Budtz-Jørgensen Esben, Debes Frodi, Weihe Pal, Grandjean Philippe
Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5B, DK-1014 Copenhagen, Denmark.
Environmetrics. 2010 Aug 1;21(5):510-527. doi: 10.1002/env.1000.
The potential of structural equation models for combining information from different studies in environmental epidemiology is explored. For illustration we synthesize data from two birth cohorts assessing the effects of prenatal exposure to methylmercury on childhood cognitive performance. One cohort was the largest by far, but a smaller cohort included superior assessment of the PCB exposure which has been considered an important confounder when estimating the mercury effect. The data were analyzed by specification of a structural equation model for each cohort. Information was then pooled based on a joint likelihood function with key parameters constrained to be equal in the different models. Modeling assumptions were chosen to obtain a meaningful biological interpretation of the joint effect parameters. Measurement errors in mercury variables were taken into account by viewing observed variables as indicators of latent variables. Adjustments for measurement error were also included for confounder variables. In particular, this example illustrates how to properly utilize that one study provided superior information about a confounder. A final more advanced model pooled information across different outcomes to gain power and to avoid multiple testing problems. In this model, the mercury effect remained statistically significant, while the effect of PCB was less certain.
探讨了结构方程模型在整合环境流行病学不同研究信息方面的潜力。为了说明这一点，我们综合了两个出生队列的数据，评估产前接触甲基汞对儿童认知能力的影响。其中一个队列是迄今为止最大的，但一个较小的队列对多氯联苯暴露有更优的评估，在估计汞的影响时，多氯联苯暴露被认为是一个重要的混杂因素。通过为每个队列设定结构方程模型来分析数据。然后基于联合似然函数合并信息，关键参数在不同模型中被约束为相等。选择建模假设以获得联合效应参数的有意义的生物学解释。通过将观察变量视为潜在变量的指标来考虑汞变量中的测量误差。对混杂变量也进行了测量误差调整。特别是，这个例子说明了如何恰当地利用一项研究提供的关于混杂因素的更优信息。最后一个更高级的模型跨不同结局合并信息以增强检验效能并避免多重检验问题。在这个模型中，汞的效应仍然具有统计学意义，而多氯联苯的效应则不太确定。
