Goodness-of-Fit Tests of Generalized Linear Mixed Models for Repeated Ordinal Responses

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Title:	Goodness-of-Fit Tests of Generalized Linear Mixed Models for Repeated Ordinal Responses
Authors:	Kuo-Chin Lin;Yi-Ju Chen
Keywords:	Bootstrap resampling;generalized linear mixed model;goodness-of-fit;longitudinal ordinal response;numerical integration
Date:	2016-11-01
Issue Date:	2017-03-17 02:11:09 (UTC+8)
Publisher:	Routledge
Abstract:	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.
Relation:	Journal of Applied Statistics 43(11), p.2053–2064
DOI:	10.1080/02664763.2015.1126568
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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