Document Type

Working Paper

Date

Summer 8-2016

Keywords

Measurement Error, Disease Prevalence, Diabetes, Hypertension, Medical Examination, Self-Reported, Health Condition

Language

English

Disciplines

Health Policy | Medicine and Health | Public Affairs, Public Policy and Public Administration | Social and Behavioral Sciences

Description/Abstract

This study develops and estimates a model of measurement error in self-reported health conditions. The model allows self-reports of a health condition to differ from a contemporaneous medical examination, prior medical records, or both. The model is estimated using a two-sample strategy, which combines survey data linked medical examination results and survey data linked to prior medical records. The study finds substantial inconsistencies between self-reported health, the medical record, and prior medical records. The study proposes alternative estimators for the prevalence of diagnosed and undiagnosed conditions and estimates the bias that arises when using self-reported health conditions as explanatory variables.

ISSN

1525-3066

Additional Information

Working paper no. 191

The authors would like to thank John Cawley, Gary Engelhardt, Alfonso Flores-Lagunes, Bruce Meyer, Jeffrey Kubik, Yoonseok Lee, and seminar participants at Cornell University for valuable comments.

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Source

Local Input

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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