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Model averaging for treatment effect estimation in subgroups
Pharmaceutical Statistics, 2016AbstractIn 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 +3 more
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Mean-square-error Calculations for Average Treatment Effects
SSRN Electronic Journal, 2005This 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 +2 more
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Robust Estimation for Average Treatment Effects
SSRN Electronic Journal, 2013We study the probability tail properties of the Inverse Probability Weighting (IPW) estimators of the Average Treatment Effect T when there is limited overlap in the covariate distribution. Our main contribution is a new robust estimator that performs substantially better than existing IPW estimators.
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Local Average Treatment Effect and Regression-Discontinuity-Design
2015Local Average Treatment Effect and Regression-Discontinuity-Design for Program ...
Cerulli, G.
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Beyond the average treatment effect
Οι ιατρικές αποφάσεις συχνά βασίζονται στη μέση επίδραση θεραπειών όπως αυτή εκτιμάται από κλινικές δοκιμές, υποθέτοντας ότι όλοι οι ασθενείς επωφελούνται εξίσου. Ωστόσο, η προσέγγιση αυτή αγνοεί τη σημαντική ετερογένεια στις αντιδράσεις των ασθενών.openaire +1 more source
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
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Estimating average treatment effects in Stata [PDF]
, 2007 In this talk, I look at several methods for estimating average effects of a program, treatment, or regime, under unconfoundedness. The setting is one with a binary program. The traditional example in economics is that of a labor market program where some individuals receive training and others do not, and interest is in some measure of the ...
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Local average treatment effects with binary outcomes
American Journal of EpidemiologyStuart G Baker, Karen S Lindeman
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