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Rasch analysis: Estimation and tests with raschtest

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Author Info

  • Jean-Benoit Hardouin

    () (Department of Biomathematics and Biostatistics, University of Nantes)

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 com- mand (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. Copyright 2007 by StataCorp LP.

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Bibliographic Info

Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 7 (2007)
Issue (Month): 1 (February)
Pages: 22-44
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:tsj:stataj:v:7:y:2007:i:1:p:22-44

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For corrections or technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research

Keywords: raschtest; Rasch model; generalized estimating equations; conditional maximum likelihood method; marginal maximum likelihood method; An- dersen 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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Cited by:
  1. Raileanu Szeles, Monica & Fusco, Alessio, 2009. "Item response theory and the measurement of deprivation: Evidence from PSELL-3," IRISS Working Paper Series 2009-05, IRISS at CEPS/INSTEAD.

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