Rasch analysis: Estimation and tests with raschtest
Jean-Benoit Hardouin
Department of Biomathematics and Biostatistics
Faculty of Pharmaceutical Sciences
University of Nantes, Nantes, France
[email protected]
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Abstract. Analyzing latent variables is becoming more and more important in several
fields, such as clinical research, psychology, educational sciences,
ecology, and epidemiology. The item response theory allows analyzing latent
variables measured by questionnaires of items with binary or ordinal
responses. The Rasch model is the best known model of this theory for binary
responses. Although one can estimate the parameters of the Rasch model with
the clogit or xtlogit command (or with the unofficial
gllamm command), these commands require special data preparation. The
proposed raschtest command easily allows estimating the parameters of the
Rasch model and fitting the resulting model.
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Jean-Benoit Hardouin
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raschtest, Rasch model, generalized estimating equations, conditional maximum likelihood method, marginal maximum likelihood method, Andersen Z test, van den Wollenberg Q1 test, R1c, R1m, fit tests, item response theory, U test, splitting test, item characteristics curves
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