Hansen Stefan Nygaard, Andersen Per Kragh, Parner Erik Thorlund
Section for Biostatistics, University of Aarhus, Bartholins Allé 2, 8000 , Aarhus C, Denmark,
Lifetime Data Anal. 2014 Oct;20(4):584-98. doi: 10.1007/s10985-013-9290-4. Epub 2014 Jan 14.
A method based on pseudo-observations has been proposed for direct regression modeling of functionals of interest with right-censored data, including the survival function, the restricted mean and the cumulative incidence function in competing risks. The models, once the pseudo-observations have been computed, can be fitted using standard generalized estimating equation software. Regression models can however yield problematic results if the number of covariates is large in relation to the number of events observed. Guidelines of events per variable are often used in practice. These rules of thumb for the number of events per variable have primarily been established based on simulation studies for the logistic regression model and Cox regression model. In this paper we conduct a simulation study to examine the small sample behavior of the pseudo-observation method to estimate risk differences and relative risks for right-censored data. We investigate how coverage probabilities and relative bias of the pseudo-observation estimator interact with sample size, number of variables and average number of events per variable.
针对含右删失数据的感兴趣函数（包括竞争风险中的生存函数、受限均值和累积发病率函数）的直接回归建模，已经提出了一种基于伪观测值的方法。一旦计算出伪观测值，这些模型就可以使用标准的广义估计方程软件进行拟合。然而，如果协变量的数量相对于观测到的事件数量较多，回归模型可能会产生有问题的结果。实践中通常会使用每个变量的事件数准则。这些关于每个变量事件数的经验法则主要是基于对逻辑回归模型和Cox回归模型的模拟研究而建立的。在本文中，我们进行了一项模拟研究，以检验伪观测值方法在估计右删失数据的风险差异和相对风险时的小样本行为。我们研究了伪观测值估计量的覆盖概率和相对偏差如何与样本量、变量数量以及每个变量的平均事件数相互作用。
