Latent Variable Models for Scaling and Clustering

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Ahlquist, John S., and Christian Breunig. 2012. “Model-Based Clustering and Typologies in the Social Sciences.” Political Analysis 20 (1): 92–112. http://doi.org/10.1093/pan/mpr039.
Bafumi, Joseph, Andrew Gelman, David Park, and Noah Kaplan. 2005. “Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation.” Political Analysis 13: 171–87.
Bailey, Michael A. 2007. “Comparable Preference Estimates across Time and Institutions for the Court, Congress, and Presidency.” American Journal of Political Science 51: 433–48.
Clinton, Joshua, Simon Jackman, and Douglas Rivers. 2004. “The Statistical Analysis of Roll Call Data.” American Political Science Review 98: 355–70.
Linzer, Drew A., and Jeffrey Lewis. 2011. “PoLCA: An R Package for Polytomous Variable Latent Class Analysis.” Journal of Statistical Software 42: 1–29.
Martin, Andrew D., and Kevin M. Quinn. 2002. “Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999.” Political Analysis 10: 134–53.
Poole, Keith T. 2005. Spatial Models of Parliamentary Voting. Cambridge: Cambridge University Press.
Poole, Keith T., and Howard Rosenthal. 1985. “A Spatial Model for Legislative Roll Call Analysis.” American Journal of Political Science 29: 357–84.