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Mixture-Distribution and HYBRID Rasch Models
2007This chapter provides an overview of mixture-distribution Rasch models (RMs) and HYBRID RMs and their extensions. Discrete mixture-distribution IRT models assume that the observed data were drawn from an unobservable mixture of populations. Within each of these populations, a different item response model may hold (HYBRID models), or models with ...
Matthias von Davier, Kentaro Yamamoto
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Analyzing Job Analysis Data Using Mixture Rasch Models
International Journal of Testing, 2018An important piece of validity evidence to support the use of credentialing exams comes from performing a job analysis of the profession.
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Survey analysis with mixture Rasch models.
Journal of applied measurement, 2014This research provides a demonstration of the utility of mixture Rasch models (MRMs) for the analysis of survey data. Specifically, a framework based on a mixture partial credit model (MPCM) will be presented. MRMs are able to provide information regarding latent classes (subpopulations without manifest grouping variables) and separate item parameter ...
Andrew D, Dallas, John T, Willse
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Loglinear Multivariate and Mixture Rasch Models
2007In this chapter, Rasch models (RMs) are derived from a stochastic subject model. Fixed-effects RMs are shown to be equivalent to loglinear models with raw-score variables; random-effects RMs are equivalent to loglinear models with latent class variables. Within the larger framework of loglinear models, various extensions of the RM can be formulated. We
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Mixture Rasch Models With Joint Maximum Likelihood Estimation
Educational and Psychological Measurement, 2010This research provides a demonstration of the utility of mixture Rasch models. Specifically, a model capable of estimating a mixture partial credit model using joint maximum likelihood is presented. Like the partial credit model, the mixture partial credit model has the beneficial feature of being appropriate for analysis of assessment data containing
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Understanding and estimating multivariate mixed and mixture Rasch models as loglinear models
, 2005 Henk Kelderman
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Testing the Rasch model by means of the mixture fit index
British Journal of Mathematical and Statistical Psychology, 2006proposed a new index of fit for contingency table analysis. Using the overparametrized two‐component mixture, where the first component with weight 1− w represents the model to be tested and the second component with weight w is unstructured, the ...
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When raters generalize: Examining sources of halo effects with mixture Rasch facets models
Behavior Research MethodsHalo effects are commonly considered a cognitive or judgmental bias leading to rating error when raters assign scores to persons or performances on multiple criteria. Though a long tradition of research has pointed to possible sources of halo effects, measurement models for identifying these sources and detecting halo have been lacking.
Kuan-Yu Jin, Thomas Eckes
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DIFFERENT APPROACHES TO COVARIATE INCLUSION IN THE MIXTURE RASCH MODEL
2014The present dissertation project investigates different approaches to adding covariates and the impact in fitting mixture item response theory (IRT) models. Mixture IRT models serve as an important methodology for tackling several important psychometric issues in test development, including detecting latent differential item functioning (DIF).
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