Times: 9.00am – 5.30pm on both days
Course leaders: Bianca De Stavola, Rhian Daniel and Richard Silverwood from the PATHWAYS node of the ESRC National Centre for Research Methods (NCRM), London School of Hygiene and Tropical Medicine
Lecture 1 gives an introduction to key concepts in causal inference: to the language of counterfactuals (part A) and to causal diagrams (part B), and is accompanied by a pen & paper practical. Lectures 2-5 cover in more detail particular statistical methods used in causal inference, grouped according to the sort of causal question they address, and the structure of the data available to answer them. Each of these lectures is followed by a computer practical using Stata.
The two days split into `simple’ causal questions (on the first day) and `complex’ causal questions (on the second). By `simple’ causal questions, we mean questions of the type `what is the causal effect of a single exposure A, such as educational achievement, on a single outcome Y, such as blood pressure?’. By `complex’, on the other hand, we mean causal questions concerning the effect of time-changing exposures, and questions concerning pathways, such as how much of the causal effect of A on Y is mediated by a third variable M?
At whom is the course aimed?
The course is aimed at researchers working in the social or medical sciences. No prior knowledge of causal inference methods is assumed, but familiarity with standard statistical techniques such as linear and logistic regression is required. The computer practicals will be carried out using the Stata software, familiarity with which would be highy beneficial.