Semi|parametric estimation of treatment effects in randomised ...

Semi-parametric estimation of treatment effects in randomised ...

To efficiently estimate that common treatment effect we can simply use a weighted average of the estimated quantile treatment effects. It turns ...

Semiparametric Estimation of Treatment Effects in Randomized ...

We develop new semiparametric methods for estimating treatment effects. We focus on settings where the outcome distributions may be thick tailed.

Semiparametric Estimation of Treatment Effects in Randomized ...

We propose using parametric models for the treatment effects, as opposed to parametric models for the full outcome distributions. This leads to ...

Semi-parametric estimation of treatment effects in randomised ...

We develop new semi-parametric methods for estimating treatment effects. We focus on settings where the outcome distributions may be thick ...

Semi-parametric estimation of treatment effects in randomised ...

Abstract. We develop new semi-parametric methods for estimating treatment effects. We focus on settings where the outcome distributions may be thick tailed.

nber working paper series

Semiparametric Estimation of Treatment Effects in Randomized Experiments. Susan Athey, Peter J. Bickel, Aiyou Chen, Guido Imbens, and Michael Pollmann. NBER ...

(PDF) Semi-parametric estimation of treatment effects in randomised ...

We develop new semiparametric methods for estimating treatment effects. We focus on a setting where the outcome distributions may be thick ...

Semiparametric Estimation of Treatment Effects in Randomized

Susan Athey & Peter J. Bickel & Aiyou Chen & Guido Imbens & Michael Pollmann, 2021. "Semiparametric Estimation of Treatment Effects in Randomized Experiments," ...

arXiv:2109.02603v2 [stat.ME] 22 Aug 2023

Semiparametric Estimation of Treatment Effects in Randomized Experiments. [ 1]. 1. Introduction. Historically, randomized experiments were ...

Semiparametric Estimation of Treatment Effects in Randomized ...

We develop new semiparametric methods for estimating treatment effects. We focus on settings where the outcome distributions may be thick tailed, ...

Semiparametric Estimation of Treatment Effects in Randomized ...

We develop new semiparametric methods for estimating treatment effects. We focus on a setting where the outcome distributions may be thick tailed, ...

Semiparametric estimation of long-term treatment effects

Long-term outcomes of experimental evaluations are necessarily observed after long delays. We develop semiparametric methods for combining the short-term ...

Semiparametric Estimation of Treatment Effect in a Pretest–Posttest ...

Key words and phrases: Analysis of covariance, covariate adjustment, in- fluence function, inverse probability weighting, missing at random. 1. INTRODUCTION.

SEMIPARAMETRIC ESTIMATION OF TREATMENT EFFECTS ... - jstor

In this paper, we propose a unified semi- parametric estimating equation approach to estimate various types of treatment effects with censored data, including ...

Semiparametric estimation of average treatment effects in ...

The outcome model and propensity score model are estimated via the nonparametric method and construct the ATE of doubly robust estimator. Our ...

Semiparametric estimation of treatment effects given base-line ...

We consider estimation, from a double-blind randomized trial, of treatment effect within levels of base-line covariates on an outcome that is measured after ...

Semiparametric estimation of average treatment effects in ...

We propose a semiparametric method to estimate average treatment effects in observational studies based on the assumption of unconfoundedness.

Semiparametric instrumental variable estimation of treatment ...

The ideas and estimators in this article are illustrated using IV to estimate the effects of 401(k) retirement programs on savings. cO 2002 Elsevier Science ...

Semiparametric estimation of long-term treatment effects

The experimental sample measures short-term outcomes of a randomized evaluation of the treatment. the treatment The observational sample ...

michaelpollmann/parTreat: Efficiently Estimate Treatment Effects ...

Efficiently estimate treatment effects imposing a parametric assumption on treatment effects of the form Y(1) = h(Y(0), a) where a is the parameter to be ...