教師資料查詢 | 類別: 期刊論文 | 教師: 李百靈 Pai-ling Li (瀏覽個人網頁)

標題:Evaluation of Multiple Imputation for Longitudinal Ordinal Data under MCAR and MAR Missing-Data Mechanisms
學年99
學期2
出版(發表)日期2011/06/01
作品名稱Evaluation of Multiple Imputation for Longitudinal Ordinal Data under MCAR and MAR Missing-Data Mechanisms
作品名稱(其他語言)
著者Tuan, Li-Wen; Chen, Yi-Ju; Li, Pai-Ling; Lin, Kuo-Chin
單位淡江大學統計學系
出版者Toroku: ICIC International
著錄名稱、卷期、頁數ICIC Express Letters 5(6), pp.1833-1838
摘要Multiple imputation can be used to solve the problem of missing data that is a common occurrence in longitudinal studies. An imputation strategy proposed by Demirtas and Hedeker (Statistics in Medicine 2008; 27, 4086-4093) is to deal with incomplete longitudinal ordinal data, which converts discrete outcomes to continuous outcomes by generating normal values, employs multiple method based on normality, and reconverts to binary scale as well as ordinal one. The performance of multiple imputation in terms of standardized bias, root-mean-squared error and coverage percentage under missing completely at random (MCAR) and missing at random (MAR) was discussed by various configurations. The simulated results indicated this mutation strategy is suitable for most of incomplete data under these two missing-data mechanisms.
關鍵字MAR; MCAR; Multiple imputation; Ordinal scale
語言英文
ISSN1881-803X
期刊性質國外
收錄於EI
產學合作
通訊作者Chen, Yi-Ju
審稿制度
國別日本
公開徵稿
出版型式紙本
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