Matching estimators for causal effects of multiple treatments

Matching to estimate the causal effects from multiple treatments

The propensity score is a common tool for estimating the causal effect of a binary treatment using observational data. In this setting, matched methods, defined as either individual matching, subclassifying, or using inverse probability weighting on the propensity score, can reduce the initial covariate bias between the treatment and control groups. With more than two treatment options, however...

Causal Inference by Minimizing the Dual Norm of Bias: Kernel Matching & Weighting Estimators for Causal Effects

We consider the problem of estimating causal effects from observational data and propose a novel framework for matchingand weighting-based causal estimators. The framework is based on expressing the bias of a causal estimator as an operator on the unknown conditional expectation function of outcomes and formulating the dual norm of the bias as the norm of this operator with respect to a functio...

Matching Estimators of Causal Effects Prospects and Pitfalls in Theory and Practice

As the counterfactual model of causality has increased in popularity, sociologists have returned to matching as a research methodology. In this article, advances over the past two decades in matching estimators are explained, and the practical limitations of matching techniques are emphasized. The authors introduce matching methods by focusing first on ideal scenarios in which stratification an...

Simultaneous Causal Inference for Multiple Treatments via Sufficiency

Estimating causal effects for multivalued treatments: a comparison of approaches.

Interventions with multivalued treatments are common in medical and health research, such as when comparing the efficacy of competing drugs or interventions, or comparing between various doses of a particular drug. In recent years, there has been a growing interest in the development of multivalued treatment effect estimators using observational data. In this paper, we compare the performance o...