Matthew Fox, Professor in the Department of Global Health and Epidemiology at Boston University School of Public Health
By the end of this week, participants should be able to:
Use the sufficient cause model, counterfactual susceptibility type model, and a causal graph to assist with the design or analysis of an epidemiologic study.
Calculate adjusted measures of effect and select those that, when collapsible, correspond to the no-confounding condition. Use the adjusted measures of effect to estimate the direction and magnitude of confounding.
Distinguish effect measure modification, interdependence, and statistical interaction from one another as separate - but related - concepts of interaction.
Identify the likely magnitude and direction of bias due to misclassification of exposure, outcomes, confounders and modifiers. Weigh the advantages and disadvantages of significance testing.
Compare the advantages and disadvantages of frequentist and Bayesian approaches to analysis of a single study, to eveidence, and to changing your mind.
Basic knowledge of epidemiology and biostatistics
510 € for enrolled students (proof required)