Katz, Jonathan N. and Katz, Gabriel Correcting for Survey Misreports Using Auxiliary Information with an Application to Estimating Turnout. American Journal of Political Science, 54 (3). pp. 815-835. ISSN 00925853 (2010)Full text not available from this repository.
Misreporting is a problem that plagues researchers who use survey data. In this article, 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.
|Subjects:||H Social Sciences > HA Statistics
J Political Science > JA Political science (General)
J Political Science > JF Political institutions (General)
|Research Area:||Economics and Institutional Change|
|Depositing User:||Users 22 not found.|
|Date Deposited:||22 Feb 2011 15:50|
|Last Modified:||11 Jul 2011 14:25|
Actions (login required)