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Correcting for Survey Misreports using Auxiliary Information with an Application to Estimating Turnout

Katz, Jonathan N. and Katz, Gabriel (2009) Correcting for Survey Misreports using Auxiliary Information with an Application to Estimating Turnout. Social Science Working Paper, 1294R. California Institute of Technology , Pasadena, CA. (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20170727-155558097

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Abstract

Misreporting is a problem that plagues researchers that use survey data. In this paper, we develop a parametric model that corrects for misclassified binary responses using information on the misreporting patterns obtained from auxiliary data sources. The model is implemented within the Bayesian framework via Markov Chain Monte Carlo (MCMC) methods, and can be easily extended to address other problems exhibited by survey data, such as missing response and/or covariate values. While the model is fully general, we illustrate its application in the context of estimating models of turnout using data from the American National Elections Studies.


Item Type:Report or Paper (Working Paper)
Related URLs:
URLURL TypeDescription
http://resolver.caltech.edu/CaltechAUTHORS:20140314-120456550Related ItemPublished Version
ORCID:
AuthorORCID
Katz, Jonathan N.0000-0002-5287-3503
Katz, Gabriel0000-0001-5970-2769
Additional Information:Revised edition. Original date: August 2008
Group:Social Science Working Papers
Series Name:Social Science Working Paper
Issue or Number:1294R
Record Number:CaltechAUTHORS:20170727-155558097
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170727-155558097
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79510
Collection:CaltechAUTHORS
Deposited By: Jacquelyn Bussone
Deposited On:02 Aug 2017 20:37
Last Modified:03 Oct 2019 18:20

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