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Safoora Gharibzadeh Mohammad Ali Mansournia Abbas Rahimiforoushani Ahad Alizadeh Atieh Amouzegar Kamran Mehrabani-Zeinabad 《统计学通讯:模拟与计算》2018,47(4):964-976
Hernan and Robins proposed a method for calculating marginal causal effect of treatment using standardization to propensity scores.?Data adaptive methods have been suggested as alternatives to logistic regression for the estimation of propensity scores. We examined the performance of various data mining methods using simulated data. The estimators' performance was evaluated in terms of relative bias, 95% CI coverage rate, and mean squared error.?All methods (except CART and GBM) displayed generally acceptable performance. However, under the conditions of moderate non-additivity and moderate nonlinearity, ANN and SL outperformed logistic regression with better bias reduction and more consistent 95% CI coverage. 相似文献
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