Record Details

Replication data for: A Unified Approach To Measurement Error And Missing Data: Details And Extensions.

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication data for: A Unified Approach To Measurement Error And Missing Data: Details And Extensions.
 
Identifier https://doi.org/10.7910/DVN/29610
 
Creator Blackwell, Matthew
Honaker, James
King, Gary
 
Publisher Harvard Dataverse
 
Description We 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.

Notes:
This is the second of two articles to appear in the same issue of the same journal by the same authors. The other one is “A Unified Approach to Measurement Error and Missing Data: Overview."
 
Subject Social Sciences
missing data, measurement error, imputation, multiple overimputation