Dan Garant

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Propensity score matching (PSM) is a widely used method for performing causal inference with observational data. PSM requires fully specifying the set of confounding variables of treatment and outcome. In the case of relational data, this set may include non-intuitive relational variables, i.e., variables derived from the relational structure of the data.(More)
The predominant method for evaluating the quality of causal models is to measure the graph-ical accuracy of the learned model structure. We present an alternative method for evaluating causal models that directly measures the accuracy of estimated interventional distributions. We contrast such distributional measures with structural measures, such as(More)
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