Approximate residual balancing: debiased inference of average treatment effects in high dimensions

There are many settings where researchers are interested in estimating average treatment effects and are willing to rely on the unconfoundedness assumption, which requires that the treatment assignment be as good as random conditional on pretreatment variables. The unconfoundedness assumption is oft...

Full description

Saved in:
Bibliographic Details
Published in:Journal of the Royal Statistical Society. Series B, Statistical methodology Statistical methodology, 2018-09, Vol.80 (4), p.597-623
Main Authors: Athey, Susan, Imbens, Guido W., Wager, Stefan
Format: Article
Language:English
Subjects:
Adjustment
Assumptions
Averages
Causal inference
equations
Inference
Linear analysis
linear models
Linearity
Potential outcomes
Pretreatment
Propensity
Propensity score
Random variables
Regression analysis
Regression models
Sparse estimation
Statistical methods
Statistics
Variables
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!