Accurate detection and estimation of true exposure-outcome associations is important in aetiological analysis; when there are multiple potential exposure variables of interest, methods for detecting the subset of variables most likely to have true associations with the outcome of interest are required. Case-cohort studies often collect data on a large number of variables which have not been measured in the entire cohort (e.g. panels of biomarkers). There is a lack of guidance on methods for variable selection in case-cohort studies.

中文翻译：

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案例研究分析中的两步变量选择方法

准确检测和估计真实的暴露结果关联对病因学分析很重要。当存在多个潜在的感兴趣的暴露变量时，需要用于检测最有可能与感兴趣的结果具有真实关联的变量子集的方法。案例队列研究通常会收集大量尚未在整个队列中测量的变量的数据（例如，生物标志物组）。在病例队列研究中，缺乏关于变量选择方法的指南。