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HGLM modelling of dropout process using a frailty model

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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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Authors and Affiliations

  1. Department of Statistics, Seoul National University, 151-742, Seoul, Korea

    Youngjo Lee & Maengseok Noh

  2. Department of Economics, Seoul Ńational University, 151-742, Seoul, Korea

    Keunkwan Ryu

Authors
  1. Youngjo Lee
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  2. Maengseok Noh
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  3. Keunkwan Ryu
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Additional information

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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