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

Likelihood Ratio-Based Confidence Intervals in Survival Analysis

S. A. Murphy
Journal of the American Statistical Association
Vol. 90, No. 432 (Dec., 1995), pp. 1399-1405
DOI: 10.2307/2291531
Stable URL: http://www.jstor.org/stable/2291531
Page Count: 7
  • Download PDF
  • Cite this Item

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
Likelihood Ratio-Based Confidence Intervals in Survival Analysis
Preview not available

Abstract

Confidence intervals for the survival function and the cumulative hazard function are considered. These confidence intervals are based on an inversion of the likelihood ratio statistic. To do this, two extensions of the likelihood, each of which yields meaningful likelihood ratio hypothesis tests and subsequent confidence intervals, are considered. The choice of the best extension is difficult. In the failure time setting, the binomial extension is best in constructing confidence intervals concerning the survival function and the Poisson extension is best in constructing confidence intervals concerning the cumulative hazard. Simulations indicate that these two methods perform as well as or better than competitors based on the asymptotic normality of the estimator.

Page Thumbnails

  • Thumbnail: Page 
1399
    1399
  • Thumbnail: Page 
1400
    1400
  • Thumbnail: Page 
1401
    1401
  • Thumbnail: Page 
1402
    1402
  • Thumbnail: Page 
1403
    1403
  • Thumbnail: Page 
1404
    1404
  • Thumbnail: Page 
1405
    1405