Analysis of correlated binary data with missing(Session 4b)
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概要
- 論文の詳細を見る
In clinical studies, correlated binary response data are frequently collected. Although various methods for analysis of correlated data have been proposed, the evaluation on those is not sufficient in case of binary responses with specifically various missing mechanisms. Therefore we investigated the performance of six statistical methods (last observation carried forward (LOCF), complete case analysis (CC), conventional generalized estimating equations (GEE), weighted-GEE (WGEE), multiple imputation (MI) and generalized linear mixed-effects models (GLMM)) for correlated binary response with missing. Continuous variables for defining binary responses were used to impute missing values in MI and to calculate the weights for WGEE. This evaluation used actual data from a clinical study that compared two antidepressants.
- 2011-11-11
著者
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Iwasaki Manabu
Department Of Computer And Information Science Seikei University
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Abe Takayuki
Center For Clinical Research Keio University School Of Medicine
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Sato Yuji
Center For Clinical Research Keio University School Of Medicine
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Iwasaki Manabu
Department Of Computer And Information Science Faculty Of Science And Engineering Seikei University
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