Empirical Bayes Estimation of the Prevalence of Uninsured Individuals by County in the State of Tennessee and Analyses of Predictive Factors

Abstract

Lawmakers at the state level require good estimates of those without health insurance in the areas they serve to inform policy decisions. These estimates are often built on inadequate data from smaller geographic areas, such as counties. The Small Area Estimates Branch of the U.S. Census Bureau developed a method to generate stable estimates at the county level using data from the Annual Social and Economic Supplement to the Current Population Survey and several other sources. Using data collected in the state of Tennessee, this article presents a less complicated and arguably less expensive alternative to that method, while providing comparable results. Limitations of both methods and suggestions for future research are discussed.

Cross-institutional OSCE Quality Assurance in Europe using a mutual assessment strategy; are we equipped for it?

“…Yet, the Classical test theory provides neither a conceptual basis nor a statistical mechanism to assess this reliability from combined sources of measurement error. It is not so much that Classical test theory denies the existence of multiple sources of measurement errors, rather it is that Classical test theory cannot accommodate this fact either conceptually or statistically 31,42 . Moreover, G-theory analysis calculates the G-coefficient as an overall reliability coefficient and estimate relative and absolute SEM directly.…”