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Title: Replication data for: Using Bayesian Aldrich-McKelvey Scaling to Study Citizens' Ideological Preferences and Perceptions      
dateReleased:
03-23-2015
downloadURL: http://dx.doi.org/10.7910/DVN/26638
ID:
doi:10.7910/DVN/26638
description:
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.
description:
Hare, Christopher; Armstrong, David A., II; Bakker, Ryan; Carroll, Royce; Poole, Keith T., 2014, "Replication data for: Using Bayesian Aldrich-McKelvey Scaling to Study Citizens' Ideological Preferences and Perceptions", http://dx.doi.org/10.7910/DVN/26638, Harvard Dataverse, V2
name:
Hare, Christopher
Armstrong, David A., II
Bakker, Ryan
Carroll, Royce
Poole, Keith T.
homePage: http://www.harvard.edu/
name:
Harvard University
ID:
SCR:011273
abbreviation:
DataVerse
homePage: http://thedata.org/
name:
Dataverse Network Project
ID:
SCR:001997