Hypothesis test to compare the survival distributions of two samples
The logrank test, or log-rank test, is a hypothesis test to compare the survival distributions of two samples. It is a nonparametric test and appropriate to use when the data are right skewed and censored (technically, the censoring must be non-informative). It is widely used in clinical trials to establish the efficacy of a new treatment in comparison with a control treatment when the measurement is the time to event (such as the time from initial treatment to a heart attack). The test is sometimes called the Mantel–Cox test. The logrank test can also be viewed as a time-stratified Cochran–Mantel–Haenszel test.
The test was first proposed by Nathan Mantel and was named the logrank test by Richard and Julian Peto.[1][2][3]
^Mantel, Nathan (1966). "Evaluation of survival data and two new rank order statistics arising in its consideration". Cancer Chemotherapy Reports. 50 (3): 163–70. PMID 5910392.
^Peto, Richard; Peto, Julian (1972). "Asymptotically Efficient Rank Invariant Test Procedures". Journal of the Royal Statistical Society, Series A. 135 (2). Blackwell Publishing: 185–207. doi:10.2307/2344317. hdl:10338.dmlcz/103602. JSTOR 2344317.
^
Harrington, David (2005). "Linear Rank Tests in Survival Analysis". Encyclopedia of Biostatistics. Wiley Interscience. doi:10.1002/0470011815.b2a11047. ISBN 047084907X.
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