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Biometrika 1990 77(4):845-851; doi:10.1093/biomet/77.4.845
© 1990 by Biometrika Trust
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Linear regression analysis of censored survival data based on rank tests

L. J. WEI, Z. YING and D. Y. LIN

Department of Statistics, University of Wisconsin Wisconsin 53706, U.S.A.
Department of Statistics, University of Illinois Illinois 61820, U.S.A.
Department of Biostatistics, University of Washington Seattle, Washington 98195, U.S.A.

Recently linear rank statistics with censored data have been used as the estimating functions for the regression parameters in the linear model with an unspecified error distribution. The resulting rank estimators are consistent and asymptotically normal. However, the asymptotic variances of these estimators are complicated and are difficult to estimate well with censored data. In this paper, we propose some simple methods for making inference about a subset of the regression coefficients while regarding others as nuisance parameters. A lack-of-fit test for the linear model is also presented. The proposed procedures are illustrated with an example.

Key Words: Accelerated failure time model • Estimating function • Generalized Wilcoxon statistic • Goodness-of-fit • Log rank statistic • Partial likelihood


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