A semiparametric extension of the Mann-Whitney test for randomly truncated data
Related Experiment Video
Updated: Oct 20, 2026

Measurement of Survival Time in Brachionus Rotifers: Synchronization of Maternal Conditions
Published on: July 22, 2016
1Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia 19104-6021, USA.
Abstract:
In many applications, statistical data are frequently observed subject to a retrospective sampling criterion resulting in pure right-truncated data. In classical testing problems, the Mann-Whitney test is used for testing the equality of two distributions. A semiparametric extension of this test is developed for the case when truncation is present. We consider a model in which the truncation distribution is parameterized, while the lifetime distribution is left as a nonparametric component. The method is seen to be applicable to many patterns of truncation including left truncation, right truncation, and doubly truncated data for which no other nonparametric or semiparametric test is currently available. Applications of the semiparametric method are given. Simulation results indicate that for pure right-truncated data the semiparametric test is more powerful than a recent nonparametric test.
Related Concept Videos
Test for Homogeneity
Wilcoxon Signed-Ranks Test for Matched Pairs
Wilcoxon Signed-Ranks Test for Median of Single Population
Wilcoxon Rank-Sum Test
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance, comparing...
Friedman Two-way Analysis of Variance by Ranks
