回淡江大學首頁
Group Sequential Analysis of Incomplete Longitudinal Ordinal Data

類別:期刊論文

學年 / 學期:98-1

出版日期:2009-12-01 00:00:00

著者:Chen, Yi-Ju; Lin, Kuo-Chin; Lin, Jian-Jhih

單位:淡江大學統計學系

出版者:Kumamoto: ICIC International

著錄名稱、卷期、頁數:ICIC Express Letters 3(4)pt.B, pp.1453-1458

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.

關鍵字:GEE model;GLMM;Group sequential method;Longitudinal ordinal data;Power;Type I rate

語言:en

ISSN:1881-803X

期刊性質:國外

收錄於:EI

通訊作者:Chen, Yi-Ju; Lin, Kuo-Chin

國別:JPN

出版型式:紙本