Numbers to the right of topics indicate sequential lecture numbers.
Hn stands for Harrell Chapter n in the book's second edition. Ln stands for lecture n.
Introduction (H1) L1
Course overview and logistics
Course philosophy
Hypothesis testing vs. estimation vs. prediction
Examples of multivariable prediction problems
Misunderstandings about classification vs. prediction (read this also)
Study planning considerations
Choice of model
Model uncertainty/data driven model selection/phantom d.f.
General methods for multivariable models (H2) L2
Notation for general regression models
Model formulations
Interpreting model parameters
nominal predictors
interactions
Review of chunk tests
Relaxing linearity assumption for continuous predictors