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Covariate adjustment for linear models in estimating treatment effects in randomised clinical trials. Some useful theory to guide simulation

随机临床试验处理效应估计中的线性模型协变量调整:指导模拟的理论

Building on key papers that were published in special issues of Biometrics in 1957 and 1982 we propose and develop a three-aspect system for evaluating the effect of fitting covariates in the analysis of designed experiments, in particular randomised clinical trials. The three aspects are: first the effect on residual mean square error, second the effect on the variance inflation factor (VIF) and third the effect on second order precision. We concentrate, in particular, on…

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A neutral comparison of statistical methods for time-to-event analyses under non-proportional hazards

非比例风险下生存分析统计方法的中立比较

While well-established methods for time-to-event data are available when the proportional hazards assumption holds, there is no consensus on the best inferential approach under non-proportional hazards (NPH). However, a wide range of parametric and non-parametric methods for testing and estimation in this scenario have been proposed. To provide recommendations on the statistical analysis of clinical trials where non proportional hazards are expected, we conducted a…

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Simultaneous inference procedures for the comparison of multiple characteristics of two survival functions

比较两个生存函数多项特征的同时推断程序

Survival time is the primary endpoint of many randomized controlled trials, and a treatment effect is typically quantified by the hazard ratio under the assumption of proportional hazards. Awareness is increasing that in many settings this assumption is a-priori violated, e.g. due to delayed onset of drug effect. In these cases, interpretation of the hazard ratio estimate is ambiguous and statistical inference for alternative parameters to quantify a treatment effect is…

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