Journal Article10.1093/PAN/MPP036
An Introduction to the Augmented Inverse Propensity Weighted Estimator
Adam N. Glynn,Kevin M. Quinn +1 more
TL;DR: In this article, the augmented inverse propensity weighted estimator (AIPW) is proposed for average treatment effects (ATEs) and compared with three other estimators: regression, inverse propensity weighting, and propensity score matching.
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Abstract: In this paper, we discuss an estimator for average treatment effects (ATEs) known as the augmented inverse propensity weighted (AIPW) estimator. This estimator has attractive theoretical properties and only requires practitioners to do two things they are already comfortable with: (1) specify a binary regression model for the propensity score, and (2) specify a regression model for the outcome variable. Perhaps the most interesting property of this estimator is its so-called “double robustness.” Put simply, the estimator remains consistent for the ATE if either the propensity score model or the outcome regression is misspecified but the other is properly specified. After explaining the AIPW estimator, we conduct a Monte Carlo experiment that compares the finite sample performance of the AIPW estimator to three common competitors: a regression estimator, an inverse propensity weighted (IPW) estimator, and a propensity score matching estimator. The Monte Carlo results show that the AIPW estimator has comparable or lower mean square error than the competing estimators when the propensity score and outcome models are both properly specified and, when one of the models is misspecified, the AIPW estimator is superior.
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Citations
A Custom-Developed Emergency Department Provider Electronic Documentation System Reduces Operational Efficiency.
Joshua Feblowitz,Sukhjit S. Takhar,Michael J. Ward,Ryan Ribeira,Adam B. Landman,Adam B. Landman +5 more
TL;DR: The findings suggest that a custom‐designed electronic provider documentation may negatively affect ED throughput, and strategies to mitigate these effects, such as reducing documentation requirements or adding clinical staff, scribes, or voice recognition, would be a valuable area of future research.
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Accounting for interactions and complex inter-subject dependency in estimating treatment effect in cluster randomized trials with missing outcomes
TL;DR: In this article, the authors proposed an augmented generalized estimating equations (AUG) estimator that weights by the inverse of the probability of being a complete case and allows different outcome models in each intervention arm.
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Regional Anesthesia Associated With Decreased Inpatient and Outpatient Opioid Demand in Tibial Plateau Fracture Surgery
21 Mar 2022
TL;DR: In this paper , the authors found that regional anesthesia (RA) is associated with decreased opioid demand in tibial plateau fracture surgery, but not with an associated risk of acute compartment syndrome, although there was no significant difference from 1 month preoperatively to 6 weeks postoperatively.
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Impact of Food Insecurity and SNAP Participation on Healthcare Utilization and Expenditures
Seth A. Berkowitz,Hilary K. Seligman,Sanjay Basu +2 more
- 01 Jan 2017
TL;DR: This project was supported with a grant from the University of Kentucky Center for Poverty Research through funding by the U.S. Department of Agriculture, Economic Research Service and the Food and Nutrition Service.
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