Goodness-of-Fit Tests of Generalized Linear Mixed Models for Repeated Ordinal Responses
學年 105
學期 1
出版(發表)日期 2016-11-01
作品名稱 Goodness-of-Fit Tests of Generalized Linear Mixed Models for Repeated Ordinal Responses
作品名稱(其他語言)
著者 Kuo-Chin Lin; Yi-Ju Chen
單位
出版者
著錄名稱、卷期、頁數 Journal of Applied Statistics 43(11), p.2053–2064
摘要 Categorical longitudinal data are frequently applied in a variety of fields, and are commonly fitted by generalized linear mixed models (GLMMs) and generalized estimating equations models. The cumulative logit is one of the useful link functions to deal with the problem involving repeated ordinal responses. To check the adequacy of the GLMMs with cumulative logit link function, two goodness-of-fit tests constructed by the unweighted sum of squared model residuals using numerical integration and bootstrap resampling technique are proposed. The empirical type I error rates and powers of the proposed tests are examined by simulation studies. The ordinal longitudinal studies are utilized to illustrate the application of the two proposed tests.
關鍵字 Bootstrap resampling;generalized linear mixed model;goodness-of-fit;longitudinal ordinal response;numerical integration
語言 en
ISSN 0266-4763; 1360-0532
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Yi-Ju Chen
審稿制度
國別 GBR
公開徵稿
出版型式 ,電子版,紙本
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