No-harm calibration for generalized Oaxaca-Blinder estimators

by   Peter L. Cohen, et al.

In randomized experiments, linear regression with baseline features can be used to form an estimate of the sample average treatment effect that is asymptotically no less efficient than the treated-minus-control difference in means. Randomization alone provides this "do-no-harm" property, with neither truth of a linear model nor a generative model for the outcomes being required. We present a general calibration step which confers the same no-harm property onto estimators leveraging a broad class of nonlinear models. The process recovers the usual regression-adjusted estimator when ordinary least squares is used, and further provides non-inferior treatment effect estimators using methods such as logistic and Poisson regression. The resulting estimators are non-inferior with respect to both the difference in means estimator and with respect to treatment effect estimators that have not undergone calibration.


page 1

page 2

page 3

page 4


Efficiency of Regression (Un)-Adjusted Rosenbaum's Rank-based Estimator in Randomized Experiments

A completely randomized experiment allows us to estimate the causal effe...

Regression-adjusted average treatment effect estimates in stratified and sequentially randomized experiments

Stratified and sequentially randomized experiments are widely used in fi...

Inference in experiments conditional on observed imbalances in covariates

Double blind randomized controlled trials are traditionally seen as the ...

Regression Adjustments for Estimating the Global Treatment Effect in Experiments with Interference

Standard estimators of the global average treatment effect can be biased...

Least Squares with Error in Variables

Error-in-variables regression is a common ingredient in treatment effect...

The Generalized Oaxaca-Blinder Estimator

After performing a randomized experiment, researchers often use ordinary...

A Framework for the Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data

A central obstacle in the objective assessment of treatment effect (TE) ...