Landscapes

    DEFF Research Database (Denmark)

    Arthur, Rudy; Sibani, Paolo

    2017-01-01

    We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et. al. that we call...... the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures....

  15. Assessing the Accuracy and Consistency of Language Proficiency Classification under Competing Measurement Models

    Science.gov (United States)

    Zhang, Bo

    2010-01-01

    This article investigates how measurement models and statistical procedures can be applied to estimate the accuracy of proficiency classification in language testing. The paper starts with a concise introduction of four measurement models: the classical test theory (CTT) model, the dichotomous item response theory (IRT) model, the testlet response…

  16. Assessing a moderating effect and the global fit of a PLS model on online trading

    Directory of Open Access Journals (Sweden)

    Juan J. García-Machado

    2017-12-01

    Full Text Available This paper proposes a PLS Model for the study of Online Trading. Traditional investing has experienced a revolution due to the rise of e-trading services that enable investors to use Internet conduct secure trading. On the hand, model results show that there is a positive, direct and statistically significant relationship between personal outcome expectations, perceived relative advantage, shared vision and economy-based trust with the quality of knowledge. On the other hand, trading frequency and portfolio performance has also this relationship. After including the investor’s income and financial wealth (IFW as moderating effect, the PLS model was enhanced, and we found that the interaction term is negative and statistically significant, so, higher IFW levels entail a weaker relationship between trading frequency and portfolio performance and vice-versa. Finally, with regard to the goodness of overall model fit measures, they showed that the model is fit for SRMR and dG measures, so it is likely that the model is true.

  17. Keep Using My Health Apps: Discover Users' Perception of Health and Fitness Apps with the UTAUT2 Model.

    Science.gov (United States)

    Yuan, Shupei; Ma, Wenjuan; Kanthawala, Shaheen; Peng, Wei

    2015-09-01

    Health and fitness applications (apps) are one of the major app categories in the current mobile app market. Few studies have examined this area from the users' perspective. This study adopted the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) Model to examine the predictors of the users' intention to adopt health and fitness apps. A survey (n=317) was conducted with college-aged smartphone users at a Midwestern university in the United States. Performance expectancy, hedonic motivations, price value, and habit were significant predictors of users' intention of continued usage of health and fitness apps. However, effort expectancy, social influence, and facilitating conditions were not found to predict users' intention of continued usage of health and fitness apps. This study extends the UTATU2 Model to the mobile apps domain and provides health professions, app designers, and marketers with the insights of user experience in terms of continuously using health and fitness apps.

  18. Phylogenetic tree reconstruction accuracy and model fit when proportions of variable sites change across the tree.

    Science.gov (United States)

    Shavit Grievink, Liat; Penny, David; Hendy, Michael D; Holland, Barbara R

    2010-05-01

    Commonly used phylogenetic models assume a homogeneous process through time in all parts of the tree. However, it is known that these models can be too simplistic as they do not account for nonhomogeneous lineage-specific properties. In particular, it is now widely recognized that as constraints on sequences evolve, the proportion and positions of variable sites can vary between lineages causing heterotachy. The extent to which this model misspecification affects tree reconstruction is still unknown. Here, we evaluate the effect of changes in the proportions and positions of variable sites on model fit and tree estimation. We consider 5 current models of nucleotide sequence evolution in a Bayesian Markov chain Monte Carlo framework as well as maximum parsimony (MP). We show that for a tree with 4 lineages where 2 nonsister taxa undergo a change in the proportion of variable sites tree reconstruction under the best-fitting model, which is chosen using a relative test, often results in the wrong tree. In this case, we found that an absolute test of model fit is a better predictor of tree estimation accuracy. We also found further evidence that MP is not immune to heterotachy. In addition, we show that increased sampling of taxa that have undergone a change in proportion and positions of variable sites is critical for accurate tree reconstruction.

  19. Measuring fit of sequence data to phylogenetic model: gain of power using marginal tests.

    Science.gov (United States)

    Waddell, Peter J; Ota, Rissa; Penny, David

    2009-10-01

    Testing fit of data to model is fundamentally important to any science, but publications in the field of phylogenetics rarely do this. Such analyses discard fundamental aspects of science as prescribed by Karl Popper. Indeed, not without cause, Popper (Unended quest: an intellectual autobiography. Fontana, London, 1976) once argued that evolutionary biology was unscientific as its hypotheses were untestable. Here we trace developments in assessing fit from Penny et al. (Nature 297:197-200, 1982) to the present. We compare the general log-likelihood ratio (the G or G (2) statistic) statistic between the evolutionary tree model and the multinomial model with that of marginalized tests applied to an alignment (using placental mammal coding sequence data). It is seen that the most general test does not reject the fit of data to model (P approximately 0.5), but the marginalized tests do. Tests on pairwise frequency (F) matrices, strongly (P < 0.001) reject the most general phylogenetic (GTR) models commonly in use. It is also clear (P < 0.01) that the sequences are not stationary in their nucleotide composition. Deviations from stationarity and homogeneity seem to be unevenly distributed amongst taxa; not necessarily those expected from examining other regions of the genome. By marginalizing the 4( t ) patterns of the i.i.d. model to observed and expected parsimony counts, that is, from constant sites, to singletons, to parsimony informative characters of a minimum possible length, then the likelihood ratio test regains power, and it too rejects the evolutionary model with P < 0.001. Given such behavior over relatively recent evolutionary time, readers in general should maintain a healthy skepticism of results, as the scale of the systematic errors in published trees may really be far larger than the analytical methods (e.g., bootstrap) report.

  20. UROX 2.0: an interactive tool for fitting atomic models into electron-microscopy reconstructions

    International Nuclear Information System (INIS)

    Siebert, Xavier; Navaza, Jorge

    2009-01-01

    UROX is software designed for the interactive fitting of atomic models into electron-microscopy reconstructions. The main features of the software are presented, along with a few examples. Electron microscopy of a macromolecular structure can lead to three-dimensional reconstructions with resolutions that are typically in the 30–10 Å range and sometimes even beyond 10 Å. Fitting atomic models of the individual components of the macromolecular structure (e.g. those obtained by X-ray crystallography or nuclear magnetic resonance) into an electron-microscopy map allows the interpretation of the latter at near-atomic resolution, providing insight into the interactions between the components. Graphical software is presented that was designed for the interactive fitting and refinement of atomic models into electron-microscopy reconstructions. Several characteristics enable it to be applied over a wide range of cases and resolutions. Firstly, calculations are performed in reciprocal space, which results in fast algorithms. This allows the entire reconstruction (or at least a sizeable portion of it) to be used by taking into account the symmetry of the reconstruction both in the calculations and in the graphical display. Secondly, atomic models can be placed graphically in the map while the correlation between the model-based electron density and the electron-microscopy reconstruction is computed and displayed in real time. The positions and orientations of the models are refined by a least-squares minimization. Thirdly, normal-mode calculations can be used to simulate conformational changes between the atomic model of an individual component and its corresponding density within a macromolecular complex determined by electron microscopy. These features are illustrated using three practical cases with different symmetries and resolutions. The software, together with examples and user instructions, is available free of charge at http://mem.ibs.fr/UROX/

  1. Fitness, Sleep-Disordered Breathing, Symptoms of Depression, and Cognition in Inactive Overweight Children: Mediation Models.

    Science.gov (United States)

    Stojek, Monika M K; Montoya, Amanda K; Drescher, Christopher F; Newberry, Andrew; Sultan, Zain; Williams, Celestine F; Pollock, Norman K; Davis, Catherine L

    We used mediation models to examine the mechanisms underlying the relationships among physical fitness, sleep-disordered breathing (SDB), symptoms of depression, and cognitive functioning. We conducted a cross-sectional secondary analysis of the cohorts involved in the 2003-2006 project PLAY (a trial of the effects of aerobic exercise on health and cognition) and the 2008-2011 SMART study (a trial of the effects of exercise on cognition). A total of 397 inactive overweight children aged 7-11 received a fitness test, standardized cognitive test (Cognitive Assessment System, yielding Planning, Attention, Simultaneous, Successive, and Full Scale scores), and depression questionnaire. Parents completed a Pediatric Sleep Questionnaire. We used bootstrapped mediation analyses to test whether SDB mediated the relationship between fitness and depression and whether SDB and depression mediated the relationship between fitness and cognition. Fitness was negatively associated with depression ( B = -0.041; 95% CI, -0.06 to -0.02) and SDB ( B = -0.005; 95% CI, -0.01 to -0.001). SDB was positively associated with depression ( B = 0.99; 95% CI, 0.32 to 1.67) after controlling for fitness. The relationship between fitness and depression was mediated by SDB (indirect effect = -0.005; 95% CI, -0.01 to -0.0004). The relationship between fitness and the attention component of cognition was independently mediated by SDB (indirect effect = 0.058; 95% CI, 0.004 to 0.13) and depression (indirect effect = -0.071; 95% CI, -0.01 to -0.17). SDB mediates the relationship between fitness and depression, and SDB and depression separately mediate the relationship between fitness and the attention component of cognition.

  2. The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting

    Science.gov (United States)

    Tao, Zhang; Li, Zhang; Dingjun, Chen

    On the basis of the idea of the second multiplication curve fitting, the number and scale of Chinese E-commerce site is analyzed. A preventing increase model is introduced in this paper, and the model parameters are solved by the software of Matlab. The validity of the preventing increase model is confirmed though the numerical experiment. The experimental results show that the precision of preventing increase model is ideal.

  3. Magnetic evaluation of hydrogen pressures changes on MHD fluctuations in IR-T1 tokamak plasma

    Science.gov (United States)

    Alipour, Ramin; Ghanbari, Mohamad R.

    2018-04-01

    Identification of tokamak plasma parameters and investigation on the effects of each parameter on the plasma characteristics is important for the better understanding of magnetohydrodynamic (MHD) activities in the tokamak plasma. The effect of different hydrogen pressures of 1.9, 2.5 and 2.9 Torr on MHD fluctuations of the IR-T1 tokamak plasma was investigated by using of 12 Mirnov coils, singular value decomposition and wavelet analysis. The parameters such as plasma current, loop voltage, power spectrum density, energy percent of poloidal modes, dominant spatial structures and temporal structures of poloidal modes at different plasma pressures are plotted. The results indicate that the MHD activities at the pressure of 2.5 Torr are less than them at other pressures. It also has been shown that in the stable area of plasma and at the pressure of 2.5 Torr, the magnetic force and the force of plasma pressure are in balance with each other and the MHD activities are at their lowest level.

  4. Testing the validity of stock-recruitment curve fits

    International Nuclear Information System (INIS)

    Christensen, S.W.; Goodyear, C.P.

    1988-01-01

    The utilities relied heavily on the Ricker stock-recruitment model as the basis for quantifying biological compensation in the Hudson River power case. They presented many fits of the Ricker model to data derived from striped bass catch and effort records compiled by the National Marine Fisheries Service. Based on this curve-fitting exercise, a value of 4 was chosen for the parameter alpha in the Ricker model, and this value was used to derive the utilities' estimates of the long-term impact of power plants on striped bass populations. A technique was developed and applied to address a single fundamental question: if the Ricker model were applicable to the Hudson River striped bass population, could the estimates of alpha from the curve-fitting exercise be considered reliable. The technique involved constructing a simulation model that incorporated the essential biological features of the population and simulated the characteristics of the available actual catch-per-unit-effort data through time. The ability or failure to retrieve the known parameter values underlying the simulation model via the curve-fitting exercise was a direct test of the reliability of the results of fitting stock-recruitment curves to the real data. The results demonstrated that estimates of alpha from the curve-fitting exercise were not reliable. The simulation-modeling technique provides an effective way to identify whether or not particular data are appropriate for use in fitting such models. 39 refs., 2 figs., 3 tabs

  5. Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach.

    Science.gov (United States)

    König, Laura M; Sproesser, Gudrun; Schupp, Harald T; Renner, Britta

    2018-03-13

    Although mobile technologies such as smartphone apps are promising means for motivating people to adopt a healthier lifestyle (mHealth apps), previous studies have shown low adoption and continued use rates. Developing the means to address this issue requires further understanding of mHealth app nonusers and adoption processes. This study utilized a stage model approach based on the Precaution Adoption Process Model (PAPM), which proposes that people pass through qualitatively different motivational stages when adopting a behavior. To establish a better understanding of between-stage transitions during app adoption, this study aimed to investigate the adoption process of nutrition and fitness app usage, and the sociodemographic and behavioral characteristics and decision-making style preferences of people at different adoption stages. Participants (N=1236) were recruited onsite within the cohort study Konstanz Life Study. Use of mobile devices and nutrition and fitness apps, 5 behavior adoption stages of using nutrition and fitness apps, preference for intuition and deliberation in eating decision-making (E-PID), healthy eating style, sociodemographic variables, and body mass index (BMI) were assessed. Analysis of the 5 behavior adoption stages showed that stage 1 ("unengaged") was the most prevalent motivational stage for both nutrition and fitness app use, with half of the participants stating that they had never thought about using a nutrition app (52.41%, 533/1017), whereas less than one-third stated they had never thought about using a fitness app (29.25%, 301/1029). "Unengaged" nonusers (stage 1) showed a higher preference for an intuitive decision-making style when making eating decisions, whereas those who were already "acting" (stage 4) showed a greater preference for a deliberative decision-making style (F 4,1012 =21.83, Pdigital interventions. This study highlights that new user groups might be better reached by apps designed to address a more intuitive

  6. Modelling job support, job fit, job role and job satisfaction for school of nursing sessional academic staff.

    Science.gov (United States)

    Cowin, Leanne S; Moroney, Robyn

    2018-01-01

    Sessional academic staff are an important part of nursing education. Increases in casualisation of the academic workforce continue and satisfaction with the job role is an important bench mark for quality curricula delivery and influences recruitment and retention. This study examined relations between four job constructs - organisation fit, organisation support, staff role and job satisfaction for Sessional Academic Staff at a School of Nursing by creating two path analysis models. A cross-sectional correlational survey design was utilised. Participants who were currently working as sessional or casual teaching staff members were invited to complete an online anonymous survey. The data represents a convenience sample of Sessional Academic Staff in 2016 at a large school of Nursing and Midwifery in Australia. After psychometric evaluation of each of the job construct measures in this study we utilised Structural Equation Modelling to better understand the relations of the variables. The measures used in this study were found to be both valid and reliable for this sample. Job support and job fit are positively linked to job satisfaction. Although the hypothesised model did not meet model fit standards, a new 'nested' model made substantive sense. This small study explored a new scale for measuring academic job role, and demonstrated how it promotes the constructs of job fit and job supports. All four job constructs are important in providing job satisfaction - an outcome that in turn supports staffing stability, retention, and motivation.

  7. A differential equation for the asymptotic fitness distribution in the Bak-Sneppen model with five species.

    Science.gov (United States)

    Schlemm, Eckhard

    2015-09-01

    The Bak-Sneppen model is an abstract representation of a biological system that evolves according to the Darwinian principles of random mutation and selection. The species in the system are characterized by a numerical fitness value between zero and one. We show that in the case of five species the steady-state fitness distribution can be obtained as a solution to a linear differential equation of order five with hypergeometric coefficients. Similar representations for the asymptotic fitness distribution in larger systems may help pave the way towards a resolution of the question of whether or not, in the limit of infinitely many species, the fitness is asymptotically uniformly distributed on the interval [fc, 1] with fc ≳ 2/3. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Permutation tests for goodness-of-fit testing of mathematical models to experimental data.

    Science.gov (United States)

    Fişek, M Hamit; Barlas, Zeynep

    2013-03-01

    This paper presents statistical procedures for improving the goodness-of-fit testing of theoretical models to data obtained from laboratory experiments. We use an experimental study in the expectation states research tradition which has been carried out in the "standardized experimental situation" associated with the program to illustrate the application of our procedures. We briefly review the expectation states research program and the fundamentals of resampling statistics as we develop our procedures in the resampling context. The first procedure we develop is a modification of the chi-square test which has been the primary statistical tool for assessing goodness of fit in the EST research program, but has problems associated with its use. We discuss these problems and suggest a procedure to overcome them. The second procedure we present, the "Average Absolute Deviation" test, is a new test and is proposed as an alternative to the chi square test, as being simpler and more informative. The third and fourth procedures are permutation versions of Jonckheere's test for ordered alternatives, and Kendall's tau(b), a rank order correlation coefficient. The fifth procedure is a new rank order goodness-of-fit test, which we call the "Deviation from Ideal Ranking" index, which we believe may be more useful than other rank order tests for assessing goodness-of-fit of models to experimental data. The application of these procedures to the sample data is illustrated in detail. We then present another laboratory study from an experimental paradigm different from the expectation states paradigm - the "network exchange" paradigm, and describe how our procedures may be applied to this data set. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. THE HERSCHEL ORION PROTOSTAR SURVEY: SPECTRAL ENERGY DISTRIBUTIONS AND FITS USING A GRID OF PROTOSTELLAR MODELS

    Energy Technology Data Exchange (ETDEWEB)

    Furlan, E. [Infrared Processing and Analysis Center, California Institute of Technology, 770 S. Wilson Ave., Pasadena, CA 91125 (United States); Fischer, W. J. [Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771 (United States); Ali, B. [Space Science Institute, 4750 Walnut Street, Boulder, CO 80301 (United States); Stutz, A. M. [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Stanke, T. [ESO, Karl-Schwarzschild-Strasse 2, D-85748 Garching bei München (Germany); Tobin, J. J. [National Radio Astronomy Observatory, Charlottesville, VA 22903 (United States); Megeath, S. T.; Booker, J. [Ritter Astrophysical Research Center, Department of Physics and Astronomy, University of Toledo, 2801 W. Bancroft Street, Toledo, OH 43606 (United States); Osorio, M. [Instituto de Astrofísica de Andalucía, CSIC, Camino Bajo de Huétor 50, E-18008 Granada (Spain); Hartmann, L.; Calvet, N. [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States); Poteet, C. A. [New York Center for Astrobiology, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY 12180 (United States); Manoj, P. [Department of Astronomy and Astrophysics, Tata Institute of Fundamental Research, Homi Bhabha Road, Colaba, Mumbai 400005 (India); Watson, D. M. [Department of Physics and Astronomy, University of Rochester, Rochester, NY 14627 (United States); Allen, L., E-mail: furlan@ipac.caltech.edu [National Optical Astronomy Observatory, 950 N. Cherry Avenue, Tucson, AZ 85719 (United States)

    2016-05-01

    We present key results from the Herschel Orion Protostar Survey: spectral energy distributions (SEDs) and model fits of 330 young stellar objects, predominantly protostars, in the Orion molecular clouds. This is the largest sample of protostars studied in a single, nearby star formation complex. With near-infrared photometry from 2MASS, mid- and far-infrared data from Spitzer and Herschel , and submillimeter photometry from APEX, our SEDs cover 1.2–870 μ m and sample the peak of the protostellar envelope emission at ∼100 μ m. Using mid-IR spectral indices and bolometric temperatures, we classify our sample into 92 Class 0 protostars, 125 Class I protostars, 102 flat-spectrum sources, and 11 Class II pre-main-sequence stars. We implement a simple protostellar model (including a disk in an infalling envelope with outflow cavities) to generate a grid of 30,400 model SEDs and use it to determine the best-fit model parameters for each protostar. We argue that far-IR data are essential for accurate constraints on protostellar envelope properties. We find that most protostars, and in particular the flat-spectrum sources, are well fit. The median envelope density and median inclination angle decrease from Class 0 to Class I to flat-spectrum protostars, despite the broad range in best-fit parameters in each of the three categories. We also discuss degeneracies in our model parameters. Our results confirm that the different protostellar classes generally correspond to an evolutionary sequence with a decreasing envelope infall rate, but the inclination angle also plays a role in the appearance, and thus interpretation, of the SEDs.

