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A modular approach for item response theory modeling with the r package flirt

The new R package flirt is introduced for flexible item response theory IRT modeling of psychological, educational, and behavior assessment data. The graphical model framework allows for efficient maximum likelihood estimation. The key feature of flirt is its modular approach to facilitate convenient and flexible model specifications. Researchers can construct customized IRT models by simply selecting various modeling modules, such as parametric forms, of dimensions, item and person covariates, person groups, link functions, etc.

In this paper, we describe major features of flirt and provide examples to illustrate how flirt works in practice. Please enable it to take advantage of the complete set of features! Clipboard, Search History, and several other advanced features are temporarily unavailable. Search: Search.

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Abstract The new R package flirt is introduced for flexible item response theory IRT modeling of psychological, educational, and behavior assessment data. Similar articles A generalized item response tree model for psychological assessments. Jeon M, De Boeck P. Jeon M, et al. Behav Res Methods. PMID: Formulating latent growth using an explanatory item response model approach. Wilson M, et al. J Appl Meas. Rockwood NJ, Jeon M. Rockwood NJ, et al.

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Multivariate Behav Res. Epub Apr Response style analysis with threshold and multi-process IRT models: A review and tutorial. Br J Math Stat Psychol.

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PMID: Review. The value of item response theory in clinical assessment: a review. Thomas ML. Epub Jul See all similar articles. Park M, Wu AD. Park M, et al. Educ Psychol Meas. Epub Feb MeSH terms Algorithms Actions.

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Behavior Actions. Educational Measurement Actions. Humans Actions. Likelihood Functions Actions. Linear Models Actions.

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Nonlinear Dynamics Actions. Psychological Theory Actions. Full text links [x] Springer. Copy Download.