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題名 Two-sample inference procedures under nonproportional hazards
作者 戴以誠
Tai, Yi-Cheng;Wang, Weijing;Wells, Martin T.
貢獻者 統計系
關鍵詞 crossing survival functions; delayed treatment effect; interpretable estimand; IPCW; Kendall's tau; MaxCombo; nonproportional hazards; restricted mean survival time; sensitivity analysis
日期 2023-07
上傳時間 5-Aug-2025 09:47:45 (UTC+8)
摘要 We introduce a new two-sample inference procedure to assess the relative performance of two groups over time. Our model-free method does not assume proportional hazards, making it suitable for scenarios where nonproportional hazards may exist. Our procedure includes a diagnostic tau plot to identify changes in hazard timing and a formal inference procedure. The tau-based measures we develop are clinically meaningful and provide interpretable estimands to summarize the treatment effect over time. Our proposed statistic is a U-statistic and exhibits a martingale structure, allowing us to construct confidence intervals and perform hypothesis testing. Our approach is robust with respect to the censoring distribution. We also demonstrate how our method can be applied for sensitivity analysis in scenarios with missing tail information due to insufficient follow-up. Without censoring, Kendall's tau estimator we propose reduces to the Wilcoxon-Mann–Whitney statistic. We evaluate our method using simulations to compare its performance with the restricted mean survival time and log-rank statistics. We also apply our approach to data from several published oncology clinical trials where nonproportional hazards may exist.
關聯 Pharmaceutical Statistics, Vol.22, No.6, pp.1016-1030
資料類型 article
DOI https://doi.org/10.1002/pst.2324
dc.contributor 統計系
dc.creator (作者) 戴以誠
dc.creator (作者) Tai, Yi-Cheng;Wang, Weijing;Wells, Martin T.
dc.date (日期) 2023-07
dc.date.accessioned 5-Aug-2025 09:47:45 (UTC+8)-
dc.date.available 5-Aug-2025 09:47:45 (UTC+8)-
dc.date.issued (上傳時間) 5-Aug-2025 09:47:45 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158802-
dc.description.abstract (摘要) We introduce a new two-sample inference procedure to assess the relative performance of two groups over time. Our model-free method does not assume proportional hazards, making it suitable for scenarios where nonproportional hazards may exist. Our procedure includes a diagnostic tau plot to identify changes in hazard timing and a formal inference procedure. The tau-based measures we develop are clinically meaningful and provide interpretable estimands to summarize the treatment effect over time. Our proposed statistic is a U-statistic and exhibits a martingale structure, allowing us to construct confidence intervals and perform hypothesis testing. Our approach is robust with respect to the censoring distribution. We also demonstrate how our method can be applied for sensitivity analysis in scenarios with missing tail information due to insufficient follow-up. Without censoring, Kendall's tau estimator we propose reduces to the Wilcoxon-Mann–Whitney statistic. We evaluate our method using simulations to compare its performance with the restricted mean survival time and log-rank statistics. We also apply our approach to data from several published oncology clinical trials where nonproportional hazards may exist.
dc.format.extent 96 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Pharmaceutical Statistics, Vol.22, No.6, pp.1016-1030
dc.subject (關鍵詞) crossing survival functions; delayed treatment effect; interpretable estimand; IPCW; Kendall's tau; MaxCombo; nonproportional hazards; restricted mean survival time; sensitivity analysis
dc.title (題名) Two-sample inference procedures under nonproportional hazards
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1002/pst.2324
dc.doi.uri (DOI) https://doi.org/10.1002/pst.2324