Modeling Area-Level Health Rankings
AbstractWe propose a Bayesian factor analysis model to rank the health of localities. Mortality and morbidity variables empirically contribute to the resulting rank, and population and spatial correlation are incorporated into a measure of uncertainty. We use county-level data from Texas and Wisconsin to compare our approach to conventional rankings that assign deterministic factor weights and ignore uncertainty. Greater discrepancies in rankings emerge for Texas than Wisconsin since the differences between the empirically-derived and deterministic weights are more substantial. Uncertainty is evident in both states but becomes especially large in Texas after incorporating noise from imputing its considerable missing data.
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Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 7631.
Length: 40 pages
Date of creation: Sep 2013
Date of revision:
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Other versions of this item:
- I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-10-05 (All new papers)
- NEP-DEM-2013-10-05 (Demographic Economics)
- NEP-GEO-2013-10-05 (Economic Geography)
- NEP-HEA-2013-10-05 (Health Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hogan J.W. & Tchernis R., 2004. "Bayesian Factor Analysis for Spatially Correlated Data, With Application to Summarizing Area-Level Material Deprivation From Census Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 314-324, January.
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- Doorslaer, Eddy van & Jones, Andrew M., 2003. "Inequalities in self-reported health: validation of a new approach to measurement," Journal of Health Economics, Elsevier, vol. 22(1), pages 61-87, January.
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