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IJMPR Didactic Paper: Weighting for Causal Inference in Mental Health Research
Eric R Cohn1, José R Zubizarreta2,3,4
1Westat, New York, New York, USA.
Objective:
Inverse probability weighting is a fundamental and general methodology for estimating the causal effects of exposures and interventions, but standard approaches to constructing such weights are often suboptimal.
Methods:
In this paper, we describe a recent approach for constructing such weights that directly balances covariates while optimizing the stability of the resulting weighting estimator.
Results:
To illustrate the use of this approach in mental health research, we present an exploratory study of the effects of exposure to violence on the risk of suicide attempt.
Conclusions:
The direct balancing approach to weighting should be given strong consideration in empirical research due to its robustness and transparency in building weighting estimators.
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