Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support

Prediction in Censored Survival Data: A Comparison of the Proportional Hazards and Linear Regression Models

Glenn Heller and Jeffrey S. Simonoff
Biometrics
Vol. 48, No. 1 (Mar., 1992), pp. 101-115
DOI: 10.2307/2532742
Stable URL: http://www.jstor.org/stable/2532742
Page Count: 15
  • Read Online (Free)
  • Download ($14.00)
  • Subscribe ($19.50)
  • Cite this Item
If you need an accessible version of this item please contact JSTOR User Support
Prediction in Censored Survival Data: A Comparison of the Proportional Hazards and Linear Regression Models
Preview not available

Abstract

Although the analysis of censored survival data using the proportional hazards and linear regression models is common, there has been little work examining the ability of these estimators to predict time to failure. This is unfortunate, since a predictive plot illustrating the relationship between time to failure and a continuous covariate can be far more informative regarding the risk associated with the covariate than a Kaplan-Meier plot obtained by discretizing the variable. In this paper the predictive power of the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-202) proportional hazards estimator and the Buckley-James (1979, Biometrika 66, 429-436) censored regression estimator are compared. Using computer simulations and heuristic arguments, it is shown that the choice of method depends on the censoring proportion, strength of the regression, the form of the censoring distribution, and the form of the failure distribution. Several examples are provided to illustrate the usefulness of the methods.

Page Thumbnails

  • Thumbnail: Page 
101
    101
  • Thumbnail: Page 
102
    102
  • Thumbnail: Page 
103
    103
  • Thumbnail: Page 
104
    104
  • Thumbnail: Page 
105
    105
  • Thumbnail: Page 
106
    106
  • Thumbnail: Page 
107
    107
  • Thumbnail: Page 
108
    108
  • Thumbnail: Page 
109
    109
  • Thumbnail: Page 
110
    110
  • Thumbnail: Page 
111
    111
  • Thumbnail: Page 
112
    112
  • Thumbnail: Page 
113
    113
  • Thumbnail: Page 
114
    114
  • Thumbnail: Page 
115
    115