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Rasch analysis: Estimation and tests with raschtest

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  • 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.

Suggested Citation

  • Jean-Benoit Hardouin, 2007. "Rasch analysis: Estimation and tests with raschtest," Stata Journal, StataCorp LP, vol. 7(1), pages 22-44, February.
    • Handle: RePEc:tsj:stataj:v:7:y:2007:i:1:p:22-44
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    References listed on IDEAS

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    8. 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.
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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.
    2. Irina Kunovskaya & Brenda Cude & Natalia Alexeev, 2014. "Evaluation of a Financial Literacy Test Using Classical Test Theory and Item Response Theory," Journal of Family and Economic Issues, Springer, vol. 35(4), pages 516-531, December.
    3. Dawit G. Ayele & Temesgen Zewotir & Henry Mwambi, 2014. "Using Rasch Modeling to Re-Evaluate Rapid Malaria Diagnosis Test Analyses," IJERPH, MDPI, vol. 11(7), pages 1-11, June.
    4. Xiaohui Zheng & Sophia Rabe-Hesketh, 2007. "Estimating parameters of dichotomous and ordinal item response models with gllamm," Stata Journal, StataCorp LP, vol. 7(3), pages 313-333, September.
    5. Monica Szeles & Alessio Fusco, 2013. "Item response theory and the measurement of deprivation: evidence from Luxembourg data," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(3), pages 1545-1560, April.

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