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Model Selection Criterion Based on the Multivariate Quasi-Likelihood for Generalized Estimating Equations

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  • Shinpei Imori

Abstract

type="main" xml:id="sjos12160-abs-0001"> The generalized estimating equations (GEE) approach has attracted considerable interest for the analysis of correlated response data. This paper considers the model selection criterion based on the multivariate quasi-likelihood (MQL) in the GEE framework. The GEE approach is closely related to the MQL. We derive a necessary and sufficient condition for the uniqueness of the risk function based on the MQL by using properties of differential geometry. Furthermore, we establish a formal derivation of model selection criterion as an asymptotically unbiased estimator of the prediction risk under this condition, and we explicitly take into account the effect of estimating the correlation matrix used in the GEE procedure.

Suggested Citation

  • Shinpei Imori, 2015. "Model Selection Criterion Based on the Multivariate Quasi-Likelihood for Generalized Estimating Equations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(4), pages 1214-1224, December.
    • Handle: RePEc:bla:scjsta:v:42:y:2015:i:4:p:1214-1224
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    File URL: http://hdl.handle.net/10.1111/sjos.12160
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    1. Wei Pan, 2002. "Goodness‐of‐fit Tests for GEE with Correlated Binary Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(1), pages 101-110, March.
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    3. Wei Pan, 2001. "Akaike's Information Criterion in Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 57(1), pages 120-125, March.
    4. Chung-Wei Shen & Yi-Hau Chen, 2012. "Model Selection for Generalized Estimating Equations Accommodating Dropout Missingness," Biometrics, The International Biometric Society, vol. 68(4), pages 1046-1054, December.
    5. Vens, Maren & Ziegler, Andreas, 2012. "Generalized estimating equations and regression diagnostics for longitudinal controlled clinical trials: A case study," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1232-1242.
    6. Wei Pan, 2001. "Model Selection in Estimating Equations," Biometrics, The International Biometric Society, vol. 57(2), pages 529-534, June.
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