Performance of a two-sample test with Mann-Whitney statistics under dependent censoring with copula models

• Main Authors: Jiun-Huang Hsu, 許竣瑝
• Other Authors: Takeshi Emura
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/2m79b7

碩士 === 國立中央大學 === 統計研究所 === 107 === The Mann-Whitney test is a nonparametric test for comparing two groups. For analysis of right-censored survival data, the Mann-Whitney effect is a measure for comparing the two survival times from the two groups. However, the two-sample test based on the estimator of the Mann-Whitney effect (Efron 1967; Koziol and Jia 2009; Dobler and Pauly 2018) can be inconsistent when the independent censoring assumption fails to hold. In this thesis, we derive the theoretical properties of the estimator of the Mann-Whitney effect under dependent censoring. We derive the asymptotic bias of the Mann-Whitney effect estimator when dependence between survival time and censoring time is modeled by a copula. We also propose a new estimator of the Mann-Whitney effect by applying the copula-graphic estimator under assumed copula models. We prove the consistency and asymptotic normality of the proposed estimator by a martingale theory. We propose a new test that is asymptotically valid under a possibly misspecified copula model. Simulations are conducted to verify the proposed method, and a real data example is given for illustration.