Various nonparametric test statistics have been proposed for censored data. Two-sample nonparametric testing plays an important role in biometry. While most of two-sample nonparametric tests intend to detect a shift… Click to show full abstract
Various nonparametric test statistics have been proposed for censored data. Two-sample nonparametric testing plays an important role in biometry. While most of two-sample nonparametric tests intend to detect a shift in location or in scale, the two-sample Cucconi test statistic is suitable for the joint comparison of both parameters. The Cucconi test statistic is extended to the left- and right-censored data based on the theory of ties. We derive the limiting distribution of the Cucconi test statistic for censored data. We conduct simulation studies to investigate the convergence of the Cucconi test statistic to the limiting distribution and the power of the proposed statistic with various population distributions. The method is illustrated with an analysis using real data.
               
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