Leslie Myint

K-Nearest Neighbors Regression

Logistic Regression

Overfitting

LASSO (Shrinkage/Regularization)

Estimating Causal Effects: Regression

Modeling Nonlinearity: Polynomial Regression and Splines

K-Nearest Neighbors Regression

Introduction to Causal Graphs

Asking Clear Questions and Building Graphs

Evaluating Classification Models

Decision Trees

D-Separation

Cross-validation

Evaluating Regression Models

KNN Regression and the Bias-Variance Tradeoff

Key Structures in Causal Graphs

Mediation Analysis

Local Regression and Generalized Additive Models

Study Designs in Causal Inference

Polynomial Regression and Splines

Estimating Causal Effects: Inverse Probability Weighting

Sensitivity Analyses for Unmeasured Variables

Causal Discovery