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含间歇观测时变二元协变量的删失生存数据分析AI 解读

In survival analyses that include a time-dependent covariate, the standard partial likelihood approach is often complicated by the fact that the necessary observations of the time-dependent covariate are not always available for the subjects in each risk set. In this article, we consider the situation of a binary time-dependent covariate. We specify a longitudinal model for the binary covariate with missing observations and a proportional hazards model for survival time…

删失配对数据的再删失方法AI 解读

In comparing two treatment regimens, a matched-pair design is often used for nonhomogeneous experimental units. A standard method of analyzing the resulting data is to consider the difference within pairs, so that the nuisance parameters due to the heterogeneity between pairs can be eliminated and the parameter of interest—the treatment effect—can be estimated. This procedure becomes invalid when the data are subject to censoring, however. In addition, the available…

连续协变量分类对生存时间比较的影响AI 解读

The variance of the estimated hazard ratio between two groups when there is one categorized continuous gamma-distributed covariate is derived using exponential and Weibull regression models and asymptotic theory. Categorizing a continuous covariate increases the variance of the estimated hazard ratio and decreases the efficiency of the analysis. The efficiency of categorization is studied as a function of the strength of the relation between survival time and the covariate,…

连续协变量分类对生存时间比较的影响AI 解读

The variance of the estimated hazard ratio between two groups when there is one categorized continuous gamma-distributed covariate is derived using exponential and Weibull regression models and asymptotic theory. Categorizing a continuous covariate increases the variance of the estimated hazard ratio and decreases the efficiency of the analysis. The efficiency of categorization is studied as a function of the strength of the relation between survival time and the covariate,…