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MMSRM: Stata module to estimate Multidimensional Marginally Sufficient Rasch Model (MMSRM)


  • Jean-Benoit Hardouin

    (University of Nantes, France)

Programming Language



mmsrm estimates by marginal maximum likelihood (MML) or generalized estimating equations (GEE) the parameters of the Multidimensional Marginally Sufficient Rasch Model (MMSRM). This Item Response Model (IRM) accepts one or several latent traits and is a particular multidimensionnal extension of the Rasch model. In this model, the items are separated in Q groups and each group of items is linked to one and only one latent trait. Each group fits a Rasch model relatively to the corresponding latent trait, so the score computed in each group of item is a sufficient statistics of this latent trait (to a specific value of this score is associated only one value for the latent trait). The program allows computing the parameter of a MMSRM with less than 4 latent traits. To improve the time of computing, the difficulty parameters are estimated in each unidimensional Rasch model and used as an offset variable to estimate the parameters of the distribution of the multidimensional latent trait. This model allows estimating the correlations between different latent traits measured by Rasch models.

Suggested Citation

  • Jean-Benoit Hardouin, 2005. "MMSRM: Stata module to estimate Multidimensional Marginally Sufficient Rasch Model (MMSRM)," Statistical Software Components S453103, Boston College Department of Economics, revised 08 May 2013.
  • Handle: RePEc:boc:bocode:s453103
    Note: This module should be installed from within Stata by typing "ssc install mmsrm". The module is made available under terms of the GPL v3 ( Windows users should not attempt to download these files with a web browser.

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