Targeted ANCOVA Estimator in RCTs
Targeted ANCOVA Estimator in RCTs
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RCT 中的目标 ANCOVA 估计器
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
M. Laan
中科院分区：
文献类型：
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作者：
D. Rubin;M. Laan
在许多随机实验中，主要目标是估计平均治疗效果，定义为分配到治疗组的受试者与分配到对照组的受试者之间的预期反应差异。线性回归通常被推荐用于随机对照试验中，试图通过利用基线协变量来估计（非二进制）结果的平均治疗效果时提高精度。然后将治疗变量前的系数报告为平均治疗效应的估计值，假设线性回归模型中不包括治疗和协变量之间的相互作用。
In many randomized experiments the primary goal is to estimate the average treatment effect, defined as the difference in expected responses between subjects assigned to a treatment group and subjects assigned to a control group. Linear regression is often recommended for use in RCTs as an attempt to increase precision when estimating an average treatment effect on a (nonbinary) outcome by exploiting baseline covariates. The coefficient in front of the treatment variable is then reported as the estimate of the average treatment effect, assuming that no interactions between treatment and covariates were included in the linear regression model.