Making Causal Claims as a Data Scientist: Tips and Tricks Using R

By Lucy D'Agostino McGowan in Invited Oral Presentation

January 27, 2018


Making believable causal claims can be difficult, especially with the much repeated adage “correlation is not causation”. This talk will walk through some tools often used to practice safe causation, such as propensity scores and sensitivity analyses. In addition, we will cover principles that suggest causation such as the understanding of counterfactuals, and applying Hill’s criteria in a data science setting. We will walk through specific examples, as well as provide R code for all methods discussed.


January 27, 2018


12:00 PM – 1:00 PM


Data Day Texas 2018