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Robert Ashmead

U.S. Census Bureau, Center for Statistical Research & Methodology



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Eric Slud

U.S. Census Bureau, Center for Statistical Research & Methodology



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282 – New Developments in Small Area Estimation Research at the U.S. Census Bureau

Small Area Model Diagnostics and Validation with Applications to the Voting Rights Act Section 203

Sponsor: Survey Research Methods Section
Keywords: Small Area Estimation, Model Diagnostics, Parametric Bootstrap

Robert Ashmead

U.S. Census Bureau, Center for Statistical Research & Methodology

Eric Slud

U.S. Census Bureau, Center for Statistical Research & Methodology

We consider the dual problems of choosing between competing small area models and validating model assumptions in an area-level model. Many classes of small area models result in an estimate that is a convex combination of the direct and the marginal estimate for a given area. Therefore, competing models may share the same direct estimates, but give different marginal estimates as well as relative weight on the estimates. We discuss diagnostics to choose between competing models and parametric bootstrap methods to check for model validity and goodness of fit. We use the example of small area models related to the Voting Rights Act Section 203(b), which are used to estimate the number of limited English proficient and illiterate persons in certain language minority groups within jurisdictions using 5-year data from the American Community Survey.

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