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    題名: Goodness-of-Fit Tests of Generalized Linear Mixed Models for Repeated Ordinal Responses
    作者: Kuo-Chin Lin;Yi-Ju Chen
    關鍵詞: Bootstrap resampling;generalized linear mixed model;goodness-of-fit;longitudinal ordinal response;numerical integration
    日期: 2016-11-01
    上傳時間: 2017-03-17 02:11:09 (UTC+8)
    出版者: Routledge
    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.
    關聯: Journal of Applied Statistics 43(11), p.2053–2064
    DOI: 10.1080/02664763.2015.1126568
    顯示於類別:[統計學系暨研究所] 期刊論文

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