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Department of Statistics, UCLA

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Principal Component Analysis of Binary Data. Applications to Roll-Call-Analysis

Abstract

We compute the maximum likelihood estimates of a principal component analysis on the logit or probit scalem using a majorization algorithm that computes a sequence of singular value decompositions. The technique is applied to 2001 house and senate roll call data and compared with other techniques for roll call analysis.

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