Abstract
We describe existing tests and introduce two new tests concerning the value of a survival function. These tests may be used to construct a confidence interval for the survival probability at a given time or for a quantile of the survival distribution. Simulation studies show that error rates can differ substantially from their nominal values, particularly at survival probabilities close to zero or one. We recommend our new constrained bootstrap test for its good overall performance.
| Original language | English |
|---|---|
| Pages (from-to) | 430-436 |
| Number of pages | 7 |
| Journal | Biometrics |
| Volume | 55 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Jun 1999 |
Bibliographical note
Copyright:Copyright 2017 Elsevier B.V., All rights reserved.
Keywords
- Beta distribution
- Bootstrap sampling
- Censoring
- Confidence interval
- Greenwood's formula
- Hypothesis test
- Kaplan-Meier estimate
- Likelihood ratio test
- Survival data
ASJC Scopus subject areas
- Statistics and Probability
- General Biochemistry,Genetics and Molecular Biology
- General Immunology and Microbiology
- General Agricultural and Biological Sciences
- Applied Mathematics