Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, I. R. of Iran.
Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, I. R. of Iran.
Arch Iran Med. 2016 Sep;19(9):666-70.
Traditional standardization methods have been used in medical research for a long time to standardize the effect of interest for one confounder such as age. Model-based standardization extension of these methods is used when we have more than one variable produces an effect which is the population average and has marginal causal interpretation. In this paper, we discuss the most traditional model-based standardization methods that are used to estimate the marginal causal effect of exposure. We applied these methods to data from Tehran Thyroid Study and estimated the standardized effect of exposure on outcome. Based on the simulation studies, covariate standardization is preferred except when 1) we have enough information about the mechanism of exposure or 2) the outcome is rare and exposure is frequent, so propensity score standardization is suggested.
传统的标准化方法在医学研究中已经使用了很长时间，用于标准化一个混杂因素（如年龄）的效果。当有多个变量产生的效果是人群平均值并且具有边际因果解释时，就会使用基于模型的标准化方法对这些方法进行扩展。在本文中，我们讨论了最传统的基于模型的标准化方法，用于估计暴露的边际因果效应。我们将这些方法应用于德黑兰甲状腺研究的数据，并估计了暴露对结果的标准化效应。基于模拟研究，除非 1）我们对暴露机制有足够的信息，或者 2）结果罕见而暴露频繁，否则建议使用协变量标准化，而不是倾向评分标准化。
