MMSRM: Stata module to estimate Multidimensional Marginally Sufficient Rasch Model (MMSRM)
Jean-Benoit Hardouin ()
Statistical Software Components from Boston College Department of Economics
Abstract:
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.
Language: Stata
Requires: Stata version 8.0
Keywords: Rasch model; MMSRM; IRT; Multidimensional model; MML; GEE (search for similar items in EconPapers)
Date: 2005-07-04, Revised 2013-05-08
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 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
References: Add references at CitEc
Citations:
Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/m/mmsrm.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/m/mmsrm.hlp help file (text/plain)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s453103
Ordering information: This software item can be ordered from
http://repec.org/docs/ssc.php
Access Statistics for this software item
More software in Statistical Software Components from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().