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.

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 ...

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

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 ...

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," ...

(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 ...

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

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.

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 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 ...

Efficient Semiparametric Estimation of Average Treatment Effects ...

In such experiments, the experimenter first stratifies the sample according to observed baseline covariates and then assigns treatment randomly ...

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.

michaelpollmann/parTreat: Efficiently Estimate Treatment Effects ...

Efficient estimation of treatment effects based on parametric models of the treatment effect, as proposed by Athey et al. (2021). To install this package in R, ...

Semiparametric Estimation of Average Treatment Effects under ...

Gelbach and Hoynes (2002) focus on estimating quantiles in a randomized experiment. Firpo (2002) considers the nonexperimental case and develops an estimator ...

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

Standard analyses in those settings typically involved estimating the average effect of the treatment using the difference in average outcomes ...

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

Typically, subjects are randomized to two treatments, and response is measured at baseline, prior to intervention with the randomized treatment (pretest) ...

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 ... - 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 ...

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