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