کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1064401 | 948476 | 2011 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modeling type 1 and type 2 diabetes mellitus incidence in youth: An application of Bayesian hierarchical regression for sparse small area data
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کلمات کلیدی
DICSPCZIPMSPEMCARConditional Autoregressive - اتخاذ شرایط محرمانهBayesian - بیزیDiabetes - بیماری قندMean squared prediction error - خطای پیش بینی میانگین مربعRelative risk - خطر نسبیSparse data - داده های انعطاف پذیرCAR - ماشینdeviance information criterion - معیار انحراف اطلاعاتZero-inflated Poisson - پواسون صفر بادیSouth Carolina - کارولینای جنوبی
موضوعات مرتبط
علوم پزشکی و سلامت
پزشکی و دندانپزشکی
سیاست های بهداشت و سلامت عمومی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Modeling type 1 and type 2 diabetes mellitus incidence in youth: An application of Bayesian hierarchical regression for sparse small area data Modeling type 1 and type 2 diabetes mellitus incidence in youth: An application of Bayesian hierarchical regression for sparse small area data](/preview/png/1064401.png)
چکیده انگلیسی
Sparse count data violate assumptions of traditional Poisson models due to the excessive amount of zeros, and modeling sparse data becomes challenging. However, since aggregation to reduce sparseness may result in biased estimates of risk, solutions need to be found at the level of disaggregated data. We investigated different statistical approaches within a Bayesian hierarchical framework for modeling sparse data without aggregation of data. We compared our proposed models with the traditional Poisson model and the zero-inflated model based on simulated data. We applied statistical models to type 1 and type 2 diabetes in youth 10-19Â years known as rare diseases, and compared models using the inference results and various model diagnostic tools. We showed that one of the models we proposed, a sparse Poisson convolution model, performed better than other models in the simulation and application based on the deviance information criterion (DIC) and the mean squared prediction error.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Spatial and Spatio-temporal Epidemiology - Volume 2, Issue 1, March 2011, Pages 23-33
Journal: Spatial and Spatio-temporal Epidemiology - Volume 2, Issue 1, March 2011, Pages 23-33
نویسندگان
Hae-Ryoung Song, Andrew Lawson, Ralph B. Jr., Angela D. Liese,