| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 416340 | Computational Statistics & Data Analysis | 2006 | 19 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Jan de Leeuw,