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Semiparametric analysis of longitudinal data with informative observation times

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Abstract

In many longitudinal studies, observation times as well as censoring times may be correlated with longitudinal responses. This paper considers a multiplicative random effects model for the longitudinal response where these correlations may exist and a joint modeling approach is proposed via a shared latent variable. For inference about regression parameters, estimating equation approaches are developed and asymptotic properties of the proposed estimators are established. The finite sample behavior of the methods is examined through simulation studies and an application to a data set from a bladder cancer study is provided for illustration.

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Authors and Affiliations

  1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Bei**g, 100190, China

    Liu-quan Sun, **ao-yun Mu & Zhi-hua Sun

  2. School of mathematical Sciences, Bei**g Normal University, Bei**g, 100875, China

    **ng-wei Tong

Authors
  1. Liu-quan Sun
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  2. **ao-yun Mu
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  3. Zhi-hua Sun
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  4. **ng-wei Tong
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Corresponding author

Correspondence to Liu-quan Sun.

Additional information

The first author’s research was partly supported by the National Natural Science Foundation of China Grants (No. 10571169 and 10731010) and the National Basic Research Program of China (973 Program) (No. 2007CB814902).

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Sun, Lq., Mu, Xy., Sun, Zh. et al. Semiparametric analysis of longitudinal data with informative observation times. Acta Math. Appl. Sin. Engl. Ser. 27, 29–42 (2011). https://doi.org/10.1007/s10255-011-0037-2

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  • DOI: https://doi.org/10.1007/s10255-011-0037-2

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