Volume 15, Issue 1 (7-2016)                   JIRSS 2016, 15(1): 1-28 | Back to browse issues page

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Dehghan M H, Duchesne ‎. Estimation of the Conditional Survival Function of a Failure Time Given a Time-varying‎ ‎Covariate with Interval-censored Observations. JIRSS. 2016; 15 (1) :1-28
URL: http://jirss.irstat.ir/article-1-374-en.html
Statistics Department‎, ‎University of Sistan and Baluchestan‎, ‎Iran
Abstract:   (4830 Views)

In this paper, we propose an approach for the nonparametric estimation of the conditional survival function of a time to failure‎ ‎given a time-varying covariate under interval-censoring for the failure time. Our strategy consists in‎ ‎modeling the covariate path with a random effects model, ‎as is done in the degradation and joint longitudinal and survival data modeling‎ ‎literature, ‎then in using a nonparametric estimator of the conditional survival function for time-fixed covariate. ‎We derive the large sample bias and variance of the estimator under simplifying assumptions and we investigate‎ ‎its finite sample efficiency and robustness by simulation. ‎We show how the proposed method can be useful in‎ ‎the early stages of data exploration and model specification by applying it to two real datasets, ‎one on‎ ‎the time to infestation of trees by pine weevil and one on the reliability of a piece of electrical equipment. ‎We conclude by suggesting avenues to make this data exploration method more suitable for formal inferences‎.

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Type of Study: Original Paper | Subject: 62Fxx: Parametric inference
Received: 2016/08/12 | Accepted: 2016/08/12 | Published: 2016/08/12

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