Using Ensemble-Based Methods for Directly Estimating Causal Effects: An Investigation of Tree-Based G-Computation.
Using Ensemble-Based Methods for Directly Estimating Causal Effects: An Investigation of Tree-Based G-Computation.
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DOI：
10.1080/00273171.2012.640600
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发表时间：
2012-01
影响因子：
3.8
通讯作者：
Austin PC
中科院分区：
文献类型：
--
作者：
Austin PC
研究人员越来越多地使用观察或非随机数据来估计因果治疗效果。对于高质量证据的产生至关重要的是能够减少或最大限度地减少观察性研究中经常发生的混淆。当使用潜在结果框架来定义因果治疗效应时，需要每种可能治疗下的潜在结果。然而，仅观察实际接受治疗的结局，而其他治疗的潜在结局被视为缺失数据。一些作者建议使用参数回归模型来估计潜在的结果。在这项研究中，我们研究了使用基于集成的方法（袋装回归树，随机森林和增强回归树）通过估算潜在结果直接估计平均治疗效果。我们使用了一系列广泛的蒙特卡罗模拟来估计偏差，方差和均方误差的治疗效果估计使用不同的合奏方法。出于比较的目的，我们比较了这些方法的性能与使用倾向评分的治疗加权的逆概率时，逻辑回归或集成方法被用来估计倾向评分。使用深度为3或4的增强回归树来插补潜在结果往往会导致估计值的偏倚与最佳性能方法的偏倚相当。通过一项实证性病例研究，我们比较了住院戒烟咨询对急性心肌梗死患者随后死亡率的影响。
Researchers are increasingly using observational or nonrandomized data to estimate causal treatment effects. Essential to the production of high-quality evidence is the ability to reduce or minimize the confounding that frequently occurs in observational studies. When using the potential outcome framework to define causal treatment effects, one requires the potential outcome under each possible treatment. However, only the outcome under the actual treatment received is observed, whereas the potential outcomes under the other treatments are considered missing data. Some authors have proposed that parametric regression models be used to estimate potential outcomes. In this study, we examined the use of ensemble-based methods (bagged regression trees, random forests, and boosted regression trees) to directly estimate average treatment effects by imputing potential outcomes. We used an extensive series of Monte Carlo simulations to estimate bias, variance, and mean squared error of treatment effects estimated using different ensemble methods. For comparative purposes, we compared the performance of these methods with inverse probability of treatment weighting using the propensity score when logistic regression or ensemble methods were used to estimate the propensity score. Using boosted regression trees of depth 3 or 4 to impute potential outcomes tended to result in estimates with bias equivalent to that of the best performing methods. Using an empirical case study, we compared inferences on the effect of in-hospital smoking cessation counseling on subsequent mortality in patients hospitalized with an acute myocardial infarction.
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影响因子：
7
作者：
McCaffrey, DF;Ridgeway, G;Morral, AR
通讯作者：
Morral, AR
DOI：
10.1016/s0169-7161(07)27002-6
发表时间：
2008-01-01
期刊：
EPIDEMIOLOGY AND MEDICAL STATISTICS
影响因子：
--
作者：
Rubin, Donald B.
通讯作者：
Rubin, Donald B.
影响因子：
2
作者：
Austin, Peter C.
通讯作者：
Austin, Peter C.
影响因子：
3.8
作者：
Hill, Jennifer;Weiss, Christopher;Zhai, Fuhua
通讯作者：
Zhai, Fuhua
DOI：
10.1080/03610910903528301
发表时间：
2010-01-01
影响因子：
0.9
作者：
Austin, Peter C.
通讯作者：
Austin, Peter C.