Multidimensional Item Response Theory Modeling of Binary Data: Large Sample Properties of NOHARM Estimates

Alberto Maydeu-Olivares ()

Journal of Educational and Behavioral Statistics, 2001, vol. 26, issue 1, 51-71

Abstract: NOHARM is a program that performs factor analysis for dichotomous variables assuming that these arise from an underlying multinormal distribution. Parameter estimates are obtained by minimizing an unweighted least squares function of the first- and second-order marginal proportions. Here, large sample standard errors for restricted as well as rotated unrestricted factor solutions are given. Also a test of the goodness of fit of the model to the first- and second-order marginals of the contingency table is proposed. In a simulation study, it was found that for small models, accurate parameter estimates, standard errors, and goodness-of-fit tests can be obtained with as few as 100 observations. Furthermore, NOHARM estimates, standard errors, and goodness-of-fit tests are comparable to those obtained using a related LISREL procedure.

Keywords: multidimensional normal ogive model; categorical data analysis; asymptotic theory; limited information (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986026001051 (text/html)

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:sae:jedbes:v:26:y:2001:i:1:p:51-71

DOI: 10.3102/10769986026001051

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().