I stumbled accros this incredibly interesting read by Mark White, who discusses the (academic) theory behind, inner workings, and example (R) applications of causal random forests: EXPLICITLY OPTIMIZING ON CAUSAL EFFECTS VIA THE CAUSAL RANDOM FOREST: A PRACTICAL INTRODUCTION AND TUTORIAL (By Mark White) These so-called “honest” forests seem a great technique to identify opportunities…

# Tag: effects

## Propensity Score Matching Explained Visually

Propensity score matching (wiki) is a statistical matching technique that attempts to estimate the effect of a treatment (e.g., intervention) by accounting for the factors that predict whether an individual would be eligble for receiving the treatment. The wikipedia page provides a good example setting: Say we are interested in the effects of smoking on…

## Animating causal inference methods

Some time back the animations below went sort of viral in the statistical programming community. In them, economics professor Nick Huntington-Klein demonstrates step-by-step how statistical tests estimate effect sizes. You will find several other animations in Nick’s original blog, and the associatedtwitter thread. Moreover, if you are interested in the R code to generate these…