Factor analysis versus multi-dimensional scaling: binary choice roll-call voting and the US Supreme Court

We evaluate factor analysis and multi-dimensional scaling (MDS) as tools for the analysis of voter decisions over a series of dichotomous choices. We simulate binary voting data with a known form and illustrate that standard factor analyses of these types of data yield additional artifactual dimensions. This effect may be exacerbated by the choice of inter-voter measures of similarity used as input. These results call in question the conclusions of others based on standard factor analyses of empirical voting data from the US Supreme Court. We demonstrate that MDS methods produce more parsimonious descriptions of these data. © 2002 Elsevier Science B.V. All rights reserved.