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Applying a Mixture Rasch Model‐Based Approach to Standard Setting
Educational Measurement: Issues and Practice, 2023AbstractThe subjective aspect of standard‐setting is often criticized, yet data‐driven standard‐setting methods are rarely applied. Therefore, we applied a mixture Rasch model approach to setting performance standards across several testing programs of various sizes and compared the results to existing passing standards derived from traditional ...
Michael R. Peabody +2 more
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Mixture Rasch Models With Joint Maximum Likelihood Estimation
Educational and Psychological Measurement, 2010 This 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 ...
John T. Willse
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Estimation of Mixture Rasch Models from Skewed Latent Ability Distributions
Measurement: Interdisciplinary Research and Perspectives, 2020Mixture Rasch (MixRasch) models conventionally assume normal distributions for latent ability. Previous research has shown that the assumption of normality is often unmet in educational and psychol...
Tugba Karadavut +2 more
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A Mixture Rasch Model With Item Response Time Components
Applied Psychological Measurement, 2010 An examinee faced with a test item will engage in solution behavior or rapid-guessing behavior. These qualitatively different test-taking behaviors bias parameter estimates for item response models that do not control for such behavior. A mixture Rasch model with item response time components was proposed and evaluated through application to real test ...
J. Patrick Meyer
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Psychometrika, 2003
A normally distributed person-fit index is proposed for detecting aberrant response patterns in latent class models and mixture distribution IRT models for dichotomous and polytomous data.This article extends previous work on the null distribution of person-fit indices for the dichotomous Rasch model to a number of models for categorical data.
von Davier, Matthias, Molenaar, Ivo W.
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A normally distributed person-fit index is proposed for detecting aberrant response patterns in latent class models and mixture distribution IRT models for dichotomous and polytomous data.This article extends previous work on the null distribution of person-fit indices for the dichotomous Rasch model to a number of models for categorical data.
von Davier, Matthias, Molenaar, Ivo W.
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A Mixture Rasch Model–Based Computerized Adaptive Test for Latent Class Identification
Applied Psychological Measurement, 2012This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback–Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions.
Hong Jiao +3 more
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DIFFERENT APPROACHES TO COVARIATE INCLUSION IN THE MIXTURE RASCH MODEL [PDF]
, 2014 The 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).
Li, Tongyun
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Multivariate and Mixture Distribution Rasch Models
2007Matthias von Davier, Claus H. Carstensen
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A mixture Rasch facets model for rater’s illusory halo effects
Behavior Research Methods, 2022A rater's overall impression of a ratee's essay (or other assessment) can influence ratings on multiple criteria to yield excessively similar ratings (halo effect). However, existing analytic methods fail to identify whether similar ratings stem from homogeneous criteria (true halo) or rater bias (illusory halo).
Kuan-Yu Jin, Ming Ming Chiu
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Mixture Distribution Rasch Models
1995This chapter deals with the generalization of the Rasch model to a discrete mixture distribution model. Its basic assumption is that the Rasch model holds within subpopulations of individuals, but with different parameter values in each subgroup. These subpopulations are not defined by manifest indicators, rather they have to be identified by applying ...
Jürgen Rost, Matthias von Davier
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