Testing and Estimation of Treatment Effects in Clinical Trials for Terminal and Nonterminal Events Subject to Competing Risks

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Treatment effects were assessed across various terminal and nonterminal events, addressing the complexities of competing risks.
Key findings highlight the limitations of traditional methods like the log-rank test, leading to wider confidence intervals.
A nonparametric approach enhances testing and estimation in clinical trials, improving data utilization and insight.
New methods highlight the need for stronger assumptions, emphasizing their validity in broader contexts.

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Observational analysis reveals treatment effects in terminal and nonterminal events, indicating challenges with current methods.

Song Yang (2025) studied this question.

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