  10. Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

    Science.gov (United States)

    Nabizadeh, Nooshin; John, Nigel

    2014-03-01

    Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

  11. Anticipating mismatches of HIT investments: Developing a viability-fit model for e-health services.

    Science.gov (United States)

    Mettler, Tobias

    2016-01-01

    Albeit massive investments in the recent years, the impact of health information technology (HIT) has been controversial and strongly disputed by both research and practice. While many studies are concerned with the development of new or the refinement of existing measurement models for assessing the impact of HIT adoption (ex post), this study presents an initial attempt to better understand the factors affecting viability and fit of HIT and thereby underscores the importance of also having instruments for managing expectations (ex ante). We extend prior research by undertaking a more granular investigation into the theoretical assumptions of viability and fit constructs. In doing so, we use a mixed-methods approach, conducting qualitative focus group discussions and a quantitative field study to improve and validate a viability-fit measurement instrument. Our findings suggest two issues for research and practice. First, the results indicate that different stakeholders perceive HIT viability and fit of the same e-health services very unequally. Second, the analysis also demonstrates that there can be a great discrepancy between the organizational viability and individual fit of a particular e-health service. The findings of this study have a number of important implications such as for health policy making, HIT portfolios, and stakeholder communication. Copyright © 2015. Published by Elsevier Ireland Ltd.

  12. Relationships among Classical Test Theory and Item Response Theory Frameworks via Factor Analytic Models

    Science.gov (United States)

    Kohli, Nidhi; Koran, Jennifer; Henn, Lisa

    2015-01-01

    There are well-defined theoretical differences between the classical test theory (CTT) and item response theory (IRT) frameworks. It is understood that in the CTT framework, person and item statistics are test- and sample-dependent. This is not the perception with IRT. For this reason, the IRT framework is considered to be theoretically superior…

  13. Amino acids intake and physical fitness among adolescents.

    Science.gov (United States)

    Gracia-Marco, Luis; Bel-Serrat, Silvia; Cuenca-Garcia, Magdalena; Gonzalez-Gross, Marcela; Pedrero-Chamizo, Raquel; Manios, Yannis; Marcos, Ascensión; Molnar, Denes; Widhalm, Kurt; Polito, Angela; Vanhelst, Jeremy; Hagströmer, Maria; Sjöström, Michael; Kafatos, Anthony; de Henauw, Stefaan; Gutierrez, Ángel; Castillo, Manuel J; Moreno, Luis A

    2017-06-01

    The aim was to investigate whether there was an association between amino acid (AA) intake and physical fitness and if so, to assess whether this association was independent of carbohydrates intake. European adolescents (n = 1481, 12.5-17.5 years) were measured. Intake was assessed via two non-consecutive 24-h dietary recalls. Lower and upper limbs muscular fitness was assessed by standing long jump and handgrip strength tests, respectively. Cardiorespiratory fitness was assessed by the 20-m shuttle run test. Physical activity was objectively measured. Socioeconomic status was obtained via questionnaires. Lower limbs muscular fitness seems to be positively associated with tryptophan, histidine and methionine intake in boys, regardless of centre, age, socioeconomic status, physical activity and total energy intake (model 1). However, these associations disappeared once carbohydrates intake was controlled for (model 2). In girls, only proline intake seems to be positively associated with lower limbs muscular fitness (model 2) while cardiorespiratory fitness seems to be positively associated with leucine (model 1) and proline intake (models 1 and 2). None of the observed significant associations remained significant once multiple testing was controlled for. In conclusion, we failed to detect any associations between any of the evaluated AAs and physical fitness after taking into account the effect of multiple testing.

  14. Fitting the two-compartment model in DCE-MRI by linear inversion.

    Science.gov (United States)

    Flouri, Dimitra; Lesnic, Daniel; Sourbron, Steven P

    2016-09-01

    Model fitting of dynamic contrast-enhanced-magnetic resonance imaging-MRI data with nonlinear least squares (NLLS) methods is slow and may be biased by the choice of initial values. The aim of this study was to develop and evaluate a linear least squares (LLS) method to fit the two-compartment exchange and -filtration models. A second-order linear differential equation for the measured concentrations was derived where model parameters act as coefficients. Simulations of normal and pathological data were performed to determine calculation time, accuracy and precision under different noise levels and temporal resolutions. Performance of the LLS was evaluated by comparison against the NLLS. The LLS method is about 200 times faster, which reduces the calculation times for a 256 × 256 MR slice from 9 min to 3 s. For ideal data with low noise and high temporal resolution the LLS and NLLS were equally accurate and precise. The LLS was more accurate and precise than the NLLS at low temporal resolution, but less accurate at high noise levels. The data show that the LLS leads to a significant reduction in calculation times, and more reliable results at low noise levels. At higher noise levels the LLS becomes exceedingly inaccurate compared to the NLLS, but this may be improved using a suitable weighting strategy. Magn Reson Med 76:998-1006, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  15. The regression-calibration method for fitting generalized linear models with additive measurement error

    OpenAIRE

    James W. Hardin; Henrik Schmeidiche; Raymond J. Carroll

    2003-01-01

    This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on s...

  16. Econometric modelling of risk adverse behaviours of entrepreneurs in the provision of house fittings in China

    Directory of Open Access Journals (Sweden)

    Rita Yi Man Li

    2012-03-01

    Full Text Available Entrepreneurs have always born the risk of running their business. They reap a profit in return for their risk taking and work. Housing developers are no different. In many countries, such as Australia, the United Kingdom and the United States, they interpret the tastes of the buyers and provide the dwellings they develop with basic fittings such as floor and wall coverings, bathroom fittings and kitchen cupboards. In mainland China, however, in most of the developments, units or houses are sold without floor or wall coverings, kitchen  or bathroom fittings. What is the motive behind this choice? This paper analyses the factors affecting housing developers’ decisions to provide fittings based on 1701 housing developments in Hangzhou, Chongqing and Hangzhou using a Probit model. The results show that developers build a higher proportion of bare units in mainland China when: 1 there is shortage of housing; 2 land costs are high so that the comparative costs of providing fittings become relatively low.

  17. FIREFLY (Fitting IteRativEly For Likelihood analYsis): a full spectral fitting code

    Science.gov (United States)

    Wilkinson, David M.; Maraston, Claudia; Goddard, Daniel; Thomas, Daniel; Parikh, Taniya

    2017-12-01

    We present a new spectral fitting code, FIREFLY, for deriving the stellar population properties of stellar systems. FIREFLY is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting process controlled by the Bayesian information criterion. No priors are applied, rather all solutions within a statistical cut are retained with their weight. Moreover, no additive or multiplicative polynomials are employed to adjust the spectral shape. This fitting freedom is envisaged in order to map out the effect of intrinsic spectral energy distribution degeneracies, such as age, metallicity, dust reddening on galaxy properties, and to quantify the effect of varying input model components on such properties. Dust attenuation is included using a new procedure, which was tested on Integral Field Spectroscopic data in a previous paper. The fitting method is extensively tested with a comprehensive suite of mock galaxies, real galaxies from the Sloan Digital Sky Survey and Milky Way globular clusters. We also assess the robustness of the derived properties as a function of signal-to-noise ratio (S/N) and adopted wavelength range. We show that FIREFLY is able to recover age, metallicity, stellar mass, and even the star formation history remarkably well down to an S/N ∼ 5, for moderately dusty systems. Code and results are publicly available.1

  18. FITTING OF PARAMETRIC BUILDING MODELS TO OBLIQUE AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    U. S. Panday

    2012-09-01

    Full Text Available In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of – 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for

  19. Fitting the Probability Distribution Functions to Model Particulate Matter Concentrations

    International Nuclear Information System (INIS)

    El-Shanshoury, Gh.I.

    2017-01-01

    The main objective of this study is to identify the best probability distribution and the plotting position formula for modeling the concentrations of Total Suspended Particles (TSP) as well as the Particulate Matter with an aerodynamic diameter<10 μm (PM 10 ). The best distribution provides the estimated probabilities that exceed the threshold limit given by the Egyptian Air Quality Limit value (EAQLV) as well the number of exceedance days is estimated. The standard limits of the EAQLV for TSP and PM 10 concentrations are 24-h average of 230 μg/m 3 and 70 μg/m 3 , respectively. Five frequency distribution functions with seven formula of plotting positions (empirical cumulative distribution functions) are compared to fit the average of daily TSP and PM 10 concentrations in year 2014 for Ain Sokhna city. The Quantile-Quantile plot (Q-Q plot) is used as a method for assessing how closely a data set fits a particular distribution. A proper probability distribution that represents the TSP and PM 10 has been chosen based on the statistical performance indicator values. The results show that Hosking and Wallis plotting position combined with Frechet distribution gave the highest fit for TSP and PM 10 concentrations. Burr distribution with the same plotting position follows Frechet distribution. The exceedance probability and days over the EAQLV are predicted using Frechet distribution. In 2014, the exceedance probability and days for TSP concentrations are 0.052 and 19 days, respectively. Furthermore, the PM 10 concentration is found to exceed the threshold limit by 174 days

  20. Using geometry to improve model fitting and experiment design for glacial isostasy

    Science.gov (United States)

    Kachuck, S. B.; Cathles, L. M.

    2017-12-01

    As scientists we routinely deal with models, which are geometric objects at their core - the manifestation of a set of parameters as predictions for comparison with observations. When the number of observations exceeds the number of parameters, the model is a hypersurface (the model manifold) in the space of all possible predictions. The object of parameter fitting is to find the parameters corresponding to the point on the model manifold as close to the vector of observations as possible. But the geometry of the model manifold can make this difficult. By curving, ending abruptly (where, for instance, parameters go to zero or infinity), and by stretching and compressing the parameters together in unexpected directions, it can be difficult to design algorithms that efficiently adjust the parameters. Even at the optimal point on the model manifold, parameters might not be individually resolved well enough to be applied to new contexts. In our context of glacial isostatic adjustment, models of sparse surface observations have a broad spread of sensitivity to mixtures of the earth's viscous structure and the surface distribution of ice over the last glacial cycle. This impedes precise statements about crucial geophysical processes, such as the planet's thermal history or the climates that controlled the ice age. We employ geometric methods developed in the field of systems biology to improve the efficiency of fitting (geodesic accelerated Levenberg-Marquardt) and to identify the maximally informative sources of additional data to make better predictions of sea levels and ice configurations (optimal experiment design). We demonstrate this in particular in reconstructions of the Barents Sea Ice Sheet, where we show that only certain kinds of data from the central Barents have the power to distinguish between proposed models.

  1. Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis.

    Science.gov (United States)

    Novakovic, A M; Krekels, E H J; Munafo, A; Ueckert, S; Karlsson, M O

    2017-01-01

    In this study, we report the development of the first item response theory (IRT) model within a pharmacometrics framework to characterize the disease progression in multiple sclerosis (MS), as measured by Expanded Disability Status Score (EDSS). Data were collected quarterly from a 96-week phase III clinical study by a blinder rater, involving 104,206 item-level observations from 1319 patients with relapsing-remitting MS (RRMS), treated with placebo or cladribine. Observed scores for each EDSS item were modeled describing the probability of a given score as a function of patients' (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time, and the model was then extended to cladribine arms to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. The IRT model was able to describe baseline and longitudinal EDSS data on item and total level. The final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of eight items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modeling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner.

  2. vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments

    Directory of Open Access Journals (Sweden)

    Demeter Lisa

    2010-05-01

    Full Text Available Abstract Background The replication rate (or fitness between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV. HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness. Results Based on a mathematical model and several statistical methods (least-squares approach and measurement error models, a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1. Conclusions Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at http://bis.urmc.rochester.edu/vFitness/.

  3. Fitted Hanbury-Brown Twiss radii versus space-time variances in flow-dominated models

    Science.gov (United States)

    Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

    2006-04-01

    The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.

  4. Fitted Hanbury-Brown-Twiss radii versus space-time variances in flow-dominated models

    International Nuclear Information System (INIS)

    Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

    2006-01-01

    The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown-Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data

  5. Worm plot to diagnose fit in quantile regression

    NARCIS (Netherlands)

    Buuren, S. van

    2007-01-01

    The worm plot is a series of detrended Q-Q plots, split by covariate levels. The worm plot is a diagnostic tool for visualizing how well a statistical model fits the data, for finding locations at which the fit can be improved, and for comparing the fit of different models. This paper shows how the

  6. Worm plot to diagnose fit in quantile regression

    NARCIS (Netherlands)

    Buuren, S. van

    2007-01-01

    The worm plot is a series of detrended Q-Q plots, split by covariate levels. The worm plot is a diagnostic tool for visualizing how well a statistical model fits the data, for finding locations at which the fit can be improved, and for comparing the fit of different models. This paper shows how

  7. Development and Analysis of Volume Multi-Sphere Method Model Generation using Electric Field Fitting

    Science.gov (United States)

    Ingram, G. J.

    Electrostatic modeling of spacecraft has wide-reaching applications such as detumbling space debris in the Geosynchronous Earth Orbit regime before docking, servicing and tugging space debris to graveyard orbits, and Lorentz augmented orbits. The viability of electrostatic actuation control applications relies on faster-than-realtime characterization of the electrostatic interaction. The Volume Multi-Sphere Method (VMSM) seeks the optimal placement and radii of a small number of equipotential spheres to accurately model the electrostatic force and torque on a conducting space object. Current VMSM models tuned using force and torque comparisons with commercially available finite element software are subject to the modeled probe size and numerical errors of the software. This work first investigates fitting of VMSM models to Surface-MSM (SMSM) generated electrical field data, removing modeling dependence on probe geometry while significantly increasing performance and speed. A proposed electric field matching cost function is compared to a force and torque cost function, the inclusion of a self-capacitance constraint is explored and 4 degree-of-freedom VMSM models generated using electric field matching are investigated. The resulting E-field based VMSM development framework is illustrated on a box-shaped hub with a single solar panel, and convergence properties of select models are qualitatively analyzed. Despite the complex non-symmetric spacecraft geometry, elegantly simple 2-sphere VMSM solutions provide force and torque fits within a few percent.

  8. Prediction of Pressing Quality for Press-Fit Assembly Based on Press-Fit Curve and Maximum Press-Mounting Force

    Directory of Open Access Journals (Sweden)

    Bo You

    2015-01-01

    Full Text Available In order to predict pressing quality of precision press-fit assembly, press-fit curves and maximum press-mounting force of press-fit assemblies were investigated by finite element analysis (FEA. The analysis was based on a 3D Solidworks model using the real dimensions of the microparts and the subsequent FEA model that was built using ANSYS Workbench. The press-fit process could thus be simulated on the basis of static structure analysis. To verify the FEA results, experiments were carried out using a press-mounting apparatus. The results show that the press-fit curves obtained by FEA agree closely with the curves obtained using the experimental method. In addition, the maximum press-mounting force calculated by FEA agrees with that obtained by the experimental method, with the maximum deviation being 4.6%, a value that can be tolerated. The comparison shows that the press-fit curve and max press-mounting force calculated by FEA can be used for predicting the pressing quality during precision press-fit assembly.

  9. Direct fit of a theoretical model of phase transition in oscillatory finger motions.

    NARCIS (Netherlands)

    Newell, K.M.; Molenaar, P.C.M.

    2003-01-01

    This paper presents a general method to fit the Schoner-Haken-Kelso (SHK) model of human movement phase transitions directly to time series data. A robust variant of the extended Kalman filter technique is applied to the data of a single subject. The options of covariance resetting and iteration

  10. The SF-8 Spanish Version for Health-Related Quality of Life Assessment: Psychometric Study with IRT and CFA Models.

    Science.gov (United States)

    Tomás, José M; Galiana, Laura; Fernández, Irene

    2018-03-22

    The aim of current research is to analyze the psychometric properties of the Spanish version of the SF-8, overcoming previous shortcomings. A double line of analyses was used: competitive structural equations models to establish factorial validity, and Item Response theory to analyze item psychometric characteristics and information. 593 people aged 60 years or older, attending long life learning programs at the University were surveyed. Their age ranged from 60 to 92 years old. 67.6% were women. The survey included scales on personality dimensions, attitudes, perceptions, and behaviors related to aging. Competitive confirmatory models pointed out two-factors (physical and mental health) as the best representation of the data: χ2(13) = 72.37 (p < .01); CFI = .99; TLI = .98; RMSEA = .08 (.06, .10). Item 5 was removed because of unreliability and cross-loading. Graded response models showed appropriate fit for two-parameter logistic model both the physical and the mental dimensions. Item Information Curves and Test Information Functions pointed out that the SF-8 was more informative for low levels of health. The Spanish SF-8 has adequate psychometric properties, being better represented by two dimensions, once Item 5 is removed. Gathering evidence on patient-reported outcome measures is of crucial importance, as this type of measurement instruments are increasingly used in clinical arena.

  11. Complex growing networks with intrinsic vertex fitness

    International Nuclear Information System (INIS)

    Bedogne, C.; Rodgers, G. J.

    2006-01-01

    One of the major questions in complex network research is to identify the range of mechanisms by which a complex network can self organize into a scale-free state. In this paper we investigate the interplay between a fitness linking mechanism and both random and preferential attachment. In our models, each vertex is assigned a fitness x, drawn from a probability distribution ρ(x). In Model A, at each time step a vertex is added and joined to an existing vertex, selected at random, with probability p and an edge is introduced between vertices with fitnesses x and y, with a rate f(x,y), with probability 1-p. Model B differs from Model A in that, with probability p, edges are added with preferential attachment rather than randomly. The analysis of Model A shows that, for every fixed fitness x, the network's degree distribution decays exponentially. In Model B we recover instead a power-law degree distribution whose exponent depends only on p, and we show how this result can be generalized. The properties of a number of particular networks are examined

  12. Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

    Science.gov (United States)

    Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

    2016-05-01

    Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

  13. Measuring Quasar Spin via X-ray Continuum Fitting

    Science.gov (United States)

    Jenkins, Matthew; Pooley, David; Rappaport, Saul; Steiner, Jack

    2018-01-01

    We have identified several quasars whose X-ray spectra appear very soft. When fit with power-law models, the best-fit indices are greater than 3. This is very suggestive of thermal disk emission, indicating that the X-ray spectrum is dominated by the disk component. Galactic black hole binaries in such states have been successfully fit with disk-blackbody models to constrain the inner radius, which also constrains the spin of the black hole. We have fit those models to XMM-Newton spectra of several of our identified soft X-ray quasars to place constraints on the spins of the supermassive black holes.

  14. RATES OF FITNESS DECLINE AND REBOUND SUGGEST PERVASIVE EPISTASIS

    Science.gov (United States)

    Perfeito, L; Sousa, A; Bataillon, T; Gordo, I

    2014-01-01

    Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS− E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models. PMID:24372601

  15. The Impact of Varied Discrimination Parameters on Mixed-Format Item Response Theory Model Selection

    Science.gov (United States)

    Whittaker, Tiffany A.; Chang, Wanchen; Dodd, Barbara G.

