From 8b08d831b5de0831ea5ff1210bd2db88fcbe70cc Mon Sep 17 00:00:00 2001 From: Erik Sverdrup Date: Wed, 25 Sep 2024 17:21:10 +1000 Subject: [PATCH] Add extra video link to intro vignette (#1454) --- r-package/grf/vignettes/grf_guide.Rmd | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/r-package/grf/vignettes/grf_guide.Rmd b/r-package/grf/vignettes/grf_guide.Rmd index 238aa74b1..8b821a9f2 100644 --- a/r-package/grf/vignettes/grf_guide.Rmd +++ b/r-package/grf/vignettes/grf_guide.Rmd @@ -27,7 +27,7 @@ This vignette gives a [brief overview](#a-grf-overview) of the GRF algorithm and * The [rank_average_treatment_effect](https://grf-labs.github.io/grf/reference/rank_average_treatment_effect.html) (*RATE*) as a generic tool to assess heterogeneity and the effectiveness of "targeting rules", as well as how the associated *TOC* curve can help identify segments of a population that respond differently to a treatment. -* [policytree](https://github.com/grf-labs/policytree) to find a tree-based policy using the estimated CATEs. +* [policytree](https://github.com/grf-labs/policytree) to find a tree-based policy. ## A grf overview @@ -405,7 +405,9 @@ qini.age * [Machine Learning & Causal Inference: A Short Course](https://www.youtube.com/playlist?list=PLxq_lXOUlvQAoWZEqhRqHNezS30lI49G-) (video lectures) -* [Causal Inference: A Statistical Learning Approach](https://web.stanford.edu/~swager/causal_inf_book.pdf) (book) +* [Estimating Heterogeneous Treatment Effects in R](https://www.youtube.com/watch?v=YBbnCDRCcAI) (video tutorial) + +* [Causal Inference: A Statistical Learning Approach](https://web.stanford.edu/~swager/causal_inf_book.pdf) (textbook)