Contents
causal-inference
Common Identification Strategies and Program Evaluation • Dec 26, 2023
The Assumptions We Take for Granted • Mar 8, 2023
The Non-Collapsibility of Logistic Regressions • May 24, 2022
Random Stuff Cancels Out, Right? • Dec 27, 2021
Multicollinearity or Omitted Variable Bias? Answers to a Seeming Conundrum • Dec 20, 2021
exposition
Common Identification Strategies and Program Evaluation • Dec 26, 2023
Cluster Distance in Hierarchical Clustering • Jun 13, 2023
The Assumptions We Take for Granted • Mar 8, 2023
Training Word Embeddings • Jul 12, 2022
The Non-Collapsibility of Logistic Regressions • May 24, 2022
The Thing about LSTM and Exploding Gradients • Apr 11, 2022
PDP, M-Plot, and ALE • Mar 23, 2022
Random Stuff Cancels Out, Right? • Dec 27, 2021
Multicollinearity or Omitted Variable Bias? Answers to a Seeming Conundrum • Dec 20, 2021
An Intuitive Explanation of ROC and AUC • Nov 23, 2021
machine-learning
Cluster Distance in Hierarchical Clustering • Jun 13, 2023
The Assumptions We Take for Granted • Mar 8, 2023
Training Word Embeddings • Jul 12, 2022
The Thing about LSTM and Exploding Gradients • Apr 11, 2022
PDP, M-Plot, and ALE • Mar 23, 2022
An Intuitive Explanation of ROC and AUC • Nov 23, 2021
Bias, Discrimination, and Algorithmic Fairness • Aug 11, 2018
research
ForestIV • Jan 10, 2022
A Collection of Natural Experiments and Research Opportunities • Jan 5, 2022
Bias, Discrimination, and Algorithmic Fairness • Aug 11, 2018