    2013-01-01

    Whittaker, Chang, and Dodd compared the performance of model selection criteria when selecting among mixed-format IRT models and found that the criteria did not perform adequately when selecting the more parameterized models. It was suggested by M. S. Johnson that the problems when selecting the more parameterized models may be because of the low…

  16. Fitting model-based psychometric functions to simultaneity and temporal-order judgment data: MATLAB and R routines.

    Science.gov (United States)

    Alcalá-Quintana, Rocío; García-Pérez, Miguel A

    2013-12-01

    Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.

  17. Nirex methodology for scenario and conceptual model development. An international peer review

    International Nuclear Information System (INIS)

    1999-06-01

    Nirex has responsibilities for nuclear waste management in the UK. The company's top level objectives are to maintain technical credibility on deep disposal, to gain public acceptance for a deep geologic repository, and to provide relevant advice to customers on the safety implications of their waste packaging proposals. Nirex utilizes peer reviews as appropriate to keep its scientific tools up-to-date and to periodically verify the quality of its products. The NEA formed an International Review Team (IRT) consisting of four internationally recognised experts plus a member of the NEA Secretariat. The IRT performed an in-depth analysis of five Nirex scientific reports identified in the terms of reference of the review. The review was to primarily judge whether the Nirex methodology provides an adequate framework to support the building of a future licensing safety case. Another objective was to judge whether the methodology could aid in establishing a better understanding, and, ideally, enhance acceptance of a repository among stakeholders. Methodologies for conducting safety assessments include at a very basic level the identification of features, events, and processes (FEPs) relevant to the system at hand, their convolution in scenarios for analysis, and the formulation of conceptual models to be addressed through numerical modelling. The main conclusion of the IRT is that Nirex has developed a potentially sound methodology for the identification and analysis of FEPs and for the identification of conceptual model needs and model requirements. The work is still in progress and is not yet complete. (R.P.)

  18. Fitness

    Science.gov (United States)

    ... gov home http://www.girlshealth.gov/ Home Fitness Fitness Want to look and feel your best? Physical ... are? Check out this info: What is physical fitness? top Physical fitness means you can do everyday ...

  19. A Bifactor Multidimensional Item Response Theory Model for Differential Item Functioning Analysis on Testlet-Based Items

    Science.gov (United States)

    Fukuhara, Hirotaka; Kamata, Akihito

    2011-01-01

    A differential item functioning (DIF) detection method for testlet-based data was proposed and evaluated in this study. The proposed DIF model is an extension of a bifactor multidimensional item response theory (MIRT) model for testlets. Unlike traditional item response theory (IRT) DIF models, the proposed model takes testlet effects into…

  20. Development and psychometric characteristics of the SCI-QOL Bladder Management Difficulties and Bowel Management Difficulties item banks and short forms and the SCI-QOL Bladder Complications scale.

    Science.gov (United States)

    Tulsky, David S; Kisala, Pamela A; Tate, Denise G; Spungen, Ann M; Kirshblum, Steven C

    2015-05-01

    To describe the development and psychometric properties of the Spinal Cord Injury--Quality of Life (SCI-QOL) Bladder Management Difficulties and Bowel Management Difficulties item banks and Bladder Complications scale. Using a mixed-methods design, a pool of items assessing bladder and bowel-related concerns were developed using focus groups with individuals with spinal cord injury (SCI) and SCI clinicians, cognitive interviews, and item response theory (IRT) analytic approaches, including tests of model fit and differential item functioning. Thirty-eight bladder items and 52 bowel items were tested at the University of Michigan, Kessler Foundation Research Center, the Rehabilitation Institute of Chicago, the University of Washington, Craig Hospital, and the James J. Peters VA Medical Center, Bronx, NY. Seven hundred fifty-seven adults with traumatic SCI. The final item banks demonstrated unidimensionality (Bladder Management Difficulties CFI=0.965; RMSEA=0.093; Bowel Management Difficulties CFI=0.955; RMSEA=0.078) and acceptable fit to a graded response IRT model. The final calibrated Bladder Management Difficulties bank includes 15 items, and the final Bowel Management Difficulties item bank consists of 26 items. Additionally, 5 items related to urinary tract infections (UTI) did not fit with the larger Bladder Management Difficulties item bank but performed relatively well independently (CFI=0.992, RMSEA=0.050) and were thus retained as a separate scale. The SCI-QOL Bladder Management Difficulties and Bowel Management Difficulties item banks are psychometrically robust and are available as computer adaptive tests or short forms. The SCI-QOL Bladder Complications scale is a brief, fixed-length outcomes instrument for individuals with a UTI.

  1. Hamiltonian inclusive fitness: a fitter fitness concept.

    Science.gov (United States)

    Costa, James T

    2013-01-01

    In 1963-1964 W. D. Hamilton introduced the concept of inclusive fitness, the only significant elaboration of Darwinian fitness since the nineteenth century. I discuss the origin of the modern fitness concept, providing context for Hamilton's discovery of inclusive fitness in relation to the puzzle of altruism. While fitness conceptually originates with Darwin, the term itself stems from Spencer and crystallized quantitatively in the early twentieth century. Hamiltonian inclusive fitness, with Price's reformulation, provided the solution to Darwin's 'special difficulty'-the evolution of caste polymorphism and sterility in social insects. Hamilton further explored the roles of inclusive fitness and reciprocation to tackle Darwin's other difficulty, the evolution of human altruism. The heuristically powerful inclusive fitness concept ramified over the past 50 years: the number and diversity of 'offspring ideas' that it has engendered render it a fitter fitness concept, one that Darwin would have appreciated.

  2. Fitting the Phenomenological MSSM

    CERN Document Server

    AbdusSalam, S S; Quevedo, F; Feroz, F; Hobson, M

    2010-01-01

    We perform a global Bayesian fit of the phenomenological minimal supersymmetric standard model (pMSSM) to current indirect collider and dark matter data. The pMSSM contains the most relevant 25 weak-scale MSSM parameters, which are simultaneously fit using `nested sampling' Monte Carlo techniques in more than 15 years of CPU time. We calculate the Bayesian evidence for the pMSSM and constrain its parameters and observables in the context of two widely different, but reasonable, priors to determine which inferences are robust. We make inferences about sparticle masses, the sign of the $\\mu$ parameter, the amount of fine tuning, dark matter properties and the prospects for direct dark matter detection without assuming a restrictive high-scale supersymmetry breaking model. We find the inferred lightest CP-even Higgs boson mass as an example of an approximately prior independent observable. This analysis constitutes the first statistically convergent pMSSM global fit to all current data.

  3. CRAPONE, Optical Model Potential Fit of Neutron Scattering Data

    International Nuclear Information System (INIS)

    Fabbri, F.; Fratamico, G.; Reffo, G.

    2004-01-01

    1 - Description of problem or function: Automatic search for local and non-local optical potential parameters for neutrons. Total, elastic, differential elastic cross sections, l=0 and l=1 strength functions and scattering length can be considered. 2 - Method of solution: A fitting procedure is applied to different sets of experimental data depending on the local or non-local approximation chosen. In the non-local approximation the fitting procedure can be simultaneously performed over the whole energy range. The best fit is obtained when a set of parameters is found where CHI 2 is at its minimum. The solution of the system equations is obtained by diagonalization of the matrix according to the Jacobi method

  4. State Authenticity as Fit to Environment: The Implications of Social Identity for Fit, Authenticity, and Self-Segregation.

    Science.gov (United States)

    Schmader, Toni; Sedikides, Constantine

    2017-10-01

    People seek out situations that "fit," but the concept of fit is not well understood. We introduce State Authenticity as Fit to the Environment (SAFE), a conceptual framework for understanding how social identities motivate the situations that people approach or avoid. Drawing from but expanding the authenticity literature, we first outline three types of person-environment fit: self-concept fit, goal fit, and social fit. Each type of fit, we argue, facilitates cognitive fluency, motivational fluency, and social fluency that promote state authenticity and drive approach or avoidance behaviors. Using this model, we assert that contexts subtly signal social identities in ways that implicate each type of fit, eliciting state authenticity for advantaged groups but state inauthenticity for disadvantaged groups. Given that people strive to be authentic, these processes cascade down to self-segregation among social groups, reinforcing social inequalities. We conclude by mapping out directions for research on relevant mechanisms and boundary conditions.

  5. Determination of the heat transfer coefficient from IRT measurement data using the Trefftz method

    Directory of Open Access Journals (Sweden)

    Maciejewska Beata

    2016-01-01

    Full Text Available The paper presents the method of heat transfer coefficient determination for boiling research during FC-72 flow in the minichannels, each 1.7 mm deep, 24 mm wide and 360 mm long. The heating element was the thin foil, enhanced on the side which comes into contact with fluid in the minichannels. Local values of the heat transfer coefficient were calculated from the Robin boundary condition. The foil temperature distribution and the derivative of the foil temperature were obtained by solving the two-dimensional inverse heat conduction problem, due to measurements obtained by IRT. Calculations was carried out by the method based on the approximation of the solution of the problem using a linear combination of Trefftz functions. The basic property of this functions is they satisfy the governing equation. Unknown coefficients of linear combination of Trefftz functions are calculated from the minimization of the functional that expresses the mean square error of the approximate solution on the boundary. The results presented as IR thermographs, two-phase flow structure images and the heat transfer coefficient as a function of the distance from the channel inlet, were analyzed.

  6. Fit-for-purpose: species distribution model performance depends on evaluation criteria - Dutch Hoverflies as a case study.

    Science.gov (United States)

    Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C

    2013-01-01

    Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data

  7. Partially Observed Mixtures of IRT Models: An Extension of the Generalized Partial-Credit Model

    Science.gov (United States)

    Von Davier, Matthias; Yamamoto, Kentaro

    2004-01-01

    The generalized partial-credit model (GPCM) is used frequently in educational testing and in large-scale assessments for analyzing polytomous data. Special cases of the generalized partial-credit model are the partial-credit model--or Rasch model for ordinal data--and the two parameter logistic (2PL) model. This article extends the GPCM to the…

  8. Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

    Science.gov (United States)

    Mandal, S.; Choudhury, B. U.

    2015-07-01

    Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

  9. Testing the goodness of fit of selected infiltration models on soils with different land use histories

    International Nuclear Information System (INIS)

    Mbagwu, J.S.C.

    1993-10-01

    Six infiltration models, some obtained by reformulating the fitting parameters of the classical Kostiakov (1932) and Philip (1957) equations, were investigated for their ability to describe water infiltration into highly permeable sandy soils from the Nsukka plains of SE Nigeria. The models were Kostiakov, Modified Kostiakov (A), Modified Kostiakov (B), Philip, Modified Philip (A) and Modified Philip (B). Infiltration data were obtained from double ring infiltrometers on field plots established on a Knadic Paleustult (Nkpologu series) to investigate the effects of land use on soil properties and maize yield. The treatments were; (i) tilled-mulched (TM), (ii) tilled-unmulched (TU), (iii) untilled-mulched (UM), (iv) untilled-unmulched (UU) and (v) continuous pasture (CP). Cumulative infiltration was highest on the TM and lowest on the CP plots. All estimated model parameters obtained by the best fit of measured data differed significantly among the treatments. Based on the magnitude of R 2 values, the Kostiakov, Modified Kostiakov (A), Philip and Modified Philip (A) models provided best predictions of cumulative infiltration as a function of time. Comparing experimental with model-predicted cumulative infiltration showed, however, that on all treatments the values predicted by the classical Kostiakov, Philip and Modified Philip (A) models deviated most from experimental data. The other models produced values that agreed very well with measured data. Considering the eases of determining the fitting parameters it is proposed that on soils with high infiltration rates, either Modified Kostiakov model (I = Kt a + Ict) or Modified Philip model (I St 1/2 + Ict), (where I is cumulative infiltration, K, the time coefficient, t, time elapsed, 'a' the time exponent, Ic the equilibrium infiltration rate and S, the soil water sorptivity), be used for routine characterization of the infiltration process. (author). 33 refs, 3 figs 6 tabs

  10. A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

    Science.gov (United States)

    Zhai, Xuetong; Chakraborty, Dev P

    2017-06-01

    The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics

  11. Building Customer Churn Prediction Models in Fitness Industry with Machine Learning Methods

    OpenAIRE

    Shan, Min

    2017-01-01

    With the rapid growth of digital systems, churn management has become a major focus within customer relationship management in many industries. Ample research has been conducted for churn prediction in different industries with various machine learning methods. This thesis aims to combine feature selection and supervised machine learning methods for defining models of churn prediction and apply them on fitness industry. Forward selection is chosen as feature selection methods. Support Vector ...

  12. Different fits satisfy different needs: linking person-environment fit to employee commitment and performance using self-determination theory.

    Science.gov (United States)

    Greguras, Gary J; Diefendorff, James M

    2009-03-01

    Integrating and expanding upon the person-environment fit (PE fit) and the self-determination theory literatures, the authors hypothesized and tested a model in which the satisfaction of the psychological needs for autonomy, relatedness, and competence partially mediated the relations between different types of perceived PE fit (i.e., person-organization fit, person-group fit, and job demands-abilities fit) with employee affective organizational commitment and overall job performance. Data from 163 full-time working employees and their supervisors were collected across 3 time periods. Results indicate that different types of PE fit predicted different types of psychological need satisfaction and that psychological need satisfaction predicted affective commitment and performance. Further, person-organization fit and demands-abilities fit also evidenced direct effects on employee affective commitment. These results begin to explicate the processes through which different types of PE fit relate to employee attitudes and behaviors. (c) 2009 APA, all rights reserved.

  13. Fit reduced GUTS models online: From theory to practice.

    Science.gov (United States)

    Baudrot, Virgile; Veber, Philippe; Gence, Guillaume; Charles, Sandrine

    2018-05-20

    Mechanistic modeling approaches, such as the toxicokinetic-toxicodynamic (TKTD) framework, are promoted by international institutions such as the European Food Safety Authority and the Organization for Economic Cooperation and Development to assess the environmental risk of chemical products generated by human activities. TKTD models can encompass a large set of mechanisms describing the kinetics of compounds inside organisms (e.g., uptake and elimination) and their effect at the level of individuals (e.g., damage accrual, recovery, and death mechanism). Compared to classical dose-response models, TKTD approaches have many advantages, including accounting for temporal aspects of exposure and toxicity, considering data points all along the experiment and not only at the end, and making predictions for untested situations as realistic exposure scenarios. Among TKTD models, the general unified threshold model of survival (GUTS) is within the most recent and innovative framework but is still underused in practice, especially by risk assessors, because specialist programming and statistical skills are necessary to run it. Making GUTS models easier to use through a new module freely available from the web platform MOSAIC (standing for MOdeling and StAtistical tools for ecotoxIClogy) should promote GUTS operability in support of the daily work of environmental risk assessors. This paper presents the main features of MOSAIC_GUTS: uploading of the experimental data, GUTS fitting analysis, and LCx estimates with their uncertainty. These features will be exemplified from literature data. Integr Environ Assess Manag 2018;00:000-000. © 2018 SETAC. © 2018 SETAC.

  14. Markov Decision Process Measurement Model.

    Science.gov (United States)

    LaMar, Michelle M

    2018-03-01

    Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.

  15. Strategy for Sustainable Utilization of IRT-Sofia Research Reactor

    International Nuclear Information System (INIS)

    Mitev, M.; Apostolov, T.; Ilieva, K.; Belousov, S.; Nonova, T.

    2013-01-01

    The Research Reactor IRT-2000 in Sofia is in process of reconstruction into a low-power reactor of 200 kW under the decision of the Council of Ministers of Republic of Bulgaria from 2001. The reactor will be utilized for development and preservation of nuclear science, skills, and knowledge; implementation of applied methods and research; education of students and training of graduated physicists and engineers in the field of nuclear science and nuclear energy; development of radiation therapy facility. Nuclear energy has a strategic place within the structure of the country’s energy system. In that aspect, the research reactor as a material base, and its scientific and technical personnel, represent a solid basis for the development of nuclear energy in our country. The acquired scientific experience and qualification in reactor operation are a precondition for the equal in rights participation of the country in the international cooperation and the approaching to the European structures, and assurance of the national interests. Therefore, the operation and use of the research reactor brings significant economic benefits for the country. For education of students in nuclear energy, reactor physics experiments for measurements of static and kinetic reactor parameters will be carried out on the research reactor. The research reactor as a national base will support training and applied research, keep up the good practice and the preparation of specialists who are able to monitor radioactivity sources, to develop new methods for detection of low quantities of radioactive isotopes which are hard to find, for deactivation and personal protection. The reactor will be used for production of isotopes needed for medical therapy and diagnostics; it will be the neutron source in element activation analysis having a number of applications in industrial production, medicine, chemistry, criminology, etc. The reactor operation will increase the public understanding, confidence

  16. Bayesian modeling of measurement error in predictor variables using item response theory

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; Glas, Cornelis A.W.

    2000-01-01

    This paper focuses on handling measurement error in predictor variables using item response theory (IRT). Measurement error is of great important in assessment of theoretical constructs, such as intelligence or the school climate. Measurement error is modeled by treating the predictors as unobserved

  17. AMS-02 fits dark matter

    Science.gov (United States)

    Balázs, Csaba; Li, Tong

    2016-05-01

    In this work we perform a comprehensive statistical analysis of the AMS-02 electron, positron fluxes and the antiproton-to-proton ratio in the context of a simplified dark matter model. We include known, standard astrophysical sources and a dark matter component in the cosmic ray injection spectra. To predict the AMS-02 observables we use propagation parameters extracted from observed fluxes of heavier nuclei and the low energy part of the AMS-02 data. We assume that the dark matter particle is a Majorana fermion coupling to third generation fermions via a spin-0 mediator, and annihilating to multiple channels at once. The simultaneous presence of various annihilation channels provides the dark matter model with additional flexibility, and this enables us to simultaneously fit all cosmic ray spectra using a simple particle physics model and coherent astrophysical assumptions. Our results indicate that AMS-02 observations are not only consistent with the dark matter hypothesis within the uncertainties, but adding a dark matter contribution improves the fit to the data. Assuming, however, that dark matter is solely responsible for this improvement of the fit, it is difficult to evade the latest CMB limits in this model.

  18. AMS-02 fits dark matter

    Energy Technology Data Exchange (ETDEWEB)

    Balázs, Csaba; Li, Tong [ARC Centre of Excellence for Particle Physics at the Tera-scale,School of Physics and Astronomy, Monash University, Melbourne, Victoria 3800 (Australia)

    2016-05-05

    In this work we perform a comprehensive statistical analysis of the AMS-02 electron, positron fluxes and the antiproton-to-proton ratio in the context of a simplified dark matter model. We include known, standard astrophysical sources and a dark matter component in the cosmic ray injection spectra. To predict the AMS-02 observables we use propagation parameters extracted from observed fluxes of heavier nuclei and the low energy part of the AMS-02 data. We assume that the dark matter particle is a Majorana fermion coupling to third generation fermions via a spin-0 mediator, and annihilating to multiple channels at once. The simultaneous presence of various annihilation channels provides the dark matter model with additional flexibility, and this enables us to simultaneously fit all cosmic ray spectra using a simple particle physics model and coherent astrophysical assumptions. Our results indicate that AMS-02 observations are not only consistent with the dark matter hypothesis within the uncertainties, but adding a dark matter contribution improves the fit to the data. Assuming, however, that dark matter is solely responsible for this improvement of the fit, it is difficult to evade the latest CMB limits in this model.

