On the comparison of models for paired Bernoulli data with extra zeros

碩士 === 國立成功大學 === 統計學系碩博士班 === 92 ===   For frequency counts, the situation of extra zeros often occurs in biomedical data. This is demonstrated with count data from a surgical treatment of refractive error which determined the risk factors for an epithelial defect during laser in situ keratomileusi...

Full description

Bibliographic Details
Main Authors: Yu-Hui Chou, 周育慧
Other Authors: Mi-Chia Ma
Format: Others
Language:zh-TW
Published: 2004
Online Access:http://ndltd.ncl.edu.tw/handle/23457172849595716782
id ndltd-TW-092NCKU5337020
record_format oai_dc
spelling ndltd-TW-092NCKU53370202016-06-17T04:16:56Z http://ndltd.ncl.edu.tw/handle/23457172849595716782 On the comparison of models for paired Bernoulli data with extra zeros 過多零事件之成對伯努力資料在不同模型下比較之研究 Yu-Hui Chou 周育慧 碩士 國立成功大學 統計學系碩博士班 92   For frequency counts, the situation of extra zeros often occurs in biomedical data. This is demonstrated with count data from a surgical treatment of refractive error which determined the risk factors for an epithelial defect during laser in situ keratomileusis (LASIK). The response variable of this data is binary. It was found that the data exhibited an excess of zeros, in the context that the majority of patients did not suffer intraoperative epithelial defect. The development of surgical treatment is very fast at the time being, count data with extra zeros are quite typical. We use a zero-inflated binomial model to analyze such binary data with extra zeros. In addition, the logistic model, generalized estimating equations, multicategorical logit model and proportional odds model are utilized to analyze this real data. Next, the advantage and defect of different models are compared by the real data and the usage opportunity of above statistical methods is discussed. Mi-Chia Ma 馬瀰嘉 2004 學位論文 ; thesis 47 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立成功大學 === 統計學系碩博士班 === 92 ===   For frequency counts, the situation of extra zeros often occurs in biomedical data. This is demonstrated with count data from a surgical treatment of refractive error which determined the risk factors for an epithelial defect during laser in situ keratomileusis (LASIK). The response variable of this data is binary. It was found that the data exhibited an excess of zeros, in the context that the majority of patients did not suffer intraoperative epithelial defect. The development of surgical treatment is very fast at the time being, count data with extra zeros are quite typical. We use a zero-inflated binomial model to analyze such binary data with extra zeros. In addition, the logistic model, generalized estimating equations, multicategorical logit model and proportional odds model are utilized to analyze this real data. Next, the advantage and defect of different models are compared by the real data and the usage opportunity of above statistical methods is discussed.
author2 Mi-Chia Ma
author_facet Mi-Chia Ma
Yu-Hui Chou
周育慧
author Yu-Hui Chou
周育慧
spellingShingle Yu-Hui Chou
周育慧
On the comparison of models for paired Bernoulli data with extra zeros
author_sort Yu-Hui Chou
title On the comparison of models for paired Bernoulli data with extra zeros
title_short On the comparison of models for paired Bernoulli data with extra zeros
title_full On the comparison of models for paired Bernoulli data with extra zeros
title_fullStr On the comparison of models for paired Bernoulli data with extra zeros
title_full_unstemmed On the comparison of models for paired Bernoulli data with extra zeros
title_sort on the comparison of models for paired bernoulli data with extra zeros
publishDate 2004
url http://ndltd.ncl.edu.tw/handle/23457172849595716782
work_keys_str_mv AT yuhuichou onthecomparisonofmodelsforpairedbernoullidatawithextrazeros
AT zhōuyùhuì onthecomparisonofmodelsforpairedbernoullidatawithextrazeros
AT yuhuichou guòduōlíngshìjiànzhīchéngduìbónǔlìzīliàozàibùtóngmóxíngxiàbǐjiàozhīyánjiū
AT zhōuyùhuì guòduōlíngshìjiànzhīchéngduìbónǔlìzīliàozàibùtóngmóxíngxiàbǐjiàozhīyánjiū
_version_ 1718308334384185344