Summary
We introduce a shared random-effect model, derived from frailty models to account for informative dropout. We extend the iterative weighted least squares algorithm for hierarchical generalized linear models to shared random-effect models. Monte-Carlo simulations are carried out to illustrate that the proposed method works well whether the random-effect distribution is correctly specified or not.
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Acknowledgments
The authors thank Professor Roger Payne and Professor Thomas Ten Have for their helpful comments.
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This study was supported by a grant of the Korea Health 21 R & D Project, Ministry of Health & Welfare, Republic of Korea. (01-PJ1-PG3-51200-0002).
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Lee, Y., Noh, M. & Ryu, K. HGLM modelling of dropout process using a frailty model. Computational Statistics 20, 295–309 (2005). https://doi.org/10.1007/BF02789705
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DOI: https://doi.org/10.1007/BF02789705