Semiparametric mixed-effects models for clustered doubly censored data
The Cox proportional frailty model with a random effect has been proposed for the analysis of right-censored data which consist of a large number of small clusters of correlated failure time observations. For right-censored data, Cai <italic>et al.</italic> [3] proposed a class of semiparametric mixed-effects models which provides useful alternatives to the Cox model. We demonstrate that the approach of Cai <italic>et al.</italic> [3] can be used to analyze clustered doubly censored data when both left- and right-censoring variables are always observed. The asymptotic properties of the proposed estimator are derived. A simulation study is conducted to investigate the performance of the proposed estimator.
Year of publication: |
2012
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Authors: | Shen, Pao-Sheng |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 39.2012, 9, p. 1881-1892
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Publisher: |
Taylor & Francis Journals |
Saved in:
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