Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Cumulative Sums of Residuals in GLMM and Its Implementation

  • Choi, DoYeon (Department of Statistics, Pusan National University) ;
  • Jeong, KwangMo (Department of Statistics, Pusan National University)
  • Received : 2014.06.09
  • Accepted : 2014.08.19
  • Published : 2014.09.30
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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.

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Acknowledgement

Supported by : Pusan National University

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