JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 415
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #312585
Title: New Insights into the Log-Rank and Gehan's Tests
Author(s): Eric R. Siegel*+ and Songthip T. Ounpraseuth and Ralph L. Kodell
Companies: University of Arkansas for Medical Sciences and University of Arkansas for Medical Sciences and University of Arkansas for Medical Sciences
Keywords: non-parametric ; survival ; log-rank ; Gehan ; invariance ; reflection
Abstract:

In survival analysis, the log-rank test is considered the canonical unweighted member of the Log-rank family of tests, whereas Gehan's generalized Wilcoxon test is considered a weighted version of the log-rank test that gives heavier weights to earlier event times. We have been studying how their chi-square statistics behave when these two tests are applied to uncensored data before and after monotone transformations. As expected, the chi-square statistics of both tests are invariant when the data are subjected to exponentiation, a rank-preserving transformation. However, when the data are subjected to a rank-reversing transformation, reflection about a constant, the log-rank test's chi-square statistic varies strongly, whereas Gehan's test's chi-square statistic remains invariant. We interpret these results as follows: (1) although it's considered unweighted, the log-rank test intrinsically gives heavier weights to later event times, and (2) the weighting scheme of Gehan's test counterbalances the log-rank test's intrinsic behavior to give equal weight to all event times.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.