Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion
碩士 === 國立陽明大學 === 公共衛生研究所 === 105 === Understand the characteristics of infectious diseases, contribute to the assessment of the disease epidemic, the future development trend for further study, and health policy makers to take appropriate health policy to prevent the expansion of the disease. Dengu...
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ndltd-TW-105YM0050580182019-05-15T23:39:47Z http://ndltd.ncl.edu.tw/handle/y8n823 Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion 比較廣義回歸模型和負二項回歸模型處理過度離散資料的問題 Yu-Ting Hsu 徐郁婷 碩士 國立陽明大學 公共衛生研究所 105 Understand the characteristics of infectious diseases, contribute to the assessment of the disease epidemic, the future development trend for further study, and health policy makers to take appropriate health policy to prevent the expansion of the disease. Dengue fever is the main exploratory infectious diseases in this research. The number of cases of dengue fever was treated as response variables, which was a discrete type and the number of morbidity was not large. The Poisson regression model, which is a common type of discrete data, was selected as a benchmark and compared with other estimates of discrete data Model(Generalized Poisson regression and Negative binomial regression), to explore its differences. Yi-Hau Chen 程毅豪 2017 學位論文 ; thesis 21 zh-TW |
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碩士 === 國立陽明大學 === 公共衛生研究所 === 105 === Understand the characteristics of infectious diseases, contribute to the assessment of the disease epidemic, the future development trend for further study, and health policy makers to take appropriate health policy to prevent the expansion of the disease. Dengue fever is the main exploratory infectious diseases in this research.
The number of cases of dengue fever was treated as response variables, which was a discrete type and the number of morbidity was not large. The Poisson regression model, which is a common type of discrete data, was selected as a benchmark and compared with other estimates of discrete data Model(Generalized Poisson regression and Negative binomial regression), to explore its differences.
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author2 |
Yi-Hau Chen |
author_facet |
Yi-Hau Chen Yu-Ting Hsu 徐郁婷 |
author |
Yu-Ting Hsu 徐郁婷 |
spellingShingle |
Yu-Ting Hsu 徐郁婷 Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion |
author_sort |
Yu-Ting Hsu |
title |
Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion |
title_short |
Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion |
title_full |
Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion |
title_fullStr |
Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion |
title_full_unstemmed |
Comparing the Generalized Poisson Regression And Negative Binomial Regression Methods In Dealing With Overdispersion |
title_sort |
comparing the generalized poisson regression and negative binomial regression methods in dealing with overdispersion |
publishDate |
2017 |
url |
http://ndltd.ncl.edu.tw/handle/y8n823 |
work_keys_str_mv |
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