Additional Reading Suggestions


Life did not stop when we finished the manusdcript. Actually, we keep finding great stuff. So let us make some suggestion for additional readings per chapters.

Part I

Part II

Chapter 09

Regarding external validity, one way to check robustness is to take out 1% of the data and repeat the exercise. The simple take is to do it many times randonly + many times by edge of distribution of key variables. The smart take is suggested by Tamara Broderick, Ryan Giordano, Rachael Meager in “An Automatic Finite-Sample Robustness Metric: Can Dropping a Little Data Change Conclusions?” Hard-core statistics. Preprint

Part III

Chapter 16

On the partial dependence plots, you may check out both a very useful review of R’s pdp package as well as Christoph Molnar’s Interpretable ML book.

On similar house prediction project, Julia Silge does a super nice job hoing through steps, showing graphs. Making great use of text. Boosted trees. Tidymodels and more. Check out her post and video: Predict housing prices in Austin TX with tidymodels and xgboost

Part IV

Chapter 19

On DAGs and Potential outcomes, deep discussion for social scientists: Imbens, Guido W. 2020. “Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics.” Journal of Economic Literature, 58 (4): 1129-79. LINK to paper. An amazing review that includes Twitter quotes.

Chapter 19

Beetroot juice is said to be great. Review study Another review. For example, reference to an RCT with beetroot juice – dietary inorganic nitrate acutely reduces blood pressure. Study. Review in medical journal