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84 – New Developments in Disease Prediction
Adjustments for Misclassification of Deployment Status in a Population Based Health Study of Operation Enduring Freedom and Operation Iraqi Freedom Veterans
Donsig Jang
Mathematica Policy Research, Inc
Frank B. Yoon
Mathematica Policy Research
Amang Sukasih
Mathematica Policy Research
Amii Kress
Department of Veteran Affairs
Shannon K. Barth
Veterans Health Administration
Clare Mahan
Veterans Health Administration
Steven Coughlin
Emory University
Erin Dursa
Veterans Health Administration
Aaron Schneiderman
Veterans Health Administration
In large, complex sample surveys, administrative data used to construct the survey frame may contain information that does not agree with self-reported information. In many cases, misclassification is the result of erroneous recordkeeping; additionally, when there is a delay between sampling and survey fielding, temporal changes in the values of sampling frame variables may occur. We present a motivating example of the National Health Study for a New Generation of U.S. Veterans; in it, deployment status is a primary sampling and analysis variable that indicates whether a Veteran had served in a combat theater in Operation Enduring Freedom or Operation Iraqi Freedom. About 11 percent of Veterans in the sample had self-reported a deployment status that differed from the administrative records used in sampling. Generally, misclassification of sampling variables requires post-stratification adjustments to the survey weights so that the weighted respondent sample is representative of the target population. We address the nature of misclassified deployment status and then discuss and implement an approach using updated administrative records to adjust the survey weights in the study.