MF9580 – Epidemiological methods, beyond the basics
Schedule, syllabus and examination date
The course introduces causal graphs (DAGs) and modern designs in epidemiology. It also introduces multilevel analysis and will give a user oriented introduction to handling of missing data (by multiple imputation) in Stata. It also covers the use of splines to handle non-linearity in regressions.
The course has five main subjects:Causal graphs (DAGs), Modern Designs, Multiple Imputation, splines in regressions and Multilevel models. Also included are three minor subjects: Interaction, register epidemiology and an introduction to Stata.
Causal graphs introduce Directed Acyclic Graphs (DAGs) and will show examples of their use in medical research. DAGs are useful tools for understanding confounding, mediation and selection bias. A DAG analysis shows variables that should be adjusted for, and variables that should not be adjusted for.
The Design part will review classic research designs; cross sectional, cohort and case control. Focus will be on more advanced designs such as nested case control, case cohort and cross over designs. Strengths and weaknesses of the different designs will be discussed and examples of the different designs presented.
Multiple imputation: The lecture gives a short introduction to different missing-data mechanisms and how to handle missing data. The focus will be on multiple imputation, describing the concept of the method, how to choose a suitable imputation model, statistical inference, and challenges. Relevant Stata commands will be given and demonstrated through some examples.
Continuous variables and Splines: Categorizing continuous variables in a regression