Registro de evidência do método

Small-Area Health Estimation

Small-area estimation produces reliable health indicators for places where the survey sample is too thin to support a trustworthy direct estimate. A national health survey may interview only a handful of people in a given county or census tract, so a county-level prevalence computed straight from the data swings wildly from area to area. The model-based solution, pioneered by Robert Fay and Roger Herriot in 1979 for estimating income in small places, is to borrow strength: combine each area's noisy direct estimate with a regression prediction built from auxiliary variables that are known for every area, weighting the two by their relative reliability. Rao and Molina's comprehensive treatment codified this area-level mixed model and its variants as the foundation of small area estimation. Applied to public health, the approach underpins local prevalence maps for chronic disease and health behaviors, such as the CDC PLACES project, that decision-makers use to target resources at neighborhood and county scale.

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Small-Area Estimation of Health Indicators (Model-Based Borrowing of Strength)

Registro de método taxonômico · regression-model / social-epidemiology

Fay, R. E., & Herriot, R. A. (1979). Estimates of Income for Small Places: An Application of James-Stein Procedures to Census Data. Journal of the American Statistical Association, 74(366), 269-277. · DOI 10.1080/01621459.1979.10482505
Rao, J. N. K., & Molina, I. (2015). Small Area Estimation (2nd ed.). Wiley, Hoboken, NJ. · ISBN 9781118735787

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Used in the same domainArea Deprivation Indexmachine-suggested · Relational suggestion, not evidence.Often confused withDisease Mappingmachine-suggested · Relational suggestion, not evidence.Same method familyMultilevel Neighborhood Effectsmachine-suggested · Relational suggestion, not evidence.