Rasch analysis: Estimation and tests with raschtest
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.
Volume (Year): 7 (2007)
Issue (Month): 1 (February)
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References listed on IDEAS
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- Arnold Wollenberg, 1982. "Two new test statistics for the rasch model," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 123-140, June.
- Ivo Molenaar, 1983. "Some improved diagnostics for failure of the Rasch model," Psychometrika, Springer;The Psychometric Society, vol. 48(1), pages 49-72, March.
- Ghosh, Malay, 1995. "Inconsistent maximum likelihood estimators for the Rasch model," Statistics & Probability Letters, Elsevier, vol. 23(2), pages 165-170, May.
- Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "GLLAMM Manual," U.C. Berkeley Division of Biostatistics Working Paper Series 1160, Berkeley Electronic Press.
- Rizopoulos, Dimitris, 2006. "ltm: An R Package for Latent Variable Modeling and Item Response Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i05).
- Henk Kelderman & Carl Rijkes, 1994. "Loglinear multidimensional IRT models for polytomously scored items," Psychometrika, Springer;The Psychometric Society, vol. 59(2), pages 149-176, June.
- Cees Glas, 1988. "The derivation of some tests for the rasch model from the multinomial distribution," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 525-546, December.
- Herbert Matschinger, 2006. "Estimating IRT models with gllamm," German Stata Users' Group Meetings 2006 03, Stata Users Group.
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