  19. A History of Regression and Related Model-Fitting in the Earth Sciences (1636?-2000)

    International Nuclear Information System (INIS)

    Howarth, Richard J.

    2001-01-01

    The (statistical) modeling of the behavior of a dependent variate as a function of one or more predictors provides examples of model-fitting which span the development of the earth sciences from the 17th Century to the present. The historical development of these methods and their subsequent application is reviewed. Bond's predictions (c. 1636 and 1668) of change in the magnetic declination at London may be the earliest attempt to fit such models to geophysical data. Following publication of Newton's theory of gravitation in 1726, analysis of data on the length of a 1 o meridian arc, and the length of a pendulum beating seconds, as a function of sin 2 (latitude), was used to determine the ellipticity of the oblate spheroid defining the Figure of the Earth. The pioneering computational methods of Mayer in 1750, Boscovich in 1755, and Lambert in 1765, and the subsequent independent discoveries of the principle of least squares by Gauss in 1799, Legendre in 1805, and Adrain in 1808, and its later substantiation on the basis of probability theory by Gauss in 1809 were all applied to the analysis of such geodetic and geophysical data. Notable later applications include: the geomagnetic survey of Ireland by Lloyd, Sabine, and Ross in 1836, Gauss's model of the terrestrial magnetic field in 1838, and Airy's 1845 analysis of the residuals from a fit to pendulum lengths, from which he recognized the anomalous character of measurements of gravitational force which had been made on islands. In the early 20th Century applications to geological topics proliferated, but the computational burden effectively held back applications of multivariate analysis. Following World War II, the arrival of digital computers in universities in the 1950s facilitated computation, and fitting linear or polynomial models as a function of geographic coordinates, trend surface analysis, became popular during the 1950-60s. The inception of geostatistics in France at this time by Matheron had its

  20. A Sport Education Fitness Season's Impact on Students' Fitness Levels, Knowledge, and In-Class Physical Activity.

    Science.gov (United States)

    Ward, Jeffery Kurt; Hastie, Peter A; Wadsworth, Danielle D; Foote, Shelby; Brock, Sheri J; Hollett, Nikki

    2017-09-01

    The purpose of this study was to determine the extent to which a sport education season of fitness could provide students with recommended levels of in-class moderate-to-vigorous physical activity (MVPA) while also increasing students' fitness knowledge and fitness achievement. One hundred and sixty-six 5th-grade students (76 boys, 90 girls) participated in a 20-lesson season called "CrossFit Challenge" during a 4-week period. The Progressive Aerobic Cardiovascular Endurance Run, push-ups, and curl-ups tests of the FITNESSGRAM® were used to assess fitness at pretest and posttest, while fitness knowledge was assessed through a validated, grade-appropriate test of health-related fitness knowledge (HRF). Physical activity was measured with Actigraph GT3X triaxial accelerometers. Results indicated a significant time effect for all fitness tests and the knowledge test. Across the entire season, the students spent an average of 54.5% of lesson time engaged in MVPA, irrespective of the type of lesson (instruction, free practice, or competition). The results suggest that configuring the key principles of sport education within a unit of fitness is an efficient model for providing students with the opportunity to improve fitness skill and HRF knowledge while attaining recommended levels of MVPA.

  1. Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

    Science.gov (United States)

    Muraki, Eiji

    1999-01-01

    Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

  2. The More, the Better? Curvilinear Effects of Job Autonomy on Well-Being From Vitamin Model and PE-Fit Theory Perspectives.

    Science.gov (United States)

    Stiglbauer, Barbara; Kovacs, Carrie

    2017-12-28

    In organizational psychology research, autonomy is generally seen as a job resource with a monotone positive relationship with desired occupational outcomes such as well-being. However, both Warr's vitamin model and person-environment (PE) fit theory suggest that negative outcomes may result from excesses of some job resources, including autonomy. Thus, the current studies used survey methodology to explore cross-sectional relationships between environmental autonomy, person-environment autonomy (mis)fit, and well-being. We found that autonomy and autonomy (mis)fit explained between 6% and 22% of variance in well-being, depending on type of autonomy (scheduling, method, or decision-making) and type of (mis)fit operationalization (atomistic operationalization through the separate assessment of actual and ideal autonomy levels vs. molecular operationalization through the direct assessment of perceived autonomy (mis)fit). Autonomy (mis)fit (PE-fit perspective) explained more unique variance in well-being than environmental autonomy itself (vitamin model perspective). Detrimental effects of autonomy excess on well-being were most evident for method autonomy and least consistent for decision-making autonomy. We argue that too-much-of-a-good-thing effects of job autonomy on well-being exist, but suggest that these may be dependent upon sample characteristics (range of autonomy levels), type of operationalization (molecular vs. atomistic fit), autonomy facet (method, scheduling, or decision-making), as well as individual and organizational moderators. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  3. Global fits of GUT-scale SUSY models with GAMBIT

    Science.gov (United States)

    Athron, Peter; Balázs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje; Raklev, Are; Rogan, Christopher; de Austri, Roberto Ruiz; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin

    2017-12-01

    We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the constrained minimal supersymmetric standard model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of dark matter in all three models, whilst avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos.

  4. Global fits of GUT-scale SUSY models with GAMBIT

    Energy Technology Data Exchange (ETDEWEB)

    Athron, Peter [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Balazs, Csaba [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Bringmann, Torsten; Dal, Lars A.; Krislock, Abram; Raklev, Are [University of Oslo, Department of Physics, Oslo (Norway); Buckley, Andy [University of Glasgow, SUPA, School of Physics and Astronomy, Glasgow (United Kingdom); Chrzaszcz, Marcin [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); H. Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Krakow (Poland); Conrad, Jan; Edsjoe, Joakim; Farmer, Ben [AlbaNova University Centre, Oskar Klein Centre for Cosmoparticle Physics, Stockholm (Sweden); Stockholm University, Department of Physics, Stockholm (Sweden); Cornell, Jonathan M. [McGill University, Department of Physics, Montreal, QC (Canada); Jackson, Paul; White, Martin [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); University of Adelaide, Department of Physics, Adelaide, SA (Australia); Kvellestad, Anders; Savage, Christopher [NORDITA, Stockholm (Sweden); Mahmoudi, Farvah [Univ Lyon, Univ Lyon 1, CNRS, ENS de Lyon, Centre de Recherche Astrophysique de Lyon UMR5574, Saint-Genis-Laval (France); Theoretical Physics Department, CERN, Geneva (Switzerland); Martinez, Gregory D. [University of California, Physics and Astronomy Department, Los Angeles, CA (United States); Putze, Antje [LAPTh, Universite de Savoie, CNRS, Annecy-le-Vieux (France); Rogan, Christopher [Harvard University, Department of Physics, Cambridge, MA (United States); Ruiz de Austri, Roberto [IFIC-UV/CSIC, Instituto de Fisica Corpuscular, Valencia (Spain); Saavedra, Aldo [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); The University of Sydney, Faculty of Engineering and Information Technologies, Centre for Translational Data Science, School of Physics, Camperdown, NSW (Australia); Scott, Pat [Imperial College London, Department of Physics, Blackett Laboratory, London (United Kingdom); Serra, Nicola [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); Collaboration: The GAMBIT Collaboration

    2017-12-15

    We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the constrained minimal supersymmetric standard model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of dark matter in all three models, whilst avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos. (orig.)

  5. Hair length, facial attractiveness, personality attribution: A multiple fitness model of hairdressing

    OpenAIRE

    Bereczkei, Tamas; Mesko, Norbert

    2007-01-01

    Multiple Fitness Model states that attractiveness varies across multiple dimensions, with each feature representing a different aspect of mate value. In the present study, male raters judged the attractiveness of young females with neotenous and mature facial features, with various hair lengths. Results revealed that the physical appearance of long-haired women was rated high, regardless of their facial attractiveness being valued high or low. Women rated as most attractive were those whose f...

  6. A classical regression framework for mediation analysis: fitting one model to estimate mediation effects.

    Science.gov (United States)

    Saunders, Christina T; Blume, Jeffrey D

    2017-10-26

    Mediation analysis explores the degree to which an exposure's effect on an outcome is diverted through a mediating variable. We describe a classical regression framework for conducting mediation analyses in which estimates of causal mediation effects and their variance are obtained from the fit of a single regression model. The vector of changes in exposure pathway coefficients, which we named the essential mediation components (EMCs), is used to estimate standard causal mediation effects. Because these effects are often simple functions of the EMCs, an analytical expression for their model-based variance follows directly. Given this formula, it is instructive to revisit the performance of routinely used variance approximations (e.g., delta method and resampling methods). Requiring the fit of only one model reduces the computation time required for complex mediation analyses and permits the use of a rich suite of regression tools that are not easily implemented on a system of three equations, as would be required in the Baron-Kenny framework. Using data from the BRAIN-ICU study, we provide examples to illustrate the advantages of this framework and compare it with the existing approaches. © The Author 2017. Published by Oxford University Press.

  7. Are all models created equal? A content analysis of women in advertisements of fitness versus fashion magazines.

    Science.gov (United States)

    Wasylkiw, L; Emms, A A; Meuse, R; Poirier, K F

    2009-03-01

    The current study is a content analysis of women appearing in advertisements in two types of magazines: fitness/health versus fashion/beauty chosen because of their large and predominantly female readerships. Women appearing in advertisements of the June 2007 issue of five fitness/health magazines were compared to women appearing in advertisements of the June 2007 issue of five beauty/fashion magazines. Female models appearing in advertisements of both types of magazines were primarily young, thin Caucasians; however, images of models were more likely to emphasize appearance over performance when they appeared in fashion magazines. This difference in emphasis has implications for future research.

  8. A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

    KAUST Repository

    Dao, Ngocanh; Genton, Marc G.

    2014-01-01

    Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte

  9. Fitness function and nonunique solutions in x-ray reflectivity curve fitting: crosserror between surface roughness and mass density

    International Nuclear Information System (INIS)

    Tiilikainen, J; Bosund, V; Mattila, M; Hakkarainen, T; Sormunen, J; Lipsanen, H

    2007-01-01

    Nonunique solutions of the x-ray reflectivity (XRR) curve fitting problem were studied by modelling layer structures with neural networks and designing a fitness function to handle the nonidealities of measurements. Modelled atomic-layer-deposited aluminium oxide film structures were used in the simulations to calculate XRR curves based on Parratt's formalism. This approach reduced the dimensionality of the parameter space and allowed the use of fitness landscapes in the study of nonunique solutions. Fitness landscapes, where the height in a map represents the fitness value as a function of the process parameters, revealed tracks where the local fitness optima lie. The tracks were projected on the physical parameter space thus allowing the construction of the crosserror equation between weakly determined parameters, i.e. between the mass density and the surface roughness of a layer. The equation gives the minimum error for the other parameters which is a consequence of the nonuniqueness of the solution if noise is present. Furthermore, the existence of a possible unique solution in a certain parameter range was found to be dependent on the layer thickness and the signal-to-noise ratio

  10. RhinAsthma patient perspective: A Rasch validation study.

    Science.gov (United States)

    Molinengo, Giorgia; Baiardini, Ilaria; Braido, Fulvio; Loera, Barbara

    2018-02-01

    In daily practice, Health-Related Quality of Life (HRQoL) tools are useful for supplementing clinical data with the patient's perspective. To encourage their use by clinicians, the availability of tools that can quickly provide valid results is crucial. A new HRQoL tool has been proposed for patients with asthma and rhinitis: the RhinAsthma Patient Perspective-RAPP. The aim of this study was to evaluate the psychometric robustness of the RAPP using the Item Response Theory (IRT) approach, to evaluate the scalability of items and test whether or not patients use the items response scale correctly. 155 patients (53.5% women, mean age 39.1, range 16-76) were recruited during a multicenter study. RAPP metric properties were investigated using IRT models. Differential item functioning (DIF) was used for gender, age, and asthma control test (ACT). The RAPP adequately fitted the Rating Scale model, demonstrating the equality of the rating scale structure for all items. All statistics on items were satisfactory. The RAPP had adequate internal reliability and showed good ability to discriminate among different groups of participants. DIF analysis indicated that there were no differential item functioning issues for gender. One item showed a DIF by age and four items by ACT. The psychometric evaluation performed using IRT models demonstrated that the RAPP met all the criteria to be considered a reliable and valid method of measurement. From a clinical perspective, this will allow physicians to confidently interpret scores as good indicators of Quality of Life of patients with asthma.

  11. A Comparison of Item Exposure Control Procedures with the Generalized Partial Credit Model

    Science.gov (United States)

    Sanchez, Edgar Isaac

    2008-01-01

    To enhance test security of high stakes tests, it is vital to understand the way various exposure control strategies function under various IRT models. To that end the present dissertation focused on the performance of several exposure control strategies under the generalized partial credit model with an item pool of 100 and 200 items. These…

  12. Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain

    Science.gov (United States)

    Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises

    2015-01-01

    Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156

  13. Trade Barrier Elimination, Economics of Scale and Market Competition: Computable General Equilibrium Model

    Directory of Open Access Journals (Sweden)

    Widyastutik Widyastutik

    2017-07-01

    Full Text Available The ASEAN and its dialogue partner countries agreed to reduce trade barriers in the services sector, one of which is sea transport services. The purpose of this study is to estimate the equivalent tax of non-tariff barriers in the sea transport services. Besides that, this study is going to analyze the economic impacts of the regulatory barriers elimination in the sea transport services of ASEAN and its dialogue partner countries. Using the gravity model, it can be identified that trade barriers of sea transport services sector of ASEAN and dialogue partner countries are still relatively high. Additionally, by adopting IC-IRTS model in Global CGE Model (GTAP, the simulation results show consistent results with the theory of pro-competitive effects. The greater gain from trade is obtained in the CGE model assuming IC-IRTS compared to PC-CRTS. China gains a greater benefit that is indicated by the highest increase in welfare and GDP followed by Japan and AustraliaDOI: 10.15408/sjie.v6i2.5279

  14. Neural network hydrological modelling: on questions of over-fitting, over-training and over-parameterisation

    Science.gov (United States)

    Abrahart, R. J.; Dawson, C. W.; Heppenstall, A. J.; See, L. M.

    2009-04-01

    The most critical issue in developing a neural network model is generalisation: how well will the preferred solution perform when it is applied to unseen datasets? The reported experiments used far-reaching sequences of model architectures and training periods to investigate the potential damage that could result from the impact of several interrelated items: (i) over-fitting - a machine learning concept related to exceeding some optimal architectural size; (ii) over-training - a machine learning concept related to the amount of adjustment that is applied to a specific model - based on the understanding that too much fine-tuning might result in a model that had accommodated random aspects of its training dataset - items that had no causal relationship to the target function; and (iii) over-parameterisation - a statistical modelling concept that is used to restrict the number of parameters in a model so as to match the information content of its calibration dataset. The last item in this triplet stems from an understanding that excessive computational complexities might permit an absurd and false solution to be fitted to the available material. Numerous feedforward multilayered perceptrons were trialled and tested. Two different methods of model construction were also compared and contrasted: (i) traditional Backpropagation of Error; and (ii) state-of-the-art Symbiotic Adaptive Neuro-Evolution. Modelling solutions were developed using the reported experimental set ups of Gaume & Gosset (2003). The models were applied to a near-linear hydrological modelling scenario in which past upstream and past downstream discharge records were used to forecast current discharge at the downstream gauging station [CS1: River Marne]; and a non-linear hydrological modelling scenario in which past river discharge measurements and past local meteorological records (precipitation and evaporation) were used to forecast current discharge at the river gauging station [CS2: Le Sauzay].

  15. Combined application of OGTT, IRT and CPRT for diagnosis and treatment of type 2 diabetes mellitus

    International Nuclear Information System (INIS)

    Wei Zikun; Yang Xiaoli; Tian Zhufang

    2006-01-01

    Objective: To assess the value of combined clinical application of oral glucose tolerance test (OGTT), insulin release test (IRT) and C-peptide release test (CPRT) for the diagnosis and treatment of type 2 diabetes mellitus (DM2). Methods: Retrospect analysis of the data of the results of these three tests in 217 subjects examined was performed. Results: (1) Among the 217 subjects, 71 of them were not diagnosed as diabetics. However, upon further scrutinization of the data, 49 (69%) should be classified as diabetics. Fasting blood sugar (FPG) levels were normal in 53% of the 49, but 2h PG levels were mostly elevated with the exception of only 4 (4/49, 8%), Therefore, 2h PG levels were much more useful for screening of diabetes than FPG levels were. (2) Treatment result in these patients was not very satisfactory: only 24% of the patients (35/146) had their disease well-controlled. Conclusion: Combined clinical application of OGTT, ITR and CPRT would enhance the diagnostic accuracy of diabetes with fewer cases missed. (authors)

  16. Universality Classes of Interaction Structures for NK Fitness Landscapes

    Science.gov (United States)

    Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim

    2018-02-01

    Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.

  17. Statistical topography of fitness landscapes

    OpenAIRE

    Franke, Jasper

    2011-01-01

    Fitness landscapes are generalized energy landscapes that play an important conceptual role in evolutionary biology. These landscapes provide a relation between the genetic configuration of an organism and that organism’s adaptive properties. In this work, global topographical features of these fitness landscapes are investigated using theoretical models. The resulting predictions are compared to empirical landscapes. It is shown that these landscapes allow, at least with respe...

  18. Fitting a defect non-linear model with or without prior, distinguishing nuclear reaction products as an example

    Science.gov (United States)

    Helgesson, P.; Sjöstrand, H.

    2017-11-01

    Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.

  19. Fitting a defect non-linear model with or without prior, distinguishing nuclear reaction products as an example.

    Science.gov (United States)

    Helgesson, P; Sjöstrand, H

    2017-11-01

    Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r 1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r 1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r 1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.

  20. Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model

    International Nuclear Information System (INIS)

    Edwards, Darrin C.; Kupinski, Matthew A.; Metz, Charles E.; Nishikawa, Robert M.

    2002-01-01

    We have developed a model for FROC curve fitting that relates the observer's FROC performance not to the ROC performance that would be obtained if the observer's responses were scored on a per image basis, but rather to a hypothesized ROC performance that the observer would obtain in the task of classifying a set of 'candidate detections' as positive or negative. We adopt the assumptions of the Bunch FROC model, namely that the observer's detections are all mutually independent, as well as assumptions qualitatively similar to, but different in nature from, those made by Chakraborty in his AFROC scoring methodology. Under the assumptions of our model, we show that the observer's FROC performance is a linearly scaled version of the candidate analysis ROC curve, where the scaling factors are just given by the FROC operating point coordinates for detecting initial candidates. Further, we show that the likelihood function of the model parameters given observational data takes on a simple form, and we develop a maximum likelihood method for fitting a FROC curve to this data. FROC and AFROC curves are produced for computer vision observer datasets and compared with the results of the AFROC scoring method. Although developed primarily with computer vision schemes in mind, we hope that the methodology presented here will prove worthy of further study in other applications as well

  1. Quantifying and Reducing Curve-Fitting Uncertainty in Isc

    Energy Technology Data Exchange (ETDEWEB)

    Campanelli, Mark; Duck, Benjamin; Emery, Keith

    2015-06-14

    Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.

