Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.
Cancer Prevention Fellowship Program, Division of Cancer Prevention, National Cancer Institute, Rockville, Maryland, USA.
Stat Med. 2021 Feb 28;40(5):1189-1203. doi: 10.1002/sim.8835. Epub 2020 Dec 10.
Continuous treatments propensity scoring remains understudied as the majority of methods are focused on the binary treatment setting. Current propensity score methods for continuous treatments typically rely on weighting in order to produce causal estimates. It has been shown that in some continuous treatment settings, weighting methods can result in worse covariate balance than had no adjustments been made to the data. Furthermore, weighting is not always stable, and resultant estimates may be unreliable due to extreme weights. These issues motivate the current development of novel propensity score stratification techniques to be used with continuous treatments. Specifically, the generalized propensity score cumulative distribution function (GPS-CDF) and the nonparametric GPS-CDF approaches are introduced. Empirical CDFs are used to stratify subjects based on pretreatment confounders in order to produce causal estimates. A detailed simulation study shows superiority of these new stratification methods based on the empirical CDF, when compared with standard weighting techniques. The proposed methods are applied to the "Mexican-American Tobacco use in Children" study to determine the causal relationship between continuous exposure to smoking imagery in movies, and smoking behavior among Mexican-American adolescents. These promising results provide investigators with new options for implementing continuous treatment propensity scoring.
连续治疗倾向评分仍然研究不足，因为大多数方法都集中在二元治疗环境中。目前用于连续治疗的倾向评分方法通常依赖于加权，以产生因果估计。已经表明，在一些连续治疗环境中，加权方法可能会导致协变量平衡状况比未对数据进行任何调整时更差。此外，加权并不总是稳定的，由于极端权重，结果估计可能不可靠。这些问题促使当前开发新的连续治疗倾向评分分层技术。具体来说，引入了广义倾向评分累积分布函数（GPS-CDF）和非参数 GPS-CDF 方法。使用经验 CDF 根据预处理混淆因素对受试者进行分层，以产生因果估计。详细的模拟研究表明，与标准加权技术相比，基于经验 CDF 的这些新分层方法具有优越性。所提出的方法应用于“墨西哥裔美国人儿童烟草使用”研究中，以确定电影中连续接触吸烟图像与墨西哥裔美国青少年吸烟行为之间的因果关系。这些有希望的结果为研究人员提供了实施连续治疗倾向评分的新选择。
