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Ihnwhi Heo; Fan Jia; Sarah Depaoli – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The Bayesian piecewise growth model (PGM) is a useful class of models for analyzing nonlinear change processes that consist of distinct growth phases. In applications of Bayesian PGMs, it is important to accurately capture growth trajectories and carefully consider knot placements. The presence of missing data is another challenge researchers…
Descriptors: Bayesian Statistics, Goodness of Fit, Data Analysis, Models
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Montoya, Amanda K.; Edwards, Michael C. – Educational and Psychological Measurement, 2021
Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the…
Descriptors: Goodness of Fit, Factor Analysis, Cutting Scores, Correlation
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Pan, Tianshu; Yin, Yue – Applied Measurement in Education, 2017
In this article, we propose using the Bayes factors (BF) to evaluate person fit in item response theory models under the framework of Bayesian evaluation of an informative diagnostic hypothesis. We first discuss the theoretical foundation for this application and how to analyze person fit using BF. To demonstrate the feasibility of this approach,…
Descriptors: Bayesian Statistics, Goodness of Fit, Item Response Theory, Monte Carlo Methods
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Dardick, William R.; Mislevy, Robert J. – Educational and Psychological Measurement, 2016
A new variant of the iterative "data = fit + residual" data-analytical approach described by Mosteller and Tukey is proposed and implemented in the context of item response theory psychometric models. Posterior probabilities from a Bayesian mixture model of a Rasch item response theory model and an unscalable latent class are expressed…
Descriptors: Bayesian Statistics, Probability, Data Analysis, Item Response Theory
Monroe, Scott; Cai, Li – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
In Ramsay curve item response theory (RC-IRT, Woods & Thissen, 2006) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's (1981) EM algorithm, which yields maximum marginal likelihood estimates. This method, however,…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Statistical Inference, Models
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Verkuilen, Jay; Smithson, Michael – Journal of Educational and Behavioral Statistics, 2012
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…
Descriptors: Responses, Regression (Statistics), Statistical Analysis, Models
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Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas – Multivariate Behavioral Research, 2011
The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…
Descriptors: Monte Carlo Methods, Patients, Probability, Item Response Theory
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Nylund, Karen L.; Asparouhov, Tihomir; Muthen, Bengt O. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study…
Descriptors: Test Items, Monte Carlo Methods, Program Effectiveness, Data Analysis
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Velicer, Wayne F.; And Others – Multivariate Behavioral Research, 1982
Factor analysis, image analysis, and principal component analysis are compared with respect to the factor patterns they would produce under various conditions. The general conclusion that is reached is that the three methods produce results that are equivalent. (Author/JKS)
Descriptors: Comparative Analysis, Data Analysis, Factor Analysis, Goodness of Fit
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Kim, Sooyeon; Kyllonen, Patrick C. – ETS Research Report Series, 2006
The Standardized Letter of Recommendation (SLR), a 28-item form, was created by ETS to supplement the qualitative rating of graduate school applicants' nonacademic qualities with a quantitative approach. The purpose of this study was to evaluate the following psychometric properties of the SLR using the Rasch rating-scale model: dimensionality,…
Descriptors: Item Response Theory, Rating Scales, Data Analysis, Models