  2. Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

    Science.gov (United States)

    Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

    2017-09-01

    In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

  3. GRace: a MATLAB-based application for fitting the discrimination-association model.

    Science.gov (United States)

    Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio

    2014-10-28

    The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.

  4. A CAD System for Evaluating Footwear Fit

    Science.gov (United States)

    Savadkoohi, Bita Ture; de Amicis, Raffaele

    With the great growth in footwear demand, the footwear manufacturing industry, for achieving commercial success, must be able to provide the footwear that fulfills consumer's requirement better than it's competitors. Accurate fitting for shoes is an important factor in comfort and functionality. Footwear fitter measurement have been using manual measurement for a long time, but the development of 3D acquisition devices and the advent of powerful 3D visualization and modeling techniques, automatically analyzing, searching and interpretation of the models have now made automatic determination of different foot dimensions feasible. In this paper, we proposed an approach for finding footwear fit within the shoe last data base. We first properly aligned the 3D models using "Weighted" Principle Component Analysis (WPCA). After solving the alignment problem we used an efficient algorithm for cutting the 3D model in order to find the footwear fit from shoe last data base.

  5. Radiation protection, radioactive waste management and site monitoring at the nuclear scientific experimental and educational centre IRT-Sofia at INRNE-BAS.

    Science.gov (United States)

    Mladenov, Al; Stankov, D; Nonova, Tz; Krezhov, K

    2014-11-01

    This article identifies important components and describes the safe practices in implementing radiation protection and radioactive waste management programmes, and in their optimisation at the Nuclear Scientific Experimental and Educational Centre with research reactor IRT at INRNE-BAS. It covers the instrumentation and personal protective equipment and organisational issues related to the continuous site monitoring. The reactor is under major reconstruction and the measures applied to radiation monitoring of environment and working area focused on restricting the radiation exposure of the staff as well as compliance with international good practices related to the environmental and public radiation safety requirements are also addressed. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. The Many Null Distributions of Person Fit Indices.

    Science.gov (United States)

    Molenaar, Ivo W.; Hoijtink, Herbert

    1990-01-01

    Statistical properties of person fit indices are reviewed as indicators of the extent to which a person's score pattern is in agreement with a measurement model. Distribution of a fit index and ability-free fit evaluation are discussed. The null distribution was simulated for a test of 20 items. (SLD)

  7. Inverse problem theory methods for data fitting and model parameter estimation

    CERN Document Server

    Tarantola, A

    2002-01-01

    Inverse Problem Theory is written for physicists, geophysicists and all scientists facing the problem of quantitative interpretation of experimental data. Although it contains a lot of mathematics, it is not intended as a mathematical book, but rather tries to explain how a method of acquisition of information can be applied to the actual world.The book provides a comprehensive, up-to-date description of the methods to be used for fitting experimental data, or to estimate model parameters, and to unify these methods into the Inverse Problem Theory. The first part of the book deals wi

  8. Black Versus Gray T-Shirts: Comparison of Spectrophotometric and Other Biophysical Properties of Physical Fitness Uniforms and Modeled Heat Strain and Thermal Comfort

    Science.gov (United States)

    2016-09-01

    PROPERTIES OF PHYSICAL FITNESS UNIFORMS AND MODELED HEAT STRAIN AND THERMAL COMFORT DISCLAIMER The opinions or assertions contained herein are the...SHIRTS: COMPARISON OF SPECTROPHOTOMETRIC AND OTHER BIOPHYSICAL PROPERTIES OF PHYSICAL FITNESS UNIFORMS AND MODELED HEAT STRAIN AND THERMAL COMFORT ...the impact of the environment on the wearer. To model these impacts on human thermal sensation (e.g., thermal comfort ) and thermoregulatory

  9. Virtual Suit Fit Assessment Using Body Shape Model

    Data.gov (United States)

    National Aeronautics and Space Administration — Shoulder injury is one of the most serious risks for crewmembers in long-duration spaceflight. While suboptimal suit fit and contact pressures between the shoulder...

  10. An NCME Instructional Module on Polytomous Item Response Theory Models

    Science.gov (United States)

    Penfield, Randall David

    2014-01-01

    A polytomous item is one for which the responses are scored according to three or more categories. Given the increasing use of polytomous items in assessment practices, item response theory (IRT) models specialized for polytomous items are becoming increasingly common. The purpose of this ITEMS module is to provide an accessible overview of…

  11. Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics

    Directory of Open Access Journals (Sweden)

    Liyun Su

    2012-01-01

    Full Text Available We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to nonparametric technique of local polynomial estimation, we do not need to know the heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we focus on comparison of parameters and reach an optimal fitting. Besides, we verify the asymptotic normality of parameters based on numerical simulations. Finally, this approach is applied to a case of economics, and it indicates that our method is surely effective in finite-sample situations.

  12. Convolution based profile fitting

    International Nuclear Information System (INIS)

    Kern, A.; Coelho, A.A.; Cheary, R.W.

    2002-01-01

    Full text: In convolution based profile fitting, profiles are generated by convoluting functions together to form the observed profile shape. For a convolution of 'n' functions this process can be written as, Y(2θ)=F 1 (2θ)x F 2 (2θ)x... x F i (2θ)x....xF n (2θ). In powder diffractometry the functions F i (2θ) can be interpreted as the aberration functions of the diffractometer, but in general any combination of appropriate functions for F i (2θ) may be used in this context. Most direct convolution fitting methods are restricted to combinations of F i (2θ) that can be convoluted analytically (e.g. GSAS) such as Lorentzians, Gaussians, the hat (impulse) function and the exponential function. However, software such as TOPAS is now available that can accurately convolute and refine a wide variety of profile shapes numerically, including user defined profiles, without the need to convolute analytically. Some of the most important advantages of modern convolution based profile fitting are: 1) virtually any peak shape and angle dependence can normally be described using minimal profile parameters in laboratory and synchrotron X-ray data as well as in CW and TOF neutron data. This is possible because numerical convolution and numerical differentiation is used within the refinement procedure so that a wide range of functions can easily be incorporated into the convolution equation; 2) it can use physically based diffractometer models by convoluting the instrument aberration functions. This can be done for most laboratory based X-ray powder diffractometer configurations including conventional divergent beam instruments, parallel beam instruments, and diffractometers used for asymmetric diffraction. It can also accommodate various optical elements (e.g. multilayers and monochromators) and detector systems (e.g. point and position sensitive detectors) and has already been applied to neutron powder diffraction systems (e.g. ANSTO) as well as synchrotron based

  13. Fitting outbreak models to data from many small norovirus outbreaks

    Directory of Open Access Journals (Sweden)

    Eamon B. O’Dea

    2014-03-01

    Full Text Available Infectious disease often occurs in small, independent outbreaks in populations with varying characteristics. Each outbreak by itself may provide too little information for accurate estimation of epidemic model parameters. Here we show that using standard stochastic epidemic models for each outbreak and allowing parameters to vary between outbreaks according to a linear predictor leads to a generalized linear model that accurately estimates parameters from many small and diverse outbreaks. By estimating initial growth rates in addition to transmission rates, we are able to characterize variation in numbers of initially susceptible individuals or contact patterns between outbreaks. With simulation, we find that the estimates are fairly robust to the data being collected at discrete intervals and imputation of about half of all infectious periods. We apply the method by fitting data from 75 norovirus outbreaks in health-care settings. Our baseline regression estimates are 0.0037 transmissions per infective-susceptible day, an initial growth rate of 0.27 transmissions per infective day, and a symptomatic period of 3.35 days. Outbreaks in long-term-care facilities had significantly higher transmission and initial growth rates than outbreaks in hospitals.

  14. Minimal see-saw model predicting best fit lepton mixing angles

    International Nuclear Information System (INIS)

    King, Stephen F.

    2013-01-01

    We discuss a minimal predictive see-saw model in which the right-handed neutrino mainly responsible for the atmospheric neutrino mass has couplings to (ν e ,ν μ ,ν τ ) proportional to (0,1,1) and the right-handed neutrino mainly responsible for the solar neutrino mass has couplings to (ν e ,ν μ ,ν τ ) proportional to (1,4,2), with a relative phase η=−2π/5. We show how these patterns of couplings could arise from an A 4 family symmetry model of leptons, together with Z 3 and Z 5 symmetries which fix η=−2π/5 up to a discrete phase choice. The PMNS matrix is then completely determined by one remaining parameter which is used to fix the neutrino mass ratio m 2 /m 3 . The model predicts the lepton mixing angles θ 12 ≈34 ∘ ,θ 23 ≈41 ∘ ,θ 13 ≈9.5 ∘ , which exactly coincide with the current best fit values for a normal neutrino mass hierarchy, together with the distinctive prediction for the CP violating oscillation phase δ≈106 ∘

  15. A Multidimensional Partial Credit Model with Associated Item and Test Statistics: An Application to Mixed-Format Tests

    Science.gov (United States)

    Yao, Lihua; Schwarz, Richard D.

    2006-01-01

    Multidimensional item response theory (IRT) models have been proposed for better understanding the dimensional structure of data or to define diagnostic profiles of student learning. A compensatory multidimensional two-parameter partial credit model (M-2PPC) for constructed-response items is presented that is a generalization of those proposed to…

  16. Psychometric evaluation of an item bank for computerized adaptive testing of the EORTC QLQ-C30 cognitive functioning dimension in cancer patients.

    Science.gov (United States)

    Dirven, Linda; Groenvold, Mogens; Taphoorn, Martin J B; Conroy, Thierry; Tomaszewski, Krzysztof A; Young, Teresa; Petersen, Morten Aa

    2017-11-01

    The European Organisation of Research and Treatment of Cancer (EORTC) Quality of Life Group is developing computerized adaptive testing (CAT) versions of all EORTC Quality of Life Questionnaire (QLQ-C30) scales with the aim to enhance measurement precision. Here we present the results on the field-testing and psychometric evaluation of the item bank for cognitive functioning (CF). In previous phases (I-III), 44 candidate items were developed measuring CF in cancer patients. In phase IV, these items were psychometrically evaluated in a large sample of international cancer patients. This evaluation included an assessment of dimensionality, fit to the item response theory (IRT) model, differential item functioning (DIF), and measurement properties. A total of 1030 cancer patients completed the 44 candidate items on CF. Of these, 34 items could be included in a unidimensional IRT model, showing an acceptable fit. Although several items showed DIF, these had a negligible impact on CF estimation. Measurement precision of the item bank was much higher than the two original QLQ-C30 CF items alone, across the whole continuum. Moreover, CAT measurement may on average reduce study sample sizes with about 35-40% compared to the original QLQ-C30 CF scale, without loss of power. A CF item bank for CAT measurement consisting of 34 items was established, applicable to various cancer patients across countries. This CAT measurement system will facilitate precise and efficient assessment of HRQOL of cancer patients, without loss of comparability of results.

  17. Optimal item discrimination and maximum information for logistic IRT models

    NARCIS (Netherlands)

    Veerkamp, W.J.J.; Veerkamp, Wim J.J.; Berger, Martijn P.F.; Berger, Martijn

    1999-01-01

    Items with the highest discrimination parameter values in a logistic item response theory model do not necessarily give maximum information. This paper derives discrimination parameter values, as functions of the guessing parameter and distances between person parameters and item difficulty, that

  18. Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson's Disease Patients.

    Science.gov (United States)

    Buatois, Simon; Retout, Sylvie; Frey, Nicolas; Ueckert, Sebastian

    2017-10-01

    This manuscript aims to precisely describe the natural disease progression of Parkinson's disease (PD) patients and evaluate approaches to increase the drug effect detection power. An item response theory (IRT) longitudinal model was built to describe the natural disease progression of 423 de novo PD patients followed during 48 months while taking into account the heterogeneous nature of the MDS-UPDRS. Clinical trial simulations were then used to compare drug effect detection power from IRT and sum of item scores based analysis under different analysis endpoints and drug effects. The IRT longitudinal model accurately describes the evolution of patients with and without PD medications while estimating different progression rates for the subscales. When comparing analysis methods, the IRT-based one consistently provided the highest power. IRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.

  19. GENFIT - a generic track-fitting toolkit

    Energy Technology Data Exchange (ETDEWEB)

    Rauch, Johannes [Technische Universitaet Muenchen (Germany); Schlueter, Tobias [Ludwig-Maximilians-Universitaet Muenchen (Germany)

    2014-07-01

    GENFIT is an experiment-independent track-fitting toolkit, which combines fitting algorithms, track representations, and measurement geometries into a modular framework. We report on a significantly improved version of GENFIT, based on experience gained in the Belle II, PANDA, and FOPI experiments. Improvements concern the implementation of additional track-fitting algorithms, enhanced implementations of Kalman fitters, enhanced visualization capabilities, and additional implementations of measurement types suited for various kinds of tracking detectors. The data model has been revised, allowing for efficient track merging, smoothing, residual calculation and alignment.

  20. New ROOT Graphical User Interfaces for fitting

    International Nuclear Information System (INIS)

    Maline, D Gonzalez; Moneta, L; Antcheva, I

    2010-01-01

    ROOT, as a scientific data analysis framework, provides extensive capabilities via Graphical User Interfaces (GUI) for performing interactive analysis and visualizing data objects like histograms and graphs. A new interface for fitting has been developed for performing, exploring and comparing fits on data point sets such as histograms, multi-dimensional graphs or trees. With this new interface, users can build interactively the fit model function, set parameter values and constraints and select fit and minimization methods with their options. Functionality for visualizing the fit results is as well provided, with the possibility of drawing residuals or confidence intervals. Furthermore, the new fit panel reacts as a standalone application and it does not prevent users from interacting with other windows. We will describe in great detail the functionality of this user interface, covering as well new capabilities provided by the new fitting and minimization tools introduced recently in the ROOT framework.

  1. International Peer Review of Swedish Nuclear Fuel and Waste Management Company's SR-Can interim report

    International Nuclear Information System (INIS)

    Sagar, Budhi; Bailey, Lucy; Bennett, David G.; Egan, Mike; Roehlig, Klaus

    2004-12-01

    SKB has produced an interim safety assessment report as part of its work to develop a licence application for the construction of a spent nuclear fuel encapsulation plant. The purpose of the interim report is to set out and demonstrate SKB's proposed methodology for long-term safety assessment. The aim of producing an interim report is to allow the Swedish regulatory authorities (SKI and SSI) to review and comment on SKB's proposed methodology before it is used in support of a formal licence application. To help inform their review of SKB's proposed methodology, the authorities appointed an international review team (IRT) to carry out a review of SKB's interim safety assessment report. Comments from the IRT are presented in this document and will be considered by the regulatory authorities in developing their own view of SKB's proposed methodology. The IRT's review included examination of SKB's documentation (the 'Interim Main Report of the Safety Assessment SR-Can' and four supporting documents) and hearings with SKB staff and contractors. The hearings provided an opportunity for the IRT to discuss the SR-Can safety assessment with the authors and contributors to SKB's work. As directed by SKI and SSI, the IRT's review focused on methodological aspects and sought to determine whether SKB's proposed safety assessment methodology: (i) is fit for the purpose of supporting a licence application; (ii) has a reasonable prospect of leading to a safety assessment that is sufficiently comprehensive, reproducible, traceable and transparent; (iii) is compatible with the authorities' regulations and guidance. No evaluation of long term safety or site acceptability was attempted by the IRT. At the request of SKI and SSI, the IRT's review considered and made recommendations on the following issues: Description of the initial state of the repository and its components; Description of features, events and processes (FEPs) relevant to repository evolution; Strategy for safety

  2. Levy flights and self-similar exploratory behaviour of termite workers: beyond model fitting.

    Directory of Open Access Journals (Sweden)

    Octavio Miramontes

    Full Text Available Animal movements have been related to optimal foraging strategies where self-similar trajectories are central. Most of the experimental studies done so far have focused mainly on fitting statistical models to data in order to test for movement patterns described by power-laws. Here we show by analyzing over half a million movement displacements that isolated termite workers actually exhibit a range of very interesting dynamical properties--including Lévy flights--in their exploratory behaviour. Going beyond the current trend of statistical model fitting alone, our study analyses anomalous diffusion and structure functions to estimate values of the scaling exponents describing displacement statistics. We evince the fractal nature of the movement patterns and show how the scaling exponents describing termite space exploration intriguingly comply with mathematical relations found in the physics of transport phenomena. By doing this, we rescue a rich variety of physical and biological phenomenology that can be potentially important and meaningful for the study of complex animal behavior and, in particular, for the study of how patterns of exploratory behaviour of individual social insects may impact not only their feeding demands but also nestmate encounter patterns and, hence, their dynamics at the social scale.

  3. Item Response Theory Models for Performance Decline during Testing

    Science.gov (United States)

    Jin, Kuan-Yu; Wang, Wen-Chung

    2014-01-01

    Sometimes, test-takers may not be able to attempt all items to the best of their ability (with full effort) due to personal factors (e.g., low motivation) or testing conditions (e.g., time limit), resulting in poor performances on certain items, especially those located toward the end of a test. Standard item response theory (IRT) models fail to…

  4. Innovation Rather than Improvement: A Solvable High-Dimensional Model Highlights the Limitations of Scalar Fitness

    Science.gov (United States)

    Tikhonov, Mikhail; Monasson, Remi

    2018-01-01

    Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.

  5. A bipartite fitness model for online music streaming services

    Science.gov (United States)

    Pongnumkul, Suchit; Motohashi, Kazuyuki

    2018-01-01

    This paper proposes an evolution model and an analysis of the behavior of music consumers on online music streaming services. While previous studies have observed power-law degree distributions of usage in online music streaming services, the underlying behavior of users has not been well understood. Users and songs can be described using a bipartite network where an edge exists between a user node and a song node when the user has listened that song. The growth mechanism of bipartite networks has been used to understand the evolution of online bipartite networks Zhang et al. (2013). Existing bipartite models are based on a preferential attachment mechanism László Barabási and Albert (1999) in which the probability that a user listens to a song is proportional to its current popularity. This mechanism does not allow for two types of real world phenomena. First, a newly released song with high quality sometimes quickly gains popularity. Second, the popularity of songs normally decreases as time goes by. Therefore, this paper proposes a new model that is more suitable for online music services by adding fitness and aging functions to the song nodes of the bipartite network proposed by Zhang et al. (2013). Theoretical analyses are performed for the degree distribution of songs. Empirical data from an online streaming service, Last.fm, are used to confirm the degree distribution of the object nodes. Simulation results show improvements from a previous model. Finally, to illustrate the application of the proposed model, a simplified royalty cost model for online music services is used to demonstrate how the changes in the proposed parameters can affect the costs for online music streaming providers. Managerial implications are also discussed.

  6. Critical Values for Yen’s Q3

    DEFF Research Database (Denmark)

    Christensen, Karl Bang; Makransky, Guido; Horton, Mike

    2017-01-01

    The assumption of local independence is central to all item response theory (IRT) models. Violations can lead to inflated estimates of reliability and problems with construct validity. For the most widely used fit statistic Q3, there are currently no well-documented suggestions of the critical...... to the data set, and provide example critical values for a number of data structure situations. The results show that for the Q3 fit statistic, no single critical value is appropriate for all situations, as the percentiles in the empirical null distribution are influenced by the number of items, the sample...... size, and the number of response categories. Furthermore, the results show that LD should be considered relative to the average observed residual correlation, rather than to a uniform value, as this results in more stable percentiles for the null distribution of an adjusted fit statistic....

