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Information based model selection criteria for generalized linear mixed models with unknown variance component parameters

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  • Yu, Dalei
  • Zhang, Xinyu
  • Yau, Kelvin K.W.

Abstract

This paper derives the corrected conditional Akaike information criteria for generalized linear mixed models by analytic approximation and parametric bootstrap. The sampling variation of both fixed effects and variance component parameter estimators are accommodated in the bias correction term. Simulation shows that the proposed corrected criteria provide good approximation to the true conditional Akaike information and demonstrates promising model selection results. The use of the criteria is demonstrated in the analysis of the chronic asthmatic patients’ data.

Suggested Citation

  • Yu, Dalei & Zhang, Xinyu & Yau, Kelvin K.W., 2013. "Information based model selection criteria for generalized linear mixed models with unknown variance component parameters," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 245-262.
    • Handle: RePEc:eee:jmvana:v:116:y:2013:i:c:p:245-262
    DOI: 10.1016/j.jmva.2012.12.005
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    References listed on IDEAS

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    Cited by:

    1. Chan, Moon-tong & Yu, Dalei & Yau, Kelvin K.W., 2015. "Multilevel cumulative logistic regression model with random effects: Application to British social attitudes panel survey data," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 173-186.
    2. Craiu, Radu V. & Duchesne, Thierry, 2018. "A scalable and efficient covariate selection criterion for mixed effects regression models with unknown random effects structure," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 154-161.
    3. Yuki Kawakubo & Shonosuke Sugasawa & Tatsuya Kubokawa, 2014. "Conditional AIC under Covariate Shift with Application to Small Area Prediction," CIRJE F-Series CIRJE-F-944, CIRJE, Faculty of Economics, University of Tokyo.
    4. Dalei Yu, 2016. "Conditional Akaike Information Criteria for a Class of Poisson Mixture Models with Random Effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1214-1235, December.

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