Using Bayesian Aldrich-McKelvey Scaling to Study Citizens’ Ideological Preferences and Perceptions
38 Pages Posted: 14 May 2019
Date Written: July 2, 2014
Aldrich-McKelvey scaling is a powerful method that corrects for differential item functioning (DIF) in estimating the positions of political stimuli (e.g., parties and candidates) and survey respondents along a latent policy dimension from issue scale data. DIF arises when respondents interpret issue scales (like the standard liberal-conservative scale) differently and distort their placements of the stimuli and themselves. We develop a Bayesian implementation of the classical maximum likelihood Aldrich-McKelvey scaling method that overcomes some important shortcomings in the classical procedure. We then apply this method to study citizens’ ideological preferences and perceptions using data from the 2004-2012 American National Election Studies and the 2010 Cooperative Congressional Election Study. Our findings indicate that DIF biases self-placements on the liberal-conservative scale in a way that understates the extent of polarization in the contemporary American electorate and that citizens have remarkably accurate perceptions of the ideological positions of Senators and Senate candidates.
Keywords: ideology, measurement, Bayesian methods, polarization, ideal point estimation
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