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Confidence intervals for the regression parameter based on weighted log-rank estimating functions

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Abstract

In this paper construction of a confidence interval for the regression parameter under the accelerated life regression model is discussed. The confidence interval is based on the distribution of the regression estimator, approximated by a resampling method. The procedures are incorporated with some weight functions which have mass at censored data points as well as non-censored data points. Numerical studies show that for some weight functions, the proposed confidence interval performs well. We illustrate the procedures in a real data example.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, Illinois Wesleyan University, PO Box 2900, Bloomington, IL, 61702, USA

    Seung-Hwan Lee

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  1. Seung-Hwan Lee
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Correspondence to Seung-Hwan Lee.

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Lee, SH. Confidence intervals for the regression parameter based on weighted log-rank estimating functions. Comput Stat 25, 429–440 (2010). https://doi.org/10.1007/s00180-010-0185-5

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  • DOI: https://doi.org/10.1007/s00180-010-0185-5

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