Results 251 to 260 of about 4,704,446 (291)

Estimating average treatment effect by model averaging

Economics Letters, 2015
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Yichen Gao, Wei Long, Zhengwei Wang
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Model averaging for estimating treatment effects

Annals of the Institute of Statistical Mathematics, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Zhihao, Zhang, Xinyu, Zou, Guohua, Wan, Alan T. K., Tso, Geoffrey K. F.   +4 more
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The Sample Average Treatment Effect

2018
In 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, Maya L. Petersen, Mark J. van der Laan   +2 more
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Propensity scores based methods for estimating average treatment effect and average treatment effect among treated: A comparative study

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, Kulasekera, K. B., Datta, Somnath, Boakye, Maxwell, Kong, Maiying   +4 more
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Subclassification estimation of the weighted average treatment effect

Biometrical Journal, 2021
AbstractWeighting 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, 2012
We 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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Model averaging for treatment effect estimation in subgroups

Pharmaceutical Statistics, 2016
AbstractIn many clinical trials, biological, pharmacological, or clinical information is used to define candidate subgroups of patients that might have a differential treatment effect. Once the trial results are available, interest will focus on subgroups with an increased treatment effect.
Björn, Bornkamp, David, Ohlssen, Baldur P, Magnusson, Heinz, Schmidli   +3 more
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Mean-square-error Calculations for Average Treatment Effects

SSRN Electronic Journal, 2005
This paper develops a new ecient estimator for the average treatment eect, if selection for treatment is on observables. The new estimator is linear in the first-stage nonparametric estimator. This simplifies the derivation of the means squared error (MSE) of the estimator as a function of the number of basis functions that is used in the first stage ...
Guido W. Imbens, Whitney K. Newey, Geert Ridder   +2 more
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