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Title: Replication data for: Integrating Voting Theory and Roll-Call Analysis: A Framework      
dateReleased:
01-21-2009
downloadURL: http://hdl.handle.net/1902.1/10755
ID:
hdl:1902.1/10755
description:
Replication data and code forthcoming Scholars of legislative studies typically use ideal point estimates from scaling procedures to test theories of legislative politics. We contend that theory and methods may be better integrated by directly incorporating \textit{maintained} and \textit{to be tested hypotheses} in the statistical model used to estimate legislator preferences. In this view of theory and estimation, formal modelling (1) provides auxiliary assumptions th at serve as constraints in the estimation process, and (2) generates testable predictions. The estimation and hypothesis testing procedure uses roll call data to evaluate the validity of theoretically derived \textit{to be tested hypotheses} in a world where \textit{maintained hypotheses} are presumed true. We articulate the approach using the language of statistical inference (both frequentist and Bayesian). The approach is demonstrated in analyses of the well-studied Powell amendment to the federal aid to education bill in the 84th House and the Compromise of 1790 in the 1st House
description:
Joshua D. Clinton; Adam Meirowitz, 2009, "Replication data for: Integrating Voting Theory and Roll-Call Analysis: A Framework", http://hdl.handle.net/1902.1/10755, Harvard Dataverse, V1
name:
Joshua D. Clinton
Adam Meirowitz
homePage: http://www.harvard.edu/
name:
Harvard University
ID:
SCR:011273
abbreviation:
DataVerse
homePage: http://thedata.org/
name:
Dataverse Network Project
ID:
SCR:001997