Two-Sample Problems for Survival Time—A Copula-Based Approach for Dependent Censoring—

DOI

Bibliographic Information

Other Title
  • 生存時間の２標本問題—コピュラに基づく従属打ち切り問題への対処—

Abstract

<p>The Mann-Whitney test is a nonparametric test for detecting the difference of two groups, which can be estimated by right-censored survival data. However, the traditional test based on Efron's estimator is invalid when the independent censoring assumption fails to hold. Recently, researchers discuss “dependent censoring”, where the independence assumption is violated. In this article, we review a method for studying the asymptotic bias of Efron's estimator under a copula-based dependent censoring model. We also review an asymptotically unbiased (consistent) estimator of the Mann-Whitney effect, which adopts the copula-graphic estimator to adjust for the effect of dependent censoring. This leads to a valid two-sample test when the structure of dependent censoring is correctly specified by a copula. We also derive the asymptotic distribution of the copula-based estimator under possible misspecification on an assumed copula. The method is illustrated by analyzing a real dataset. We provide the R code to reproduce the data analysis results.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390295270228161408
  • DOI
    10.11329/jjssj.52.295
  • ISSN
    21891478
    03895602
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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