  7. ACCELERATED FITTING OF STELLAR SPECTRA

    Energy Technology Data Exchange (ETDEWEB)

    Ting, Yuan-Sen; Conroy, Charlie [Harvard–Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Rix, Hans-Walter [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany)

    2016-07-20

    Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating a sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.

  8. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus

    2006-01-01

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice, the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution...

  9. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus Plenge

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution function...

  10. The Experience of Storage and Shipment for Reprocessing of HEU Nuclear Fuel Irradiated in the IRT-M Research Reactor and Pamir-630 Mobile Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Sikorin, S. N.; Polazau, S. A.; Luneu, A. N.; Hrigarovich, T. K. [Joint Institute for Power and Nuclear Research–Sosny of the National Academy of Sciences of Belarus, Minsk (Belarus)

    2014-08-15

    At the end of 2010 under the Global Threat Reduction Initiative (GTRI), the Joint Institute for Power and Nuclear Research–“Sosny” (JIPNR–Sosny) of the National Academy of Sciences of the Republic of Belarus repatriated HEU spent nuclear fuel to the Russian Federation. The spent nuclear fuel was from the decommissioned Pamir-630D mobile reactor and IRT-M research reactor. The paper discusses the Pamir-630D spent nuclear fuel; experience and problems of spent nuclear fuel storage; and various aspects of the shipment including legal framework, preparation activities and shipment logistics. The conceptual project of a new research reactor for Belarus is also presented.

  11. Introduction: Occam’s Razor (SOT - Fit for Purpose workshop introduction)

    Science.gov (United States)

    Mathematical models provide important, reproducible, and transparent information for risk-based decision making. However, these models must be constructed to fit the needs of the problem to be solved. A “fit for purpose” model is an abstraction of a complicated problem that allow...

  12. Development and validation of a new knowledge, attitude, belief and practice questionnaire on leptospirosis in Malaysia.

    Science.gov (United States)

    Zahiruddin, Wan Mohd; Arifin, Wan Nor; Mohd-Nazri, Shafei; Sukeri, Surianti; Zawaha, Idris; Bakar, Rahman Abu; Hamat, Rukman Awang; Malina, Osman; Jamaludin, Tengku Zetty Maztura Tengku; Pathman, Arumugam; Mas-Harithulfadhli-Agus, Ab Rahman; Norazlin, Idris; Suhailah, Binti Samsudin; Saudi, Siti Nor Sakinah; Abdullah, Nurul Munirah; Nozmi, Noramira; Zainuddin, Abdul Wahab; Aziah, Daud

    2018-03-07

    In Malaysia, leptospirosis is considered an endemic disease, with sporadic outbreaks following rainy or flood seasons. The objective of this study was to develop and validate a new knowledge, attitude, belief and practice (KABP) questionnaire on leptospirosis for use in urban and rural populations in Malaysia. The questionnaire comprised development and validation stages. The development phase encompassed a literature review, expert panel review, focus-group testing, and evaluation. The validation phase consisted of exploratory and confirmatory parts to verify the psychometric properties of the questionnaire. A total of 214 and 759 participants were recruited from two Malaysian states, Kelantan and Selangor respectively, for the validation phase. The participants comprised urban and rural communities with a high reported incidence of leptospirosis. The knowledge section of the validation phase utilized item response theory (IRT) analysis. The attitude and belief sections utilized exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The development phase resulted in a questionnaire that included four main sections: knowledge, attitude, belief, and practice. In the exploratory phase, as shown by the IRT analysis of knowledge about leptospirosis, the difficulty and discrimination values of the items were acceptable, with the exception of two items. Based on the EFA, the psychometric properties of the attitude, belief, and practice sections were poor. Thus, these sections were revised, and no further factor analysis of the practice section was conducted. In the confirmatory stage, the difficulty and discrimination values of the items in the knowledge section remained within the acceptable range. The CFA of the attitude section resulted in a good-fitting two-factor model. The CFA of the belief section retained low number of items, although the analysis resulted in a good fit in the final three-factor model. Based on the IRT analysis and factor

  13. Development of a computer-adaptive physical function instrument for Social Security Administration disability determination.

    Science.gov (United States)

    Ni, Pengsheng; McDonough, Christine M; Jette, Alan M; Bogusz, Kara; Marfeo, Elizabeth E; Rasch, Elizabeth K; Brandt, Diane E; Meterko, Mark; Haley, Stephen M; Chan, Leighton

    2013-09-01

    To develop and test an instrument to assess physical function for Social Security Administration (SSA) disability programs, the SSA-Physical Function (SSA-PF) instrument. Item response theory (IRT) analyses were used to (1) create a calibrated item bank for each of the factors identified in prior factor analyses, (2) assess the fit of the items within each scale, (3) develop separate computer-adaptive testing (CAT) instruments for each scale, and (4) conduct initial psychometric testing. Cross-sectional data collection; IRT analyses; CAT simulation. Telephone and Internet survey. Two samples: SSA claimants (n=1017) and adults from the U.S. general population (n=999). None. Model fit statistics, correlation, and reliability coefficients. IRT analyses resulted in 5 unidimensional SSA-PF scales: Changing & Maintaining Body Position, Whole Body Mobility, Upper Body Function, Upper Extremity Fine Motor, and Wheelchair Mobility for a total of 102 items. High CAT accuracy was demonstrated by strong correlations between simulated CAT scores and those from the full item banks. On comparing the simulated CATs with the full item banks, very little loss of reliability or precision was noted, except at the lower and upper ranges of each scale. No difference in response patterns by age or sex was noted. The distributions of claimant scores were shifted to the lower end of each scale compared with those of a sample of U.S. adults. The SSA-PF instrument contributes important new methodology for measuring the physical function of adults applying to the SSA disability programs. Initial evaluation revealed that the SSA-PF instrument achieved considerable breadth of coverage in each content domain and demonstrated noteworthy psychometric properties. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  14. The psychometric properties of the 16-item version of the Prodromal Questionnaire (PQ-16) as a screening instrument for perinatal psychosis

    DEFF Research Database (Denmark)

    Levey, Elizabeth J.; Zhong, Q; Rondon, M

    2018-01-01

    negative symptoms, accounted for 6.3%. Rasch IRT analysis found that all of the items fit the model. These findings support the construct validity of the PQ-16 in this pregnant Peruvian population. Also, further research is needed to establish definitive psychiatric diagnoses to determine the predictive...... accounted for 44% of the variance. Factor 1, representing "unstable sense of self," accounted for 22.1% of the total variance; factor 2, representing "ideas of reference/paranoia," for 8.4%; factor 3, representing "sensitivity to sensory experiences," accounted for 7.2%; and factor 4, possibly representing...

  15. VizieR Online Data Catalog: GRB prompt emission fitted with the DREAM model (Ahlgren+, 2015)

    Science.gov (United States)

    Ahlgren, B.; Larsson, J.; Nymark, T.; Ryde, F.; Pe'Er, A.

    2018-01-01

    We illustrate the application of the DREAM model by fitting it to two different, bright Fermi GRBs; GRB 090618 and GRB 100724B. While GRB 090618 is well fitted by a Band function, GRB 100724B was the first example of a burst with a significant additional BB component (Guiriec et al. 2011ApJ...727L..33G). GRB 090618 is analysed using Gamma-ray Burst Monitor (GBM) data (Meegan et al. 2009ApJ...702..791M) from the NaI and BGO detectors. For GRB 100724B, we used GBM data from the NaI and BGO detectors as well as Large Area Telescope Low Energy (LAT-LLE) data. For both bursts we selected NaI detectors seeing the GRB at an off-axis angle lower than 60° and the BGO detector as being the best aligned of the two BGO detectors. The spectra were fitted in the energy ranges 8-1000 keV (NaI), 200-40000 keV (BGO) and 30-1000 MeV (LAT-LLE). (2 data files).

  16. Stochastic order in dichotomous item response models for fixed tests, research adaptive tests, or multiple abilities

    NARCIS (Netherlands)

    van der Linden, Willem J.

    1995-01-01

    Dichotomous item response theory (IRT) models can be viewed as families of stochastically ordered distributions of responses to test items. This paper explores several properties of such distributiom. The focus is on the conditions under which stochastic order in families of conditional

  17. A review of the effects on IRT item parameter estimates with a focus on misbehaving common items in test equating

    Directory of Open Access Journals (Sweden)

    Michalis P Michaelides

    2010-10-01

    Full Text Available Many studies have investigated the topic of change or drift in item parameter estimates in the context of Item Response Theory. Content effects, such as instructional variation and curricular emphasis, as well as context effects, such as the wording, position, or exposure of an item have been found to impact item parameter estimates. The issue becomes more critical when items with estimates exhibiting differential behavior across test administrations are used as common for deriving equating transformations. This paper reviews the types of effects on IRT item parameter estimates and focuses on the impact of misbehaving or aberrant common items on equating transformations. Implications relating to test validity and the judgmental nature of the decision to keep or discard aberrant common items are discussed, with recommendations for future research into more informed and formal ways of dealing with misbehaving common items.

  18. Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

    Science.gov (United States)

    Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

    2013-01-01

    In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

  19. Modeling Composite Assessment Data Using Item Response Theory

    Science.gov (United States)

    Ueckert, Sebastian

    2018-01-01

    Composite assessments aim to combine different aspects of a disease in a single score and are utilized in a variety of therapeutic areas. The data arising from these evaluations are inherently discrete with distinct statistical properties. This tutorial presents the framework of the item response theory (IRT) for the analysis of this data type in a pharmacometric context. The article considers both conceptual (terms and assumptions) and practical questions (modeling software, data requirements, and model building). PMID:29493119

  20. Comments on Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?"

    Science.gov (United States)

    McCluskey, Ken W.

    2010-01-01

    This article presents the author's comments on Hisham B. Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib's article focuses on the transformation of science from pre-modern times to the present. Ghassib (2010) notes that, unlike in an earlier era when the economy depended on static…

  1. Supersymmetric Fits after the Higgs Discovery and Implications for Model Building

    CERN Document Server

    Ellis, John

    2014-01-01

    The data from the first run of the LHC at 7 and 8 TeV, together with the information provided by other experiments such as precision electroweak measurements, flavour measurements, the cosmological density of cold dark matter and the direct search for the scattering of dark matter particles in the LUX experiment, provide important constraints on supersymmetric models. Important information is provided by the ATLAS and CMS measurements of the mass of the Higgs boson, as well as the negative results of searches at the LHC for events with missing transverse energy accompanied by jets, and the LHCb and CMS measurements off BR($B_s \\to \\mu^+ \\mu^-$). Results are presented from frequentist analyses of the parameter spaces of the CMSSM and NUHM1. The global $\\chi^2$ functions for the supersymmetric models vary slowly over most of the parameter spaces allowed by the Higgs mass and the missing transverse energy search, with best-fit values that are comparable to the $\\chi^2$ for the Standard Model. The $95\\%$ CL lower...

  2. Non-linear least squares curve fitting of a simple theoretical model to radioimmunoassay dose-response data using a mini-computer

    International Nuclear Information System (INIS)

    Wilkins, T.A.; Chadney, D.C.; Bryant, J.; Palmstroem, S.H.; Winder, R.L.

    1977-01-01

    Using the simple univalent antigen univalent-antibody equilibrium model the dose-response curve of a radioimmunoassay (RIA) may be expressed as a function of Y, X and the four physical parameters of the idealised system. A compact but powerful mini-computer program has been written in BASIC for rapid iterative non-linear least squares curve fitting and dose interpolation with this function. In its simplest form the program can be operated in an 8K byte mini-computer. The program has been extensively tested with data from 10 different assay systems (RIA and CPBA) for measurement of drugs and hormones ranging in molecular size from thyroxine to insulin. For each assay system the results have been analysed in terms of (a) curve fitting biases and (b) direct comparison with manual fitting. In all cases the quality of fitting was remarkably good in spite of the fact that the chemistry of each system departed significantly from one or more of the assumptions implicit in the model used. A mathematical analysis of departures from the model's principal assumption has provided an explanation for this somewhat unexpected observation. The essential features of this analysis are presented in this paper together with the statistical analyses of the performance of the program. From these and the results obtained to date in the routine quality control of these 10 assays, it is concluded that the method of curve fitting and dose interpolation presented in this paper is likely to be of general applicability. (orig.) [de

  3. Fits combining hyperon semileptonic decays and magnetic moments and CVC

    International Nuclear Information System (INIS)

    Bohm, A.; Kielanowski, P.

    1982-10-01

    We have performed a test of CVC by determining the baryon charges and magnetic moments from the hyperon semileptonic data. Then CVC was applied in order to make a joint fit of all baryon semileptonic decay data and baryon magnetic moments for the spectrum generating group (SG) model as well as for the conventional (cabibbo and magnetic moments in nuclear magnetons) model. The SG model gives a very good fit with chi 2 /n/sub D/ = 25/20 approximately equals 21% C.L. whereas the conventional model gives a fit with chi 2 /n/sub D/ = 244/20

  4. Two Aspects of the Simplex Model: Goodness of Fit to Linear Growth Curve Structures and the Analysis of Mean Trends.

    Science.gov (United States)

    Mandys, Frantisek; Dolan, Conor V.; Molenaar, Peter C. M.

    1994-01-01

    Studied the conditions under which the quasi-Markov simplex model fits a linear growth curve covariance structure and determined when the model is rejected. Presents a quasi-Markov simplex model with structured means and gives an example. (SLD)

  5. Determining Mission Statement Effectiveness from a Fit Perspective

    Directory of Open Access Journals (Sweden)

    Toh Seong-Yuen

    2017-08-01

    Full Text Available The purpose of this paper is to study the relationship between the organization's mission statement and its outcomes from a fit perspective in the alignment of the organization's structural and cultural elements. Based on an extension of Campbell's (1991 mission model by combination of ideas from two schools of thought in mission statement studies (structural and cultural, the authors introduce the concept of “fit” to show how it contributes towards a new mission statement model. The results show that both alignments are important to create a fit situation in order to positively impact organization outcomes. Based on Cohen (1988, the detected effect size of .322 is considered large. The managerial implication is that there should be more focus on managing organisational alignment to support a fit situation as this is instrumental to mission statement effectiveness. The originality of this study stems from the idea that while past studies develop model based on ideas from within the confine of a particular school of thought, this study is one of the first to combine ideas from both the structural and cultural schools of thought by extending Campbell's (1991 mission model using the fit perspective.

  6. The fitting parameters extraction of conversion model of the low dose rate effect in bipolar devices

    International Nuclear Information System (INIS)

    Bakerenkov, Alexander

    2011-01-01

    The Enhanced Low Dose Rate Sensitivity (ELDRS) in bipolar devices consists of in base current degradation of NPN and PNP transistors increase as the dose rate is decreased. As a result of almost 20-year studying, the some physical models of effect are developed, being described in detail. Accelerated test methods, based on these models use in standards. The conversion model of the effect, that allows to describe the inverse S-shaped excess base current dependence versus dose rate, was proposed. This paper presents the problem of conversion model fitting parameters extraction.

  7. Quantifying and Reducing Curve-Fitting Uncertainty in Isc: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Campanelli, Mark; Duck, Benjamin; Emery, Keith

    2015-09-28

    Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.

  8. Applying Kaplan-Meier to Item Response Data

    Science.gov (United States)

    McNeish, Daniel

    2018-01-01

    Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…

  9. Theoretically unprejudiced fits to proton scattering

    International Nuclear Information System (INIS)

    Kobos, A.M.; Mackintosh, R.S.

    1979-01-01

    By using a spline interpolation method applied to all components of the proton optical potential we have fitted elastic scattering from 40 Ca and from 16 O at a range of energies. The potentials are highly oscillatory and we have shown that similar oscillations are found when the spline fitting procedure is applied to pseudo-data generated from potentials of known l-dependence. Moreover, we show how to find an l-independent potential equivalent to one that is l-dependent and we find that it is oscillatory and that various characteristic features of empirical spline fit potentials can be explained. Thus, by fitting the data with model indenpendt l-independent potentials we have found support for the contention that the nucleon optical potential should be viewed as being l-dependent. This work may be regarded as an example of the kind of physical information that can be gained by pursuing exact fits to proton elastic scattering data

  10. A comparison of approaches in fitting continuum SEDs

    International Nuclear Information System (INIS)

    Liu Yao; Wang Hong-Chi; Madlener David; Wolf Sebastian

    2013-01-01

    We present a detailed comparison of two approaches, the use of a pre-calculated database and simulated annealing (SA), for fitting the continuum spectral energy distribution (SED) of astrophysical objects whose appearance is dominated by surrounding dust. While pre-calculated databases are commonly used to model SED data, only a few studies to date employed SA due to its unclear accuracy and convergence time for this specific problem. From a methodological point of view, different approaches lead to different fitting quality, demand on computational resources and calculation time. We compare the fitting quality and computational costs of these two approaches for the task of SED fitting to provide a guide to the practitioner to find a compromise between desired accuracy and available resources. To reduce uncertainties inherent to real datasets, we introduce a reference model resembling a typical circumstellar system with 10 free parameters. We derive the SED of the reference model with our code MC3 D at 78 logarithmically distributed wavelengths in the range [0.3 μm, 1.3 mm] and use this setup to simulate SEDs for the database and SA. Our result directly demonstrates the applicability of SA in the field of SED modeling, since the algorithm regularly finds better solutions to the optimization problem than a pre-calculated database. As both methods have advantages and shortcomings, a hybrid approach is preferable. While the database provides an approximate fit and overall probability distributions for all parameters deduced using Bayesian analysis, SA can be used to improve upon the results returned by the model grid.

  11. Fitness club

    CERN Multimedia

    Fitness club

    2011-01-01

    General fitness Classes Enrolments are open for general fitness classes at CERN taking place on Monday, Wednesday, and Friday lunchtimes in the Pump Hall (building 216). There are shower facilities for both men and women. It is possible to pay for 1, 2 or 3 classes per week for a minimum of 1 month and up to 6 months. Check out our rates and enrol at: http://cern.ch/club-fitness Hope to see you among us! CERN Fitness Club fitness.club@cern.ch  

  12. Further Simplification of the Simple Erosion Narrowing Score With Item Response Theory Methodology.

    Science.gov (United States)

    Oude Voshaar, Martijn A H; Schenk, Olga; Ten Klooster, Peter M; Vonkeman, Harald E; Bernelot Moens, Hein J; Boers, Maarten; van de Laar, Mart A F J

    2016-08-01

    To further simplify the simple erosion narrowing score (SENS) by removing scored areas that contribute the least to its measurement precision according to analysis based on item response theory (IRT) and to compare the measurement performance of the simplified version to the original. Baseline and 18-month data of the Combinatietherapie Bij Reumatoide Artritis (COBRA) trial were modeled using longitudinal IRT methodology. Measurement precision was evaluated across different levels of structural damage. SENS was further simplified by omitting the least reliably scored areas. Discriminant validity of SENS and its simplification were studied by comparing their ability to differentiate between the COBRA and sulfasalazine arms. Responsiveness was studied by comparing standardized change scores between versions. SENS data showed good fit to the IRT model. Carpal and feet joints contributed the least statistical information to both erosion and joint space narrowing scores. Omitting the joints of the foot reduced measurement precision for the erosion score in cases with below-average levels of structural damage (relative efficiency compared with the original version ranged 35-59%). Omitting the carpal joints had minimal effect on precision (relative efficiency range 77-88%). Responsiveness of a simplified SENS without carpal joints closely approximated the original version (i.e., all Δ standardized change scores were ≤0.06). Discriminant validity was also similar between versions for both the erosion score (relative efficiency = 97%) and the SENS total score (relative efficiency = 84%). Our results show that the carpal joints may be omitted from the SENS without notable repercussion for its measurement performance. © 2016, American College of Rheumatology.

