Literature DB >> 12924814

A nonlinear mixed model framework for item response theory.

Frank Rijmen1, Francis Tuerlinckx, Paul De Boeck, Peter Kuppens.   

Abstract

Mixed models take the dependency between observations based on the same cluster into account by introducing 1 or more random effects. Common item response theory (IRT) models introduce latent person variables to model the dependence between responses of the same participant. Assuming a distribution for the latent variables, these IRT models are formally equivalent with nonlinear mixed models. It is shown how a variety of IRT models can be formulated as particular instances of nonlinear mixed models. The unifying framework offers the advantage that relations between different IRT models become explicit and that it is rather straightforward to see how existing IRT models can be adapted and extended. The approach is illustrated with a self-report study on anger.

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Year:  2003        PMID: 12924814     DOI: 10.1037/1082-989x.8.2.185

Source DB:  PubMed          Journal:  Psychol Methods        ISSN: 1082-989X


  35 in total

1.  Misuse of the linear mixed model when evaluating risk factors of cognitive decline.

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2.  Validity of an abbreviated quality of life enjoyment and satisfaction questionnaire (Q-LES-Q-18) for schizophrenia, schizoaffective, and mood disorder patients.

Authors:  Michael Ritsner; Rena Kurs; Anatoly Gibel; Yael Ratner; Jean Endicott
Journal:  Qual Life Res       Date:  2005-09       Impact factor: 4.147

3.  Validating, improving reliability, and estimating correlation of the four subscales in the WHOQOL-BREF using multidimensional Rasch analysis.

Authors:  Wen-Chung Wang; Grace Yao; Yih-Jian Tsai; Jung-Der Wang; Ching-Lin Hsieh
Journal:  Qual Life Res       Date:  2006-05       Impact factor: 4.147

4.  Rasch Trees: A New Method for Detecting Differential Item Functioning in the Rasch Model.

Authors:  Carolin Strobl; Julia Kopf; Achim Zeileis
Journal:  Psychometrika       Date:  2013-12-19       Impact factor: 2.500

5.  Polytomous Item Explanatory Item Response Theory Models.

Authors:  Jinho Kim; Mark Wilson
Journal:  Educ Psychol Meas       Date:  2019-12-13       Impact factor: 2.821

6.  A Variational Maximization-Maximization Algorithm for Generalized Linear Mixed Models with Crossed Random Effects.

Authors:  Minjeong Jeon; Frank Rijmen; Sophia Rabe-Hesketh
Journal:  Psychometrika       Date:  2017-02-28       Impact factor: 2.500

7.  IRT in SPSS Using the SPIRIT Macro.

Authors:  Jack DiTrapani; Nicholas Rockwood; Minjeong Jeon
Journal:  Appl Psychol Meas       Date:  2017-10-06

8.  A Mixed-effects Location-Scale Model for Ordinal Questionnaire Data.

Authors:  Donald Hedeker; Robin J Mermelstein; Hakan Demirtas; Michael L Berbaum
Journal:  Health Serv Outcomes Res Methodol       Date:  2016-04-11

9.  Robust Bayesian inference for multivariate longitudinal data by using normal/independent distributions.

Authors:  Sheng Luo; Junsheng Ma; Karl D Kieburtz
Journal:  Stat Med       Date:  2013-03-11       Impact factor: 2.373

10.  An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

Authors:  Carolin Strobl; James Malley; Gerhard Tutz
Journal:  Psychol Methods       Date:  2009-12
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