Murdoch Childrens Research Institute, Melbourne, Australia.
Stat Methods Med Res. 2012 Jun;21(3):273-93. doi: 10.1177/0962280210394483. Epub 2011 Jan 24.
Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often carried out via outcome regression modelling. An alternative approach is to use propensity score methodology. The propensity score is the conditional probability of receiving the exposure given the observed covariates and can be used, under the assumption of no unmeasured confounders, to estimate the causal effect of the exposure. In this article, we provide a non-technical and intuitive discussion of propensity score methodology, motivating the use of the propensity score approach by analogy with randomised studies, and describe the four main ways in which this methodology can be implemented. We carefully describe the population parameters being estimated - an issue that is frequently overlooked in the medical literature. We illustrate these four methods using data from a study investigating the association between maternal choice to provide breast milk and the infant's subsequent neurodevelopment. We outline useful extensions of propensity score methodology and discuss directions for future research. Propensity score methods remain controversial and there is no consensus as to when, if ever, they should be used in place of traditional outcome regression models. We therefore end with a discussion of the relative advantages and disadvantages of each.
在存在混杂的情况下，估计二项暴露对结局的影响通常通过结局回归模型进行。另一种方法是使用倾向评分方法。倾向评分是在观察到的协变量下接受暴露的条件概率，并且可以在没有未测量混杂因素的假设下，用于估计暴露的因果效应。在本文中，我们提供了一种非技术性的、直观的倾向评分方法讨论，通过类比随机研究来说明使用倾向评分方法的理由，并描述了该方法的四种主要实施方式。我们仔细描述了正在估计的人群参数 - 这是医学文献中经常被忽视的一个问题。我们使用一项研究的数据来说明这四种方法，该研究调查了母亲选择提供母乳与婴儿随后的神经发育之间的关联。我们概述了倾向评分方法的有用扩展，并讨论了未来研究的方向。倾向评分方法仍然存在争议，并且对于何时（如果有）应该代替传统的结局回归模型使用，尚无共识。因此，本文最后讨论了每种方法的相对优缺点。
