| Group Sequential Analysis of Incomplete Longitudinal Ordinal Data | |
|---|---|
| 學年 | 98 |
| 學期 | 1 |
| 出版（發表）日期 | 2009-12-01 |
| 作品名稱 | Group Sequential Analysis of Incomplete Longitudinal Ordinal Data |
| 作品名稱（其他語言） | |
| 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 |
| 產學合作 | |
| 通訊作者 | Chen, Yi-Ju; Lin, Kuo-Chin |
| 審稿制度 | |
| 國別 | JPN |
| 公開徵稿 | |
| 出版型式 | 紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/69197 ) |
| SDGS | 良好健康和福祉,優質教育 |
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