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Adjusting Body Mass for Measurement Error with Invalid Validation Data

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  • Charles Courtemanche
  • Joshua C. Pinkston
  • Jay Stewart

Abstract

We propose a new method for using validation data to correct self-reported weight and height in surveys that do not measure respondents. The standard correction in prior research regresses actual measures on reported values using an external validation dataset, and then uses the estimated coefficients to predict actual measures in the primary dataset. This approach requires the strong assumption that the expectations of measured weight and height conditional on the reported values are the same in both datasets. In contrast, we use percentile ranks rather than levels of reported weight and height. Our approach requires the weaker assumption that the conditional expectations of actual measures are increasing in reported values in both samples. This makes our correction more robust to differences in measurement error across surveys as long as both surveys represent the same population. We examine three nationally representative datasets and find that misreporting appears to be sensitive to differences in survey context. When we compare predicted BMI distributions using the two validation approaches, we find that the standard correction is affected by differences in misreporting while our correction is not. Finally, we present several examples that demonstrate the potential importance of our correction for future econometric analyses and estimates of obesity rates.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 19928.

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Date of creation: Feb 2014
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Handle: RePEc:nbr:nberwo:19928

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  1. John Cawley, 2004. "The Impact of Obesity on Wages," Journal of Human Resources, University of Wisconsin Press, vol. 39(2).
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  15. Charles L. Baum II, 2010. "The Effects of Food Stamps on Obesity," Working Papers, Middle Tennessee State University, Department of Economics and Finance 201003, Middle Tennessee State University, Department of Economics and Finance.
  16. Maximilian D. Schmeiser, 2009. "Expanding wallets and waistlines: the impact of family income on the BMI of women and men eligible for the Earned Income Tax Credit," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1277-1294.
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Cited by:
  1. Silvia Barbaresco & Charles J. Courtemanche & Yanling Qi, 2014. "Impacts of the Affordable Care Act Dependent Coverage Provision on Health-Related Outcomes of Young Adults," NBER Working Papers 20148, National Bureau of Economic Research, Inc.

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