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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
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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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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