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Showing papers by "Hammou El Barmi published in 2016"


Journal ArticleDOI
TL;DR: In this article, an empirical likelihood approach to testing for the presence of uniform stochastic ordering (or hazard rate ordering) among univariate distributions based on independent random samples from each distribution is developed.
Abstract: This paper develops an empirical likelihood approach to testing for the presence of uniform stochastic ordering (or hazard rate ordering) among univariate distributions based on independent random samples from each distribution. The proposed test statistic is formed by integrating a localized empirical likelihood statistic with respect to the empirical distribution of the pooled sample. The asymptotic null distribution of this test statistic is found to have a simple distribution-free representation in terms of standard Brownian motion. The approach is extended to the case of right-censored survival data via multiple imputation. Two applications are discussed: (1) uncensored survival time data of mice exposed to radiation, and (2) right-censored time-to-infection data from a human HIV vaccine trial comparing a placebo group with a vaccine group.

8 citations


Journal ArticleDOI
TL;DR: This paper provides consistent estimators in the k -sample case, with and without censoring, and develops a new algorithm for isotonic regression that may be of independent interest.

7 citations


Journal ArticleDOI
TL;DR: A nonparametric test for stochastic ordering from size-biased data, allowing the pattern of the size bias to differ between the two samples, is developed in terms of a maximally selected local empirical likelihood statistic.
Abstract: In two-sample comparison problems it is often of interest to examine whether one distribution function majorises the other, that is, for the presence of stochastic ordering. This paper develops a nonparametric test for stochastic ordering from size-biased data, allowing the pattern of the size bias to differ between the two samples. The test is formulated in terms of a maximally selected local empirical likelihood statistic. A Gaussian multiplier bootstrap is devised to calibrate the test. Simulation results show that the proposed test outperforms an analogous Wald-type test, and that it provides substantially greater power over ignoring the size bias. The approach is illustrated using data on blood alcohol concentration of drivers involved in car accidents, where the size bias is due to drunker drivers being more likely to be involved in accidents. Further, younger drivers tend to be more affected by alcohol, so in making comparisons with older drivers the analysis is adjusted for differences in ...

5 citations