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Cumulative Sums of Residuals in GLMM and Its Implementation
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 Title & Authors
Cumulative Sums of Residuals in GLMM and Its Implementation
Choi, DoYeon; Jeong, KwangMo;
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 Abstract
Test statistics using cumulative sums of residuals have been widely used in various regression models including generalized linear models(GLM). Recently, Pan and Lin (2005) extended this testing procedure to the generalized linear mixed models(GLMM) having random effects, in which we encounter difficulties in computing the marginal likelihood that is expressed as an integral of random effects distribution. The Gaussian quadrature algorithm is commonly used to approximate the marginal likelihood. Many commercial statistical packages provide an option to apply this type of goodness-of-fit test in GLMs but available programs are very rare for GLMMs. We suggest a computational algorithm to implement the testing procedure in GLMMs by a freely accessible R package, and also illustrate through practical examples.
 Keywords
Clustered data;generalized linear mixed model;cumulative sums of residuals;gaussian process;gradient;hessian matrix;
 Language
English
 Cited by
1.
Goodness-of-Fit for the Clustered Binomial Models,;

Journal of the Korean Data Analysis Society, 2015. vol.17. 4A, pp.1725-1737
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