Article
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Computation of The Mann-Whitney Effect under Parametric Survival Copula Models
Version 1
: Received: 20 March 2024 / Approved: 20 March 2024 / Online: 26 March 2024 (09:41:01 CET)
A peer-reviewed article of this Preprint also exists.
Nakazono, K.; Lin, Y.-C.; Liao, G.-Y.; Uozumi, R.; Emura, T. Computation of the Mann–Whitney Effect under Parametric Survival Copula Models. Mathematics 2024, 12, 1453. Nakazono, K.; Lin, Y.-C.; Liao, G.-Y.; Uozumi, R.; Emura, T. Computation of the Mann–Whitney Effect under Parametric Survival Copula Models. Mathematics 2024, 12, 1453.
Abstract
The Mann-Whitney effect is a measure for comparing survival distributions between two groups.
The Mann-Whitney effect is interpreted as the probability that a randomly selected subject in a
group survives longer than a randomly selected subject in the other group. Under the independence
assumption of two groups, the Mann-Whitney effect can be expressed as the traditional integral
formula of survival functions. However, when the survival times in two groups are not independent
each other, the traditional expression of the Mann-Whitney effect has to be modified. In this article,
we propose a copula-based approach to compute the Mann-Witney effect with parametric survival
models under dependence of two groups, which may arise in the potential outcome framework. In
addition, we develop a Shiny web app that can implement the proposed method via simple commands
(https://nkosuke.shinyapps.io/shiny_survival/). Through a simulation study, we show
the correctness of the proposed calculator. We apply the proposed methods to two real datasets.
Keywords
censoring; copula; Hand’s paradox; potential outcome; Mann-Whitney effect; stress-strength model; two-sample comparison; survival analysis; survival function; treatment effect
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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