Longitudinal Analysis and Causal Inference

17-28 July 2017





Michael G Hudgens PhD

Tobias Chirwa, PhD

Professor of Biostatistics

Associate Professor of Bios and Epid

University of North Carolina

Head, Witwatersrand SPH




HW assignment: Due 24 July

Lab assignments for 27-28 July

Final assignment: Due 11 Aug

Causal Inference by Hernan and Robins



Lecture Notes


1 A definition of causal effect

2 Randomized experiments

3 Observational studies

4 Effect modification

5 Interaction

6 DAGs

7 Confounding

8 Selection bias

9 Measurement bias

10 Random variability

11 Why model?

12 Marginal structural models

13 Parametric g-formula

14 Structural nested models

15 Outcome reg. & p-scores

Time varying exposures


Data and Code

NHEFS data codebook sas7bdat xls csv

11 Introduction R SAS Stata

12 Marg. structural models R SAS Stata

13 Parametric g-formula R SAS Stata

14 Structural nested models R SAS Stata

15 Outcome reg. & p-scores R SAS Stata