  13. A Test of the Need Hierarchy Concept by a Markov Model of Change in Need Strength.

    Science.gov (United States)

    Rauschenberger, John; And Others

    1980-01-01

    In this study of 547 high school graduates, Alderfer's and Maslow's need hierarchy theories were expressed in Markov chain form and were subjected to empirical test. Both models were disconfirmed. Corroborative multiwave correlational analysis also failed to support the need hierarchy concept. (Author/IRT)

  14. LOCO with Constraints and Improved Fitting Technique

    International Nuclear Information System (INIS)

    Not Available

    2007-01-01

    LOCO has been a powerful beam-based diagnostics and optics control method for storage rings and synchrotrons worldwide ever since it was established at NSLS by J. Safranek. This method measures the orbit response matrix and optionally the dispersion function of the machine. The data are then fitted to a lattice model by adjusting parameters such as quadrupole and skew quadrupole strengths in the model, BPM gains and rolls, corrector gains and rolls of the measurement system. Any abnormality of the machine that affects the machine optics can then be identified. The resulting lattice model is equivalent to the real machine lattice as seen by the BPMs. Since there are usually two or more BPMs per betatron period in modern circular accelerators, the model is often a very accurate representation of the real machine. According to the fitting result, one can correct the machine lattice to the design lattice by changing the quadrupole and skew quadrupole strengths. LOCO is so important that it is routinely performed at many electron storage rings to guarantee machine performance, especially after the Matlab-based LOCO code became available. However, for some machines, LOCO is not easy to carry out. In some cases, LOCO fitting converges to an unrealistic solution with large changes to the quadrupole strengths ΔK. The quadrupole gradient changes can be so large that the resulting lattice model fails to find a closed orbit and subsequent iterations become impossible. In cases when LOCO converges, the solution can have ΔK that is larger than realistic and often along with a spurious zigzag pattern between adjacent quadrupoles. This degeneracy behavior of LOCO is due to the correlation between the fitting parameters - usually between neighboring quadrupoles. The fitting scheme is therefore less restrictive over certain patterns of changes to these quadrupoles with which the correlated quadrupoles fight each other and the net effect is very inefficient χ 2 reduction, i

  15. Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis.

    NARCIS (Netherlands)

    Novakovic, A.M.; Krekels, E.H.; Munafo, A.; Ueckert, S.; Karlsson, M.O.

    2016-01-01

    In this study, we report the development of the first item response theory (IRT) model within a pharmacometrics framework to characterize the disease progression in multiple sclerosis (MS), as measured by Expanded Disability Status Score (EDSS). Data were collected quarterly from a 96-week phase III

  16. Fitness voter model: Damped oscillations and anomalous consensus.

    Science.gov (United States)

    Woolcock, Anthony; Connaughton, Colm; Merali, Yasmin; Vazquez, Federico

    2017-09-01

    We study the dynamics of opinion formation in a heterogeneous voter model on a complete graph, in which each agent is endowed with an integer fitness parameter k≥0, in addition to its + or - opinion state. The evolution of the distribution of k-values and the opinion dynamics are coupled together, so as to allow the system to dynamically develop heterogeneity and memory in a simple way. When two agents with different opinions interact, their k-values are compared, and with probability p the agent with the lower value adopts the opinion of the one with the higher value, while with probability 1-p the opposite happens. The agent that keeps its opinion (winning agent) increments its k-value by one. We study the dynamics of the system in the entire 0≤p≤1 range and compare with the case p=1/2, in which opinions are decoupled from the k-values and the dynamics is equivalent to that of the standard voter model. When 0≤psystem approaches exponentially fast to the consensus state of the initial majority opinion. The mean consensus time τ appears to grow logarithmically with the number of agents N, and it is greatly decreased relative to the linear behavior τ∼N found in the standard voter model. When 1/2system initially relaxes to a state with an even coexistence of opinions, but eventually reaches consensus by finite-size fluctuations. The approach to the coexistence state is monotonic for 1/2oscillations around the coexistence value. The final approach to coexistence is approximately a power law t^{-b(p)} in both regimes, where the exponent b increases with p. Also, τ increases respect to the standard voter model, although it still scales linearly with N. The p=1 case is special, with a relaxation to coexistence that scales as t^{-2.73} and a consensus time that scales as τ∼N^{β}, with β≃1.45.

  17. Physical Work Demands and Fitness

    DEFF Research Database (Denmark)

    Larsen, Mette Korshøj

    . The effects were evaluated with objective physiological or diurnal data in an intention-to-treat analysis using multi-adjusted mixed models. The results indicated that the intervention led to several improvements in risk factors for cardiovascular disease, e.g. enhanced cardiorespiratory fitness, reduced...... exposed to high relative aerobic workloads obtained more pronounced increases of resting and 24-hour ambulatory blood pressure, an unaltered cardiorespiratory fitness and a reduced sleeping heart rate. The enhanced resting and 24-hour ambulatory blood pressure may be explained as a potential...

  18. Strategic Planning for Management Information Systems.

    Science.gov (United States)

    Ein-Dor, Phillip; Segev, Eli

    1978-01-01

    Two factors predominate in determining the appropriateness of strategic plans for management information systems (MIS)--explicitness (the degree to which the process is conscious, formal, and documented) and situational fit (the degree to which the MIS is compatible with the specific organization and its members). (Author/IRT)

  19. Using Rasch Analysis to Evaluate the Reliability and Validity of the Swallowing Quality of Life Questionnaire: An Item Response Theory Approach.

    Science.gov (United States)

    Cordier, Reinie; Speyer, Renée; Schindler, Antonio; Michou, Emilia; Heijnen, Bas Joris; Baijens, Laura; Karaduman, Ayşe; Swan, Katina; Clavé, Pere; Joosten, Annette Veronica

    2018-02-01

    The Swallowing Quality of Life questionnaire (SWAL-QOL) is widely used clinically and in research to evaluate quality of life related to swallowing difficulties. It has been described as a valid and reliable tool, but was developed and tested using classic test theory. This study describes the reliability and validity of the SWAL-QOL using item response theory (IRT; Rasch analysis). SWAL-QOL data were gathered from 507 participants at risk of oropharyngeal dysphagia (OD) across four European countries. OD was confirmed in 75.7% of participants via videofluoroscopy and/or fiberoptic endoscopic evaluation, or a clinical diagnosis based on meeting selected criteria. Patients with esophageal dysphagia were excluded. Data were analysed using Rasch analysis. Item and person reliability was good for all the items combined. However, person reliability was poor for 8 subscales and item reliability was poor for one subscale. Eight subscales exhibited poor person separation and two exhibited poor item separation. Overall item and person fit statistics were acceptable. However, at an individual item fit level results indicated unpredictable item responses for 28 items, and item redundancy for 10 items. The item-person dimensionality map confirmed these findings. Results from the overall Rasch model fit and Principal Component Analysis were suggestive of a second dimension. For all the items combined, none of the item categories were 'category', 'threshold' or 'step' disordered; however, all subscales demonstrated category disordered functioning. Findings suggest an urgent need to further investigate the underlying structure of the SWAL-QOL and its psychometric characteristics using IRT.

  20. Item Response Theory Models for Wording Effects in Mixed-Format Scales

    Science.gov (United States)

    Wang, Wen-Chung; Chen, Hui-Fang; Jin, Kuan-Yu

    2015-01-01

    Many scales contain both positively and negatively worded items. Reverse recoding of negatively worded items might not be enough for them to function as positively worded items do. In this study, we commented on the drawbacks of existing approaches to wording effect in mixed-format scales and used bi-factor item response theory (IRT) models to…

  1. The role of social capital and community belongingness for exercise adherence: An exploratory study of the CrossFit gym model.

    Science.gov (United States)

    Whiteman-Sandland, Jessica; Hawkins, Jemma; Clayton, Debbie

    2016-08-01

    This is the first study to measure the 'sense of community' reportedly offered by the CrossFit gym model. A cross-sectional study adapted Social Capital and General Belongingness scales to compare perceptions of a CrossFit gym and a traditional gym. CrossFit gym members reported significantly higher levels of social capital (both bridging and bonding) and community belongingness compared with traditional gym members. However, regression analysis showed neither social capital, community belongingness, nor gym type was an independent predictor of gym attendance. Exercise and health professionals may benefit from evaluating further the 'sense of community' offered by gym-based exercise programmes.

  2. Covariances for neutron cross sections calculated using a regional model based on local-model fits to experimental data

    Energy Technology Data Exchange (ETDEWEB)

    Smith, D.L.; Guenther, P.T.

    1983-11-01

    We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references.

  3. Covariances for neutron cross sections calculated using a regional model based on local-model fits to experimental data

    International Nuclear Information System (INIS)

    Smith, D.L.; Guenther, P.T.

    1983-11-01

    We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references

  4. Modelling the association between weight status and social deprivation in English school children: Can physical activity and fitness affect the relationship?

    Science.gov (United States)

    Nevill, Alan M; Duncan, Michael J; Lahart, Ian; Sandercock, Gavin

    2016-11-01

    The association between being overweight/obese and deprivation is a serious concern in English schoolchildren. To model this association incorporating known confounders and to discover whether physical fitness and physical activity may reduce or eliminate this association. Cross-sectional data were collected between 2007-2009, from 8053 10-16 year old children from the East-of-England Healthy Heart Study. Weight status was assessed using waist circumference (cm) and body mass (kg). Deprivation was measured using the Index of Multiple Deprivation (IMD). Confounding variables used in the proportional, allometric models were hip circumference, stature, age and sex. Children's fitness levels were assessed using predicted VO 2 max (20-metre shuttle-run test) and physical activity was estimated using the Physical Activity Questionnaire for Adolescents or Children. A strong association was found between both waist circumference and body mass and the IMD. These associations persisted after controlling for all confounding variables. When the children's physical activity and fitness levels were added to the models, the association was either greatly reduced or, in the case of body mass, absent. To reduce deprivation inequalities in children's weight-status, health practitioners should focus on increasing physical fitness via physical activity in areas of greater deprivation.

  5. On the fit of models to covariances and methodology to the Bulletin.

    Science.gov (United States)

    Bentler, P M

    1992-11-01

    It is noted that 7 of the 10 top-cited articles in the Psychological Bulletin deal with methodological topics. One of these is the Bentler-Bonett (1980) article on the assessment of fit in covariance structure models. Some context is provided on the popularity of this article. In addition, a citation study of methodology articles appearing in the Bulletin since 1978 was carried out. It verified that publications in design, evaluation, measurement, and statistics continue to be important to psychological research. Some thoughts are offered on the role of the journal in making developments in these areas more accessible to psychologists.

  6. Construction of a memory battery for computerized administration, using item response theory.

    Science.gov (United States)

    Ferreira, Aristides I; Almeida, Leandro S; Prieto, Gerardo

    2012-10-01

    In accordance with Item Response Theory, a computer memory battery with six tests was constructed for use in the Portuguese adult population. A factor analysis was conducted to assess the internal structure of the tests (N = 547 undergraduate students). According to the literature, several confirmatory factor models were evaluated. Results showed better fit of a model with two independent latent variables corresponding to verbal and non-verbal factors, reproducing the initial battery organization. Internal consistency reliability for the six tests were alpha = .72 to .89. IRT analyses (Rasch and partial credit models) yielded good Infit and Outfit measures and high precision for parameter estimation. The potential utility of these memory tasks for psychological research and practice willbe discussed.

  7. Experimental Rugged Fitness Landscape in Protein Sequence Space

    Science.gov (United States)

    Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

    2006-01-01

    The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728

  8. Experimental rugged fitness landscape in protein sequence space.

    Science.gov (United States)

    Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

    2006-12-20

    The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

  9. Experimental rugged fitness landscape in protein sequence space.

    Directory of Open Access Journals (Sweden)

    Yuuki Hayashi

    Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

  10. A neutronic feasibility study for LEU conversion of the IR-8 research reactor

    International Nuclear Information System (INIS)

    Deen, J.R.; Hanan, N.A.; Matos, J.E.; Egorenkov, P.M.; Nasonov, V.A.

    1998-01-01

    Equilibrium fuel cycle comparisons for the IR-8 research reactor were made for HEU (90%), HEU (36%), and LEU (19.75%) fuel assembly (FA) designs using three dimensional multi-group diffusion theory models benchmarked to detailed Monte Carlo models of the reactor. Comparisons were made of changes in reactivity, cycle length, average 235 U discharge burnup, thermal neutron flux, and control rod worths for the 90% and 36% enriched IRT-3M fuel assembly and the 19.75% enriched IRT-4M fuel assembly with the same fuel management strategy. The results of these comparisons showed that a uranium density of 3.5 g/cm 3 in the fuel meat would be required in the LEU IRT-4M fuel assembly to match the cycle length of the HEU (90%) IRT-3M FA and an LEU density of 3.7 g/cm 3 is needed to match the cycle length of the HEU (36%) IRT-3M FA. (author)

  11. A hands-on approach for fitting long-term survival models under the GAMLSS framework.

    Science.gov (United States)

    de Castro, Mário; Cancho, Vicente G; Rodrigues, Josemar

    2010-02-01

    In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. In this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

  12. Whole Protein Native Fitness Potentials

    Science.gov (United States)

    Faraggi, Eshel; Kloczkowski, Andrzej

    2013-03-01

    Protein structure prediction can be separated into two tasks: sample the configuration space of the protein chain, and assign a fitness between these hypothetical models and the native structure of the protein. One of the more promising developments in this area is that of knowledge based energy functions. However, standard approaches using pair-wise interactions have shown shortcomings demonstrated by the superiority of multi-body-potentials. These shortcomings are due to residue pair-wise interaction being dependent on other residues along the chain. We developed a method that uses whole protein information filtered through machine learners to score protein models based on their likeness to native structures. For all models we calculated parameters associated with the distance to the solvent and with distances between residues. These parameters, in addition to energy estimates obtained by using a four-body-potential, DFIRE, and RWPlus were used as training for machine learners to predict the fitness of the models. Testing on CASP 9 targets showed that our method is superior to DFIRE, RWPlus, and the four-body potential, which are considered standards in the field.

  13. Predicting the Best Fit: A Comparison of Response Surface Models for Midazolam and Alfentanil Sedation in Procedures With Varying Stimulation.

    Science.gov (United States)

    Liou, Jing-Yang; Ting, Chien-Kun; Mandell, M Susan; Chang, Kuang-Yi; Teng, Wei-Nung; Huang, Yu-Yin; Tsou, Mei-Yung

    2016-08-01

    Selecting an effective dose of sedative drugs in combined upper and lower gastrointestinal endoscopy is complicated by varying degrees of pain stimulation. We tested the ability of 5 response surface models to predict depth of sedation after administration of midazolam and alfentanil in this complex model. The procedure was divided into 3 phases: esophagogastroduodenoscopy (EGD), colonoscopy, and the time interval between the 2 (intersession). The depth of sedation in 33 adult patients was monitored by Observer Assessment of Alertness/Scores. A total of 218 combinations of midazolam and alfentanil effect-site concentrations derived from pharmacokinetic models were used to test 5 response surface models in each of the 3 phases of endoscopy. Model fit was evaluated with objective function value, corrected Akaike Information Criterion (AICc), and Spearman ranked correlation. A model was arbitrarily defined as accurate if the predicted probability is effect-site concentrations tested ranged from 1 to 76 ng/mL and from 5 to 80 ng/mL for midazolam and alfentanil, respectively. Midazolam and alfentanil had synergistic effects in colonoscopy and EGD, but additivity was observed in the intersession group. Adequate prediction rates were 84% to 85% in the intersession group, 84% to 88% during colonoscopy, and 82% to 87% during EGD. The reduced Greco and Fixed alfentanil concentration required for 50% of the patients to achieve targeted response Hierarchy models performed better with comparable predictive strength. The reduced Greco model had the lowest AICc with strong correlation in all 3 phases of endoscopy. Dynamic, rather than fixed, γ and γalf in the Hierarchy model improved model fit. The reduced Greco model had the lowest objective function value and AICc and thus the best fit. This model was reliable with acceptable predictive ability based on adequate clinical correlation. We suggest that this model has practical clinical value for patients undergoing procedures

  14. Estimation of error components in a multi-error linear regression model, with an application to track fitting

    International Nuclear Information System (INIS)

    Fruehwirth, R.

    1993-01-01

    We present an estimation procedure of the error components in a linear regression model with multiple independent stochastic error contributions. After solving the general problem we apply the results to the estimation of the actual trajectory in track fitting with multiple scattering. (orig.)

  15. Item response theory analysis of Centers for Disease Control and Prevention Health-Related Quality of Life (CDC HRQOL) items in adults with arthritis.

    Science.gov (United States)

    Mielenz, Thelma J; Callahan, Leigh F; Edwards, Michael C

    2016-03-12

    Examine the feasibility of performing an item response theory (IRT) analysis on two of the Centers for Disease Control and Prevention health-related quality of life (CDC HRQOL) modules - the 4-item Healthy Days Core Module (HDCM) and the 5-item Healthy days Symptoms Module (HDSM). Previous principal components analyses confirm that the two scales both assess a mix of mental (CDC-MH) and physical health (CDC-PH). The purpose is to conduct item response theory (IRT) analysis on the CDC-MH and CDC-PH scales separately. 2182 patients with self-reported or physician-diagnosed arthritis completed a cross-sectional survey including HDCM and HDSM items. Besides global health, the other 8 items ask the number of days that some statement was true; we chose to recode the data into 8 categories based on observed clustering. The IRT assumptions were assessed using confirmatory factor analysis and the data could be modeled using an unidimensional IRT model. The graded response model was used for IRT analyses and CDC-MH and CDC-PH scales were analyzed separately in flexMIRT. The IRT parameter estimates for the five-item CDC-PH all appeared reasonable. The three-item CDC-MH did not have reasonable parameter estimates. The CDC-PH scale is amenable to IRT analysis but the existing The CDC-MH scale is not. We suggest either using the 4-item Healthy Days Core Module (HDCM) and the 5-item Healthy days Symptoms Module (HDSM) as they currently stand or the CDC-PH scale alone if the primary goal is to measure physical health related HRQOL.

  16. Spreadsheets, Graphing Calculators and the Line of Best Fit

    Directory of Open Access Journals (Sweden)

    Bernie O'Sullivan

    2003-07-01

    One technique that can now be done, almost mindlessly, is the line of best fit. Both the graphing calculator and the Excel spreadsheet produce models for collected data that appear to be very good fits, but upon closer scrutiny, are revealed to be quite poor. This article will examine one such case. I will couch the paper within the framework of a very good classroom investigation that will help generate students’ understanding of the basic principles of curve fitting and will enable them to produce a very accurate model of collected data by combining the technology of the graphing calculator and the spreadsheet.

  17. Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation-Maximization (SAEM) Algorithm.

