STA5062Z - Causal Modelling

15 credits at NQF level 9

Entry Requirements:

Acceptance into Master's programs in Advanced Analytics, Data Science or Biostatistics, and/ or statistical background deemed sufficient by the Head of Department.

Course Outline:

This course introduces students to the concept of causality, causal diagrams and causal modelling. Topics to be covered include Counterfactual Theory, Directed Acyclical Graphs, Propensity Scores, Inverse Probablity Weighting, Marginal Structural Models, G-estimation, Path Analysis, Confirmatory Factor Analysis, Structural Equation Modeling (SEM), Multiple Group SEM, MIMIC (Multiple Indicators and Multiple Causes) Models, Multilevel SEM, and Latent Growth Curve SEM. The course covers both the theory and the application of the methods with computer software such as R, STATA and LISREL. The course may not be offered every year.