Journal
COMPUTATIONAL STATISTICS & DATA ANALYSIS
Volume 50, Issue 1, Pages 21-39Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.csda.2004.07.010
Keywords
multivariate analysis; factor analysis; binary data; item response models; applications to social sciences
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The maximum-likelihood estimates of a principal component analysis on the logit or probit scale are computed using majorization algorithms that iterate a sequence of weighted or unweighted singular value decompositions. The relation with similar methods in item response theory, roll call analysis, and binary choice analysis is discussed. The technique is applied to 2001 US House roll call data. (c) 2004 Elsevier B.V. All rights reserved.
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