Results 11 to 20 of about 20,519,205 (284)
The functional average treatment effect
Journal of Causal InferenceThis article establishes the functional average as an important estimand for causal inference. The significance of the estimand lies in its robustness against traditional issues of confounding.
Sparkes Shane, Garcia Erika, Zhang Lu
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The average treatment effect and average partial effect in nonlinear models [PDF]
, 2007 In the literature on program impact evaluation, the popular impact parameters can the average treatment effect, the average treatment effect on the treated, the average partial effect, and the average partial effect on the treated. In empirical studies, these parameters are not always presented and estimated clearly. In addition, when outcome functions
Nguyen Viet, Cuong
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Efficient collaborative learning of the average treatment effect. [PDF]
BiometricsAbstract In response to the growing need for generating real-world evidence from multisite collaborative studies, we introduce an efficient collaborative learning approach to evaluate average treatment effect (ECO-ATE) in a multisite setting under data-sharing constraints.
Li S, Duan R.
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Average treatment effects in the presence of unknown interference [PDF]
The Annals of Statistics, 2021 We investigate large-sample properties of treatment effect estimators under unknown interference in randomized experiments. The inferential target is a generalization of the average treatment effect estimand that marginalizes over potential spillover effects.
Sävje, Fredrik +2 more
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Identification and Estimation of Local Average Treatment Effects [PDF]
Econometrica, 1994 We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and
Joshua D. Angrist, Guido W. Imbens
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Mhbounds - Sensitivity Analysis for Average Treatment Effects [PDF]
, 2007 Matching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly important topic in the applied evaluation literature.
Sascha O. Becker, Marco Caliendo
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Doubly robust nonparametric inference on the average treatment effect. [PDF]
Biometrika, 2017 Summary Doubly robust estimators are widely used to draw inference about the average effect of a treatment. Such estimators are consistent for the effect of interest if either one of two nuisance parameters is consistently estimated. However, if flexible, data-adaptive estimators of these nuisance parameters are used, double robustness ...
Benkeser D +3 more
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Estimation of the Local Conditional Tail Average Treatment Effect [PDF]
Journal of Business & Economic Statistics, 2021 The conditional tail average treatment effect (CTATE) is defined as a difference between the conditional tail expectations of potential outcomes, which can capture heterogeneity and deliver aggregated local information on treatment effects over different quantile levels and is closely related to the notion of second-order stochastic dominance and the ...
Chen, Le-Yu, Yen, Yu-Min
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Conditional average treatment effect estimation with marginally constrained models
Journal of Causal Inference, 2023 Treatment effect estimates are often available from randomized controlled trials as a single average treatment effect for a certain patient population.
van Amsterdam Wouter A. C. +1 more
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Frontiers in Sustainable Food Systems, 2022 Drought is one of the major abiotic constraints that adversely affect maize production in the rain-fed agro-environment in the Asian tropics. In view of the recurrent drought, stress-resilient (SR) maize hybrids were developed and deployed to minimize ...
Atul P. Kulkarni +4 more
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