TY  - JOUR
AU  - Quick, Harrison
AU  - Tootoo, Joshua
AU  - Li, Ruiyang
AU  - Vaughan, Adam S.
AU  - Schieb, Linda
AU  - Casper, Michele
AU  - Miranda, Marie Lynn
PY  - 2019
TI  - The Rate Stabilizing Tool: Generating Stable Local-Level Measures of Chronic Disease
T2  - Preventing Chronic Disease
JO  - Prev Chronic Dis
SP  - E38
VL  - 16
CY  - Centers for Disease Control and Prevention, Atlanta, Georgia 30333, USA.
N2  - Accurate and precise estimates of local-level epidemiologic measures are critical to informing policy and program decisions, but they often require advanced statistical knowledge, programming/coding skills, and extensive computing power. In response, we developed the Rate Stabilizing Tool (RST), an ArcGIS-based tool that enables users to input their own record-level data to generate more reliable age-standardized measures of chronic disease (eg, prevalence rates, mortality rates) or other population health outcomes at the county or census tract levels. The RST uses 2 forms of empirical Bayesian modeling (nonspatial and spatial) to estimate age-standardized rates and 95% credible intervals for user-specified geographic units. The RST also provides indicators of the reliability of point estimates. In addition to reviewing the RST's statistical techniques, we present results from a simulation study that illustrates the key benefit of smoothing. We demonstrate the dramatic reduction in root mean-squared error (rMSE), indicating a better compromise between accuracy and stability for both smoothing approaches relative to the unsmoothed estimates. Finally, we provide an example of the RST's use. This example uses heart disease mortality data for North Carolina census tracts to map the RST output, including reliability of estimates, and demonstrates a subsequent statistical test.
SN  - 1545-1151
UR  - https://doi.org/10.5888/pcd16.180442
DO  - 10.5888/pcd16.180442
ER  - 
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