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Biometrika 1992 79(1):205-209; doi:10.1093/biomet/79.1.205
© 1992 by Biometrika Trust
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MISCELLANEA

Prediction of survival probability based on a linear regression model

Z. YING1, L. J. WEI2 and J. S. LIN3

1Department of Statistics, University of Illinois Champaign, Illinois 61820, U.S.A.
2Department of Biostatistics, Harvard School of Public Health 677 Huntington Avenue, Boston, Massachusetts 02115, U.S.A.
3Department of Biostatistics, St. Jude Children's Research Hospital Memphis, Tennessee 38101, U.S.A.

After fitting survival data with a linear regression model, it is important to know how to use the results to make prediction of the t-year survival probability or median failure time for future patients with certain covariates. We propose some simple prediction procedures without using complicated and unstable nonparametric functional estimates. The new methods are illustrated with the Stanford heart transplant data.

Key Words: Accelerated failure time model • Buckley-James procedures • Cox's proportional hazards model • Estimating equations • Median failure time


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