| 1 |
14th Jan |
Introduction: Revision of concepts covered in Introduction to Epidemiology, discussion of course and assessment |
Prof David McAllister |
103B (Clarice Pears) |
| 2 |
21st Jan |
Causation: Concepts in causation 1 |
Dr Michal Shimonovich |
103B (Clarice Pears) |
| 3 |
28th Jan |
Causation: Concepts in causation 2 |
Dr Erik Igelstrom |
103B (Clarice Pears) |
| 4 |
4th Feb |
Approaches to estimate causal effects: Methods which can accommodate observed confounders (e.g. restriction, stratification, regression and matching) |
Prof Vittal Katikireddi |
103B (Clarice Pears) |
| 5 |
11th Feb |
Scale and effect measure modification: Understanding implications of competing risks for interpreting effects |
Dr Anna Pearce |
103B (Clarice Pears) |
| 6 |
18th Feb |
Reading week – drop-in Q&A session |
Prof Vittal Katikireddi |
TBC |
| 7 |
25th Feb |
Administrative data: Understanding typical data sources and pitfalls |
Dr Mike Fleming |
103B (Clarice Pears) |
| 8 |
4th March |
Competing risks: Understanding implications of competing risks of interpreting effects |
Prof David McAllister |
103B (Clarice Pears |
| 9 |
11th March |
Measurement of bias: Surveys, non-differential misclass and systematic bias |
Dr Eliud Kibuchi |
103B (Clarice Pears) |
| 10 |
18th March |
Approaches to estimate causal effects: Methods designed to accommodate unobserved confounding (e.g. regression, discontinuity, difference-in-difference, IVs, synthetic controls etc) |
Prof. Peter Craig |
103A (Clarice Pears) |
| 11 |
25th March |
Revision: Revision for course |
Prof Vittal Katikireddi, Prof David McAllister, Dr Anna Pearce |
103A (Clarice Pears) |