Michael Johns: Propensity Score Matching: A Non-experimental Approach to Causal... | PyData NYC 2019

Full title: Michael Johns: Propensity Score Matching: A Non-experimental Approach to Causal Inference | PyData New York 2019

Propensity score matching provides an alternative framework for causal inference when random assignment is not possible. The technique draws on core data science skills of predictive model building and algorithm development. Data scientists who need alternatives to experiments will find this a useful and accessible addition to their methodological toolbox.

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