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Estimating average treatment effect by model averaging
Economics Letters, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yichen Gao, Wei Long, Zhengwei Wang
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Model averaging for estimating treatment effects
Annals of the Institute of Statistical Mathematics, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Zhihao +4 more
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The Sample Average Treatment Effect
2018In cluster randomized trials (CRTs), the study units usually are not a simple random sample from some clearly defined target population. Instead, the target population tends to be hypothetical or ill-defined, and the selection of study units tends to be systematic, driven by logistical and practical considerations.
Laura B. Balzer +2 more
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Biometrical Journal, 2017
Propensity score based statistical methods, such as matching, regression, stratification, inverse probability weighting (IPW), and doubly robust (DR) estimating equations, have become popular in estimating average treatment effect (ATE) and average treatment effect among treated (ATT) in observational studies.
Abdia, Younathan +4 more
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Propensity score based statistical methods, such as matching, regression, stratification, inverse probability weighting (IPW), and doubly robust (DR) estimating equations, have become popular in estimating average treatment effect (ATE) and average treatment effect among treated (ATT) in observational studies.
Abdia, Younathan +4 more
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Subclassification estimation of the weighted average treatment effect
Biometrical Journal, 2021AbstractWeighting and subclassification are popular approaches using propensity scores (PSs) for estimation of causal effects. Weighting is appealing in that it gives consistent estimators for various causal estimands if appropriate weights are well defined and the PS model is correctly specified.
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On estimating average effects for multiple treatment groups
Statistics in Medicine, 2012We propose to estimate average exposure (or treatment) effects from observational data for multiple exposure groups by fitting an approximation of the marginal sample distribution of the response variable in each exposure group to the data. The marginal sample distribution is a function of the true distribution of the response variable in the ...
Landsman, V., Pfeiffer, R. M.
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