    Science.gov (United States)

    Chow, Sy-Miin; Lu, Zhaohua; Sherwood, Andrew; Zhu, Hongtu

    2016-03-01

    The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting multivariate nonlinear differential equation models with random effects and unknown initial conditions to irregularly spaced data. A stochastic approximation expectation-maximization algorithm is proposed and its performance is evaluated using a benchmark nonlinear dynamical systems model, namely, the Van der Pol oscillator equations. The empirical utility of the proposed technique is illustrated using a set of 24-h ambulatory cardiovascular data from 168 men and women. Pertinent methodological challenges and unresolved issues are discussed.

  18. GMTR: two-dimensional geo-fit multitarget retrieval model for michelson interferometer for passive atmospheric sounding/environmental satellite observations.

    Science.gov (United States)

    Carlotti, Massimo; Brizzi, Gabriele; Papandrea, Enzo; Prevedelli, Marco; Ridolfi, Marco; Dinelli, Bianca Maria; Magnani, Luca

    2006-02-01

    We present a new retrieval model designed to analyze the observations of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is on board the ENVironmental SATellite (ENVISAT). The new geo-fit multitarget retrieval model (GMTR) implements the geo-fit two-dimensional inversion for the simultaneous retrieval of several targets including a set of atmospheric constituents that are not considered by the ground processor of the MIPAS experiment. We describe the innovative solutions adopted in the inversion algorithm and the main functionalities of the corresponding computer code. The performance of GMTR is compared with that of the MIPAS ground processor in terms of accuracy of the retrieval products. Furthermore, we show the capability of GMTR to resolve the horizontal structures of the atmosphere. The new retrieval model is implemented in an optimized computer code that is distributed by the European Space Agency as "open source" in a package that includes a full set of auxiliary data for the retrieval of 28 atmospheric targets.

  19. Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

    Directory of Open Access Journals (Sweden)

    Yun Wang

    2016-01-01

    Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

  20. CUSUM-based person-fit statistics for adaptive testing

    NARCIS (Netherlands)

    van Krimpen-Stoop, Edith; Meijer, R.R.

    2001-01-01

    Item scores that do not fit an assumed item response theory model may cause the latent trait value to be inaccurately estimated. Several person-fit statistics for detecting nonfitting score patterns for paper-and-pencil tests have been proposed. In the context of computerized adaptive tests (CAT),

  1. CUSUM-based person-fit statistics for adaptive testing

    NARCIS (Netherlands)

    van Krimpen-Stoop, Edith; Meijer, R.R.

    1999-01-01

    Item scores that do not fit an assumed item response theory model may cause the latent trait value to be estimated inaccurately. Several person-fit statistics for detecting nonfitting score patterns for paper-and-pencil tests have been proposed. In the context of computerized adaptive tests (CAT),

  2. Isochrone Fitting of Hubble Photometry in UV–VIS–IR Bands

    Science.gov (United States)

    Barker, Hallie; Paust, Nathaniel E. Q.

    2018-03-01

    We present new isochrone fits to color–magnitude diagrams from Hubble Space Telescope Wide Field Camera 3 and Advanced Camera for Surveys photometry of the globular clusters M13 and M80 in five bands from the ultraviolet to near-infrared. Isochrone fits to the photometry using the Dartmouth Stellar Evolution Program (DSEP), the PAdova and TRieste Stellar Evolution Code (PARSEC), and MESA Isochrones and Stellar Tracks (MIST) are examined to study the isochrone morphology. Additionally, cluster ages, extinctions, and distances are found from the visible-infrared color–magnitude diagrams. We conduct careful qualitative analysis on the inconsistencies of the fits across twelve color combinations of the five observed bands, and find that the (F606W‑F814W) color generally produces very good fits, but that there are large discrepancies when the data is fit using colors including UV bands for all three models. We also find that the best fits in the UV are achieved using MIST isochrones, but that they require metallicities that are lower than the other two models, as well published spectroscopic values. Finally, we directly compare DSEP and PARSEC by performing isochrone-isochrone fitting, and find that, for globular cluster aged populations, similar appearing PARSEC isochrones are on average 1.5 Gyr younger than DSEP isochrones. We find that the two models become less discrepant at lower metallicities.

  3. Fitness Club

    CERN Multimedia

    Fitness Club

    2012-01-01

    Open to All: http://cern.ch/club-fitness  fitness.club@cern.ch Boxing Your supervisor makes your life too tough ! You really need to release the pressure you've been building up ! Come and join the fit-boxers. We train three times a week in Bd 216, classes for beginners and advanced available. Visit our website cern.ch/Boxing General Fitness Escape from your desk with our general fitness classes, to strengthen your heart, muscles and bones, improve you stamina, balance and flexibility, achieve new goals, be more productive and experience a sense of well-being, every Monday, Wednesday and Friday lunchtime, Tuesday mornings before work and Thursday evenings after work – join us for one of our monthly fitness workshops. Nordic Walking Enjoy the great outdoors; Nordic Walking is a great way to get your whole body moving and to significantly improve the condition of your muscles, heart and lungs. It will boost your energy levels no end. Pilates A body-conditioning technique de...

  4. Fitting the e+e- → e+e- lineshape

    International Nuclear Information System (INIS)

    Martinez, M.; Miquel, R.

    1992-01-01

    The implications of different treatments of the e + e - →e + e - cross sections in the context of Z parameter fitting are discussed. We show that fitting with a complete description of the process might become important for an accurate determination of the Z parameters. A fitting formula describing the integrated cross section in terms of the Z parameters is presented. This formula agrees with the most accurate calculations in the Standard Model to within 1 per mil. (orig.)

  5. FITS: a function-fitting program

    Energy Technology Data Exchange (ETDEWEB)

    Balestrini, S.J.; Chezem, C.G.

    1982-01-01

    FITS is an iterating computer program that adjusts the parameters of a function to fit a set of data points according to the least squares criterion and then lists and plots the results. The function can be programmed or chosen from a library that is provided. The library can be expanded to include up to 99 functions. A general plotting routine, contained in the program but useful in its own right, is described separately in an Appendix.

  6. FITTING A THREE DIMENSIONAL PEM FUEL CELL MODEL TO MEASUREMENTS BY TUNING THE POROSITY AND

    DEFF Research Database (Denmark)

    Bang, Mads; Odgaard, Madeleine; Condra, Thomas Joseph

    2004-01-01

    the distribution of current density and further how thisaffects the polarization curve.The porosity and conductivity of the catalyst layer are some ofthe most difficult parameters to measure, estimate and especiallycontrol. Yet the proposed model shows how these two parameterscan have significant influence...... on the performance of the fuel cell.The two parameters are shown to be key elements in adjusting thethree-dimensional model to fit measured polarization curves.Results from the proposed model are compared to single cellmeasurements on a test MEA from IRD Fuel Cells.......A three-dimensional, computational fluid dynamics (CFD) model of a PEM fuel cell is presented. The model consists ofstraight channels, porous gas diffusion layers, porous catalystlayers and a membrane. In this computational domain, most ofthe transport phenomena which govern the performance of the...

  7. Fitness Club

    CERN Multimedia

    Fitness Club

    2011-01-01

    The CERN Fitness Club is organising Zumba Classes on the first Wednesday of each month, starting 7 September (19.00 – 20.00). What is Zumba®? It’s an exhilarating, effective, easy-to-follow, Latin-inspired, calorie-burning dance fitness-party™ that’s moving millions of people toward joy and health. Above all it’s great fun and an excellent work out. Price: 22 CHF/person Sign-up via the following form: https://espace.cern.ch/club-fitness/Lists/Zumba%20Subscription/NewForm.aspx For more info: fitness.club@cern.ch

  8. A Mixture Rasch Model with a Covariate: A Simulation Study via Bayesian Markov Chain Monte Carlo Estimation

    Science.gov (United States)

    Dai, Yunyun

    2013-01-01

    Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying…

  9. Parent Ratings of ADHD Symptoms: Generalized Partial Credit Model Analysis of Differential Item Functioning across Gender

    Science.gov (United States)

    Gomez, Rapson

    2012-01-01

    Objective: Generalized partial credit model, which is based on item response theory (IRT), was used to test differential item functioning (DIF) for the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed.), inattention (IA), and hyperactivity/impulsivity (HI) symptoms across boys and girls. Method: To accomplish this, parents completed…

  10. Fitness for duty: A tried-and-true model for decision making

    International Nuclear Information System (INIS)

    Horn, G.L.

    1989-01-01

    The US Nuclear Regulatory Commission (NRC) rules and regulations pertaining to fitness for duty specify development of programs designed to ensure that nuclear power plant personnel are not under the influence of legal or illegal substances that cause mental or physical impairment of work performance such that public safety is compromised. These regulations specify the type of decision loop to employ in determining the employee's movement through the process of initial restriction of access to the point at which his access authorization is restores. Suggestions are also offered to determine the roles that various components of the organization should take in the decision loop. This paper discusses some implications and labor concerns arising from the suggested role of employee assistance programs (EAPs) in the decision loop for clinical assessment and return-to-work evaluation of chemical testing failures. A model for a decision loop addressing some of the issues raised is presented. The proposed model has been implemented in one nuclear facility and has withstood the scrutiny of an NRC audit

  11. Optimized aerodynamic design process for subsonic transport wing fitted with winglets. [wind tunnel model

    Science.gov (United States)

    Kuhlman, J. M.

    1979-01-01

    The aerodynamic design of a wind-tunnel model of a wing representative of that of a subsonic jet transport aircraft, fitted with winglets, was performed using two recently developed optimal wing-design computer programs. Both potential flow codes use a vortex lattice representation of the near-field of the aerodynamic surfaces for determination of the required mean camber surfaces for minimum induced drag, and both codes use far-field induced drag minimization procedures to obtain the required spanloads. One code uses a discrete vortex wake model for this far-field drag computation, while the second uses a 2-D advanced panel wake model. Wing camber shapes for the two codes are very similar, but the resulting winglet camber shapes differ widely. Design techniques and considerations for these two wind-tunnel models are detailed, including a description of the necessary modifications of the design geometry to format it for use by a numerically controlled machine for the actual model construction.

  12. Exploring the fitness landscape of poliovirus

    Science.gov (United States)

    Bianco, Simone; Acevedo, Ashely; Andino, Raul; Tang, Chao

    2012-02-01

    RNA viruses are known to display extraordinary adaptation capabilities to different environments, due to high mutation rates. Their very dynamical evolution is captured by the quasispecies concept, according to which the viral population forms a swarm of genetic variants linked through mutation, which cooperatively interact at a functional level and collectively contribute to the characteristics of the population. The description of the viral fitness landscape becomes paramount towards a more thorough understanding of the virus evolution and spread. The high mutation rate, together with the cooperative nature of the quasispecies, makes it particularly challenging to explore its fitness landscape. I will present an investigation of the dynamical properties of poliovirus fitness landscape, through both the adoption of new experimental techniques and theoretical models.

  13. Dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria: implications for the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition.

    Science.gov (United States)

    Kerridge, Bradley T; Saha, Tulshi D; Smith, Sharon; Chou, Patricia S; Pickering, Roger P; Huang, Boji; Ruan, June W; Pulay, Attila J

    2011-09-01

    Prior research has demonstrated the dimensionality of Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV) alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria. The purpose of this study was to examine the dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria. In addition, we assessed the impact of elimination of the legal problems abuse criterion on the information value of the aggregate abuse and dependence criteria, another proposed change for DSM-IV currently lacking empirical justification. Factor analyses and item response theory (IRT) analyses were used to explore the unidimisionality and psychometric properties of hallucinogen and inhalant/solvent abuse and dependence criteria using a large representative sample of the United States (U.S.) general population. Hallucinogen and inhalant/solvent abuse and dependence criteria formed unidimensional latent traits. For both substances, IRT models without the legal problems abuse criterion demonstrated better fit than the corresponding model with the legal problem abuse criterion. Further, there were no differences in the information value of the IRT models with and without the legal problems abuse criterion, supporting the elimination of that criterion. No bias in the new diagnoses was observed by sex, age and race-ethnicity. Consistent with findings for alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria, hallucinogen and inhalant/solvent criteria reflect underlying dimensions of severity. The legal problems criterion associated with each of these substance use disorders can be eliminated with no loss in informational value and an advantage of parsimony. Taken together, these findings support the changes to substance use disorder diagnoses recommended by the DSM-V Substance and Related Disorders Workgroup, that is, combining DSM-IV abuse and dependence criteria and eliminating the legal problems abuse

  14. Probabilistic model fitting for spatio-temporal variability studies of precipitation: the Sara-Brut system - a case study

    International Nuclear Information System (INIS)

    Dorado Delgado, Jennifer; Burbano Criollo, Juan Carlos; Molina Tabares, Jose Manuel; Carvajal Escobar, Yesid; Aristizabal, Hector Fabio

    2006-01-01

    In this study, space and time variability of monthly and annual rainfall was analyzed for the downstream influence zone of a Colombian supply-regulation reservoir, Sara-Brut, located on the Cauca valley department. Monthly precipitation data from 18 gauge stations and for a 29-year record (1975-2003) were used. These data were processed by means of time series completion, consistency analyses and sample statistics computations. Theoretical probabilistic distribution models such as Gumbel, normal, lognormal and wake by, and other empirical distributions such as Weibull and Landwehr were applied in order to fit the historical precipitation data set. The fit standard error (FSE) was used to test the goodness of fit of the theoretical distribution models and to choose the best of this probabilistic function. The wake by approach showed the best goodness of fit in 89% of the total gauges taken into account. Time variability was analyzed by means of wake by estimated values of monthly and annual precipitation associated with return periods of 1,052, 1,25, 2, 10, 20 and 50 years. Precipitation space variability is presents by means of ArcGis v8.3 and using krigging as interpolation method. In general terms the results obtained from this study show significant distribution variability in precipitation over the whole area, and particularity, the formation of dry and humid nucleus over the northeastern strip and microclimates at the southwestern and central zone of the study area were observed, depending on the season of year. The mentioned distribution pattern is likely caused by the influence of pacific wind streams, which come from the Andean western mountain range. It is expected that the results from this work be helpful for future planning and hydrologic project design

  15. Self-Fitting Hearing Aids

    Directory of Open Access Journals (Sweden)

    Gitte Keidser

    2016-04-01

    Full Text Available A self-contained, self-fitting hearing aid (SFHA is a device that enables the user to perform both threshold measurements leading to a prescribed hearing aid setting and fine-tuning, without the need for audiological support or access to other equipment. The SFHA has been proposed as a potential solution to address unmet hearing health care in developing countries and remote locations in the developed world and is considered a means to lower cost and increase uptake of hearing aids in developed countries. This article reviews the status of the SFHA and the evidence for its feasibility and challenges and predicts where it is heading. Devices that can be considered partly or fully self-fitting without audiological support were identified in the direct-to-consumer market. None of these devices are considered self-contained as they require access to other hardware such as a proprietary interface, computer, smartphone, or tablet for manipulation. While there is evidence that self-administered fitting processes can provide valid and reliable results, their success relies on user-friendly device designs and interfaces and easy-to-interpret instructions. Until these issues have been sufficiently addressed, optional assistance with the self-fitting process and on-going use of SFHAs is recommended. Affordability and a sustainable delivery system remain additional challenges for the SFHA in developing countries. Future predictions include a growth in self-fitting products, with most future SFHAs consisting of earpieces that connect wirelessly with a smartphone and providers offering assistance through a telehealth infrastructure, and the integration of SFHAs into the traditional hearing health-care model.

  16. Estimating the fitness cost and benefit of cefixime resistance in Neisseria gonorrhoeae to inform prescription policy: A modelling study.

    Directory of Open Access Journals (Sweden)

    Lilith K Whittles

    2017-10-01

    Full Text Available Gonorrhoea is one of the most common bacterial sexually transmitted infections in England. Over 41,000 cases were recorded in 2015, more than half of which occurred in men who have sex with men (MSM. As the bacterium has developed resistance to each first-line antibiotic in turn, we need an improved understanding of fitness benefits and costs of antibiotic resistance to inform control policy and planning. Cefixime was recommended as a single-dose treatment for gonorrhoea from 2005 to 2010, during which time resistance increased, and subsequently declined.We developed a stochastic compartmental model representing the natural history and transmission of cefixime-sensitive and cefixime-resistant strains of Neisseria gonorrhoeae in MSM in England, which was applied to data on diagnoses and prescriptions between 2008 and 2015. We estimated that asymptomatic carriers play a crucial role in overall transmission dynamics, with 37% (95% credible interval CrI 24%-52% of infections remaining asymptomatic and untreated, accounting for 89% (95% CrI 82%-93% of onward transmission. The fitness cost of cefixime resistance in the absence of cefixime usage was estimated to be such that the number of secondary infections caused by resistant strains is only about half as much as for the susceptible strains, which is insufficient to maintain persistence. However, we estimated that treatment of cefixime-resistant strains with cefixime was unsuccessful in 83% (95% CrI 53%-99% of cases, representing a fitness benefit of resistance. This benefit was large enough to counterbalance the fitness cost when 31% (95% CrI 26%-36% of cases were treated with cefixime, and when more than 55% (95% CrI 44%-66% of cases were treated with cefixime, the resistant strain had a net fitness advantage over the susceptible strain. Limitations include sparse data leading to large intervals on key model parameters and necessary assumptions in the modelling of a complex epidemiological process

  17. Damage Identification of Bridge Based on Chebyshev Polynomial Fitting and Fuzzy Logic without Considering Baseline Model Parameters

    Directory of Open Access Journals (Sweden)

    Yu-Bo Jiao

    2015-01-01

    Full Text Available The paper presents an effective approach for damage identification of bridge based on Chebyshev polynomial fitting and fuzzy logic systems without considering baseline model data. The modal curvature of damaged bridge can be obtained through central difference approximation based on displacement modal shape. Depending on the modal curvature of damaged structure, Chebyshev polynomial fitting is applied to acquire the curvature of undamaged one without considering baseline parameters. Therefore, modal curvature difference can be derived and used for damage localizing. Subsequently, the normalized modal curvature difference is treated as input variable of fuzzy logic systems for damage condition assessment. Numerical simulation on a simply supported bridge was carried out to demonstrate the feasibility of the proposed method.

  18. TASK-TECHNOLOGY FIT AND PERSON-JOB FIT: A BEAUTY CONTEST TO IMPROVE THE SUCCESS OF INFORMATION SYSTEMS

    OpenAIRE

    Suryani, Woro Dwi; Sumiyana, Sumiyana

    2015-01-01

    This study raises the issue that information system success could be enhanced by complementingother factors. This study investigates the success of information systems by inducing2the task-technology fit (TTF) and person-job fit (PJF) into the DeLone and McLean model. Thisstudy aims to examine, among the two induced factors, which one is able to explain andimprove the success of the information systems implementation.The results of this study indicate that the TTF explains the models’ goodnes...

  19. A new three-dimensional track fit with multiple scattering

    International Nuclear Information System (INIS)

    Berger, Niklaus; Kozlinskiy, Alexandr; Kiehn, Moritz; Schöning, André

    2017-01-01

    Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.

  20. A new three-dimensional track fit with multiple scattering

    Energy Technology Data Exchange (ETDEWEB)

    Berger, Niklaus; Kozlinskiy, Alexandr [Physikalisches Institut, Heidelberg University, Heidelberg (Germany); Institut für Kernphysik and PRISMA cluster of excellence, Mainz University, Mainz (Germany); Kiehn, Moritz; Schöning, André [Physikalisches Institut, Heidelberg University, Heidelberg (Germany)

    2017-02-01

    Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.