average treatment effect
The average treatment effect and average partial effect in nonlinear models
... the average treatment effect, the average treatment effect on the treated, the average partial effect, and the average partial effect on the ...
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Targeted Estimation and Inference for the Sample Average Treatment Effect
... sample average treatment effect (SATE) and the conditional average treatment effect ...sample effect is the average difference in the counterfactual outcomes for ...
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Regression-assisted inference for the average treatment effect in paired experiments
... ple average treatment effect in completely randomized ...sample average treatment effect whose asymptotic vari- ance is no larger than the standard difference-in-means estimator ...
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ROBUST ESTIMATION OF THE AVERAGE TREATMENT EFFECT IN ALZHEIMER\u27S DISEASE CLINICAL TRIALS
... the average treatment effect, called targeted minimum loss based estimation ...variables, treatment assignment, and the outcome measured at previous ...
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Doubly robust uniform confidence band for the conditional average treatment effect function
... Different roles of covariates between X and V are noted in the recent literature. For example, Ogburn, Rotnitzky, and Robins (2015) consider a similar issue in the context of the local average treatment ...
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Partial Identification of the Average Treatment Effect Using Instrumental Variables: Review of Methods for Binary Instruments, Treatments, and Outcomes
... This article provides a comprehensive review of the methods for partial identification of the average treatment effect (ATE) of a time-fixed binary treatment on a binary outcome using a binary ...
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Doubly-robust Nonparametric Inference on the Average Treatment Effect
... In recent years, doubly-robust estimators have gained immense popularity in many fields, including causal inference. An estimator is said to be doubly-robust if it is consistent for the target parameter of interest if ...
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Effect of Competitive Fundraising: The population average treatment effect from a covariate balancing propensity score and sampling weight
... ignorable treatment assignment， 以 下 SITA） 条 件（Rosenbaum and Rubin 1993），２値以上などの 一般的な割付条件の時には，弱非交絡（Hirano and Imbens 2004）の仮定を満たせば因果効果を推定する ことが可能となる。もちろん，このような手法にも限 界はあり，いくつかの批判がなされている。その中の 一つが共変量を調整することで擬似的なランダム化を ...
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Likelihood inference on semiparametric models: average derivative and treatment effect
... This paper is organized as follows. In Section 2, we consider weighted average derivatives. After introducing the basic setup in Section 2.1, Sections 2.2 and 2.3 discuss the semiparametric and jackknife empirical ...
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Bootstrap inference of matching estimators for average treatment effects
... 6. Conclusion This paper proposes a weighted bootstrap inference method for matching estimators of treatment effects. In contrast to the naive bootstrap, our weighted bootstrap method is valid under asymptotics ...
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Dealing with limited overlap in estimation of average treatment effects
... on average treatment effects within a selected subpopulation defined in terms of covariate ...estimated average treatment ...the average treatment within this subpopulation more ...
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Dealing with Limited Overlap in Estimation of Average Treatment Effects
... the treatment or control ...of average treatment effects having substantial bias and large ...on average treatment effects within a selected subpopulation, defined solely in terms of ...
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Dealing with Limited Overlap in Estimation of Average Treatment Effects
... on average treatment effects within a selected subpopulation defined in terms of covariate ...estimated average treatment ...the average treatment within this subpopulation more ...
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G-computation of average treatment effects on the treated and the untreated
... the average treatment effect in the total population (average treatment effect, ...the average difference in outcome between units assigned to the treatment and ...
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Simple and Bias-Corrected Matching Estimators for Average Treatment Effects
... In this article, we propose a new framework to study simple matching estimators and establish a number of new results. In contrast with much of the previous literature, we allow each unit to be used as match more than ...
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Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review
... opposite treatment. The bias of these within-pair estimates of the average treatment effect disappears as the sample size increases, although their variance does not go to zero since the ...
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Bounds on Average and Quantile Treatment Effects of Job Corps Training on Wages
... the average treatment effect of JC on participants’ ...the effect of JC on employment (to be discussed in section 4), we prefer to leave this group out of the remaining analysis because ...
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Estimation of conditional average treatment effects
... nonlinear treatment-covariate interactions (corresponding to AIC’s preferred model), a model with two linear treatment-covariate interaction terms (the model se- lected by wFIC), and BIC’s model, which ...
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Estimating average treatment effects in Stata
... Estimate average treatment ef- fect within each block as the difference in average outcomes for treated and ...controls. Average within block estimates by the proportion of observations in each ...
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mhbounds - Sensitivity Analysis for Average Treatment Effects
... whether or not inference about treatment effects may be altered by unobserved factors. In other words, one wants to determine how strongly an unmeasured variable must influence the selection process in order to ...
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