IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

Rasch analysis: Estimation and tests with raschtest

  • Jean-Benoit Hardouin


    (Department of Biomathematics and Biostatistics, University of Nantes)

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.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

File URL:
Download Restriction: no

Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 7 (2007)
Issue (Month): 1 (February)
Pages: 22-44

in new window

Handle: RePEc:tsj:stataj:v:7:y:2007:i:1:p:22-44
Contact details of provider: Web page:

Order Information: Web:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Ghosh, Malay, 1995. "Inconsistent maximum likelihood estimators for the Rasch model," Statistics & Probability Letters, Elsevier, vol. 23(2), pages 165-170, May.
  2. 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.
  3. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "GLLAMM Manual," U.C. Berkeley Division of Biostatistics Working Paper Series 1160, Berkeley Electronic Press.
  4. Arnold Wollenberg, 1982. "Two new test statistics for the rasch model," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 123-140, June.
  5. Herbert Matschinger, 2006. "Estimating IRT models with gllamm," German Stata Users' Group Meetings 2006 03, Stata Users Group.
  6. 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.
  7. 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).
  8. Ivo Molenaar, 1983. "Some improved diagnostics for failure of the Rasch model," Psychometrika, Springer;The Psychometric Society, vol. 48(1), pages 49-72, March.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:7:y:2007:i:1:p:22-44. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)

or (Lisa Gilmore)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.