Different hypotheses have been proposed in life course epidemiology on how a time-varying exposure can affect health or disease later in life. Researchers are often interested in investigating the probability of these hypotheses based on observed life course data. However, current techniques based on model/variable selection do not provide a direct estimate of this probability. We propose an alternative technique for a continuous exposure, using a Bayesian approach that has specific advantages, to investigate which life course hypotheses are supported by the observed data.

中文翻译：

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一种贝叶斯方法来研究涉及持续暴露的生命历程假设

关于随时间变化的暴露如何影响生命后期的健康或疾病，在生命历程流行病学中提出了不同的假设。研究人员通常有兴趣根据观察到的生命历程数据来调查这些假设的概率。然而，当前基于模型/变量选择的技术不能直接估计这种概率。我们提出了一种连续曝光的替代技术，使用具有特定优势的贝叶斯方法来研究观察到的数据支持哪些生命历程假设。