Statistical inferences of extended concentration indices for directly standardized rates.
作者： Mandi Yu , Benmei Liu , Yan Li , Zhaohui (Joe) Zou , Nancy Breen
DOI: 10.1002/SIM.7952
关键词: Linearization 、 Statistics 、 Sample (statistics) 、 Estimator 、 Variance (accounting) 、 Standardized rate 、 Monte Carlo method 、 Statistical inference 、 Mathematics 、 Population
摘要: The relative concentration index (RCI) and the absolute (ACI) have been widely used for monitoring health disparities with ranked determinants. RCI has extended to allow value judgments about inequality aversion by Pereira in 1998 Wagstaff 2002. Previous studies of focused on survey sample data. This paper adapts use directly standardized rates (DSRs) calculated from population-based surveillance A Taylor series linearization (TL)-based variance estimator is developed evaluated using simulations. simulation-based Monte Carlo (MC) also as a comparison. Following Wagstaff's approach 1991, we extend ACI DSRs. In all simulations, both TL MC methods produce valid estimates. simple, closed form that attractive users without sophisticated programming skills. estimators incorporated into beta version National Cancer Institute's Health Disparities Calculator, free statistical software tool enables estimation 11 commonly summary measures
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