دورية أكاديمية
A Bayesian semi-parametric model for small area estimation
العنوان: | A Bayesian semi-parametric model for small area estimation |
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المؤلفون: | Malec, Donald, Müller, Peter |
بيانات النشر: | Institute of Mathematical Statistics |
سنة النشر: | 2008 |
المجموعة: | Project Euclid (Cornell University Library) |
مصطلحات موضوعية: | Dirichlet process, mixture models, National Health Interview Survey, 62G07 |
الوقت: | 62-07 |
الوصف: | In public health management there is a need to produce subnational estimates of health outcomes. Often, however, funds are not available to collect samples large enough to produce traditional survey sample estimates for each subnational area. Although parametric hierarchical methods have been successfully used to derive estimates from small samples, there is a concern that the geographic diversity of the U.S. population may be oversimplified in these models. In this paper, a semi-parametric model is used to describe the geographic variability component of the model. Specifically, we assume Dirichlet process mixtures of normals for county-specific random effects. Results are compared to a parametric model based on the base measure of the Dirichlet process, using binary health outcomes related to mammogram usage. |
نوع الوثيقة: | text |
وصف الملف: | application/pdf |
اللغة: | English |
العلاقة: | http://projecteuclid.org/euclid.imsc/1209398471Test; Bertrand Clarke and Subhashis Ghosal, eds., Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2008), 223-236 |
DOI: | 10.1214/074921708000000165 |
الإتاحة: | https://doi.org/10.1214/074921708000000165Test http://projecteuclid.org/euclid.imsc/1209398471Test |
حقوق: | Copyright © 2008, Institute of Mathematical Statistics |
رقم الانضمام: | edsbas.CF441574 |
قاعدة البيانات: | BASE |
DOI: | 10.1214/074921708000000165 |
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