药物流行病学
审查(临床试验)
医学
非参数统计
统计推断
推论
比例危险模型
参数统计
因果推理
计量经济学
统计
计算机科学
人工智能
数学
内科学
药理学
药方
病理
作者
Gerd Rippin,Shahrzad Salmasi,Héctor Sanz,Joan Largent
摘要
ABSTRACT Aim This article provides an overview of time‐to‐event (TTE) analysis in pharmacoepidemiology. Materials & Methods The key concept of censoring is reviewed, including right‐, left‐, interval‐ and informative censoring. Simple descriptive statistics are explained, including the nonparametric estimation of the TTE distribution as per Kaplan–Meier method, as well as more complex TTE regression approaches, including the parametric Accelerated Failure Time (AFT) model and the semi‐parametric Cox Proportional Hazards and Restricted Mean Survival Time (RMST) models. Additional approaches and various TTE model extensions are presented as well. Finally, causal inference for TTE outcomes is addressed. Results A thorough review of the available concepts and methods outlines the immense variety of available and useful TTE models. Discussion There may be underused TTE concepts and methods, which are highlighted to raise awareness for researchers who aim to apply the most appropriate TTE approach for their study. Conclusion This paper constitutes a modern summary of TTE analysis concepts and methods. A curated list of references is provided.
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