A Unified Approach to Measurement Error and Missing�Data: Details and Extensions
AbstractWe extend a unified and easy-to-use approach to measurement error and missing data. Blackwell, Honaker, and King (2014a) gives an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details; more sophisticated measurement error model specifications and estimation procedures; and analyses to assess the approach's robustness to correlated measurement errors and to errors in categorical variables. These results support using the technique to reduce bias and increase efficiency in a wide variety of empirical research.
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Bibliographic InfoPaper provided by Harvard University OpenScholar in its series Working Paper with number 161326.
Date of creation: Jan 2014
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