Recovering a Basic Space from Issue Scales in R

Keith T. Poole, Jeffrey B. Lewis, Howard Rosenthal, James Lo, Royce Carroll

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Abstract

basicspace is an R package that conducts Aldrich-McKelvey and Blackbox scaling to recover estimates of the underlying latent dimensions of issue scale data. We illustrate several applications of the package to survey data commonly used in the social sciences. Monte Carlo tests demonstrate that the procedure can recover latent dimensions and reproduce the matrix of responses at moderate levels of error and missing data.

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