منابع مشابه
Covariate balancing propensity score
The propensity score plays a central role in a variety of causal inference settings. In particular, matching and weighting methods based on the estimated propensity score have become increasingly common in the analysis of observational data. Despite their popularity and theoretical appeal, the main practical difficulty of these methods is that the propensity score must be estimated. Researchers...
متن کاملHigh Dimensional Propensity Score Estimation via Covariate Balancing
In this paper, we address the problem of estimating the average treatment effect (ATE) and the average treatment effect for the treated (ATT) in observational studies when the number of potential confounders is possibly much greater than the sample size. In particular, we develop a robust method to estimate the propensity score via covariate balancing in high-dimensional settings. Since it is u...
متن کاملCovariate Balancing Propensity Score for General Treatment Regimes
Propensity score matching and inverse-probability weighting are popular methods for causal inference in observational studies. Under the assumption of unconfoundedness, these methods enable researchers to estimate causal effects by balancing observed covariates across different treatment values. While their extensions to general treatment regimes exist, a vast majority of applications have been...
متن کاملCovariate Balancing Propensity Score for a Continuous Treatment: Application to the Efficacy of Political Advertisements∗
Propensity score matching and weighting are popular methods when estimating causal effects in observational studies. Beyond the assumption of unconfoundedness, however, these methods also require the model for the propensity score to be correctly specified. The recently proposed covariate balancing propensity score (CBPS) methodology increases the robustness to model misspecification by directl...
متن کاملParametric and Nonparametric Covariate Balancing Propensity Score for General Treatment Regimes∗
Propensity score matching and weighting are popular methods when estimating causal effects in observational studies. Beyond the assumption of unconfoundedness, however, these methods also require the model for propensity score to be correctly specified. The recently proposed covariate balancing propensity score (CBPS) methodology weakens this assumption by directly optimizing sample covariate b...
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ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series B (Statistical Methodology)
سال: 2013
ISSN: 1369-7412
DOI: 10.1111/rssb.12027