Doubly robust estimation in causal inference with missing outcomes: With an application to the Aerobics Center Longitudinal Study

Kecheng Wei, Guoyou Qin, Jiajia Zhang and Xuemei Sui

Computational Statistics & Data Analysis, 2022, vol. 168, issue C

Abstract: Estimation of the average treatment effect (ATE) and the average treatment effect on the treated (ATT) are two important topics of causal inference. However, when using the observational data for causal inference, two main problems including unbalanced covariates and missing outcomes should be tackled. In order to handle these two challenges and provide protection against model misspecification, the doubly robust estimators are developed, which remain consistent when the propensity score model and the selection probability model are correctly specified concurrently, or the outcome regression model is correctly specified. Under regularity conditions, the asymptotic normality of the estimators is established. Simulation studies confirm the desirable finite-sample performance of the proposed methods. Based on the Aerobics Center Longitudinal Study, the significant positive causal effect of physical activity levels on health status is discovered.

Keywords: Average treatment effect; Average treatment effect on the treated; Causal inference; Missing data; Propensity score; Double robustness (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167947321002334
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:168:y:2022:i:c:s0167947321002334

DOI: 10.1016/j.csda.2021.107399

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().