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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/69197

    题名: Group Sequential Analysis of Incomplete Longitudinal Ordinal Data
    作者: Chen, Yi-Ju;Lin, Kuo-Chin;Lin, Jian-Jhih
    贡献者: 淡江大學統計學系
    关键词: GEE model;GLMM;Group sequential method;Longitudinal ordinal data;Power;Type I rate
    日期: 2009-12
    上传时间: 2011-10-23 16:34:18 (UTC+8)
    出版者: Kumamoto: ICIC International
    摘要: Group sequential methods have been used for a correct application of interim analysis, which is conducted to allow for possibly early termination of a alinical trial for ethical, economical and administrative considerations. The classical group sequential methods are applied for cross-sectional data and the boundaries can be easily computed due to the property of independent increment structure (IIS) between the successive test statistices. owever, it does not hold for longitudinal data. For analyzing longitudinal ordinal data, group sequential methods based on generalized linear mixed models (GLMM) and generalized estimating equations (GEE) models are proposed. The performance ofthese two approaches are compared with respect to their type I error rate and power bysimulation studies. The proposed methods are demonstrated by a real data set with ordinal responses.
    關聯: ICIC Express Letters 3(4)pt.B, pp.1453-1458
    显示于类别:[統計學系暨研究所] 期刊論文





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