Abstract
The log-rank test is frequently used to compare survival curves. While sample size estimation for comparison of binomial proportions has been adapted to typical clinical trial conditions such as noncompliance, lag time, and staggered entry, the estimation of sample size when the log-rank statistic is to be used has not been generalized to these types of clinical trial conditions. This paper presents a method of estimating sample sizes for the comparison of survival curves by the log-rank statistic in the presence of unrestricted rates of noncompliance, lag time, and so forth. The method applies to stratified trials in which the above conditions may vary across the different strata, and does not assume proportional hazards. Power and duration, as well as sample sizes, can be estimated. The method also produces estimates for binomial proportions and the Tarone-Ware class of statistics.
Keywords
StatisticsStatisticMathematicsSample size determinationLog-rank testRank (graph theory)Test statisticNegative binomial distributionSample (material)Binomial (polynomial)Statistical hypothesis testingEconometricsSurvival analysisCombinatorics
MeSH Terms
Clinical Trials as TopicHumansMarkov ChainsResearch DesignStatistics as Topic
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Publication Info
- Year
- 1988
- Type
- article
- Volume
- 44
- Issue
- 1
- Pages
- 229-229
- Citations
- 351
- Access
- Closed
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Cite This
Edward Lakatos
(1988).
Sample Sizes Based on the Log-Rank Statistic in Complex Clinical Trials.
Biometrics
, 44
(1)
, 229-229.
https://doi.org/10.2307/2531910
Identifiers
- DOI
- 10.2307/2531910
- PMID
- 3358991