ASSESSING GENERALIZED LINEAR MIXED MODELS USING RESIDUAL ANALYSIS

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Title:	ASSESSING GENERALIZED LINEAR MIXED MODELS USING RESIDUAL ANALYSIS
Authors:	Lin, Kuo-Chin;Chen, Yi-Ju
Contributors:	淡江大學統計學系
Date:	2012-08
Issue Date:	2014-03-17 10:41:12 (UTC+8)
Publisher:	Kumamoto: ICIC International
Abstract:	A nonparametric smoothing method for assessing the adequacy of generalized linear mixed models (GLMMs) is developed. The proposed method is based on smoothing the residuals over continuous covariates to avoid the partition of continuous covariates on model checking. The global test statistic has a quadratic form and its formulae of expectation as well as variance are derived. The sampling distribution of the quadratic form test statistic is approximated by a scaled chi-squared distribution. For bandwidth selection, the leave-one-out cross-validation approach is recommendable for use. A longitudinal binary data set is utilized to demonstrate the proposed approach.
Relation:	International Journal of Innovative Computing, Information and Control 8(8), pp.5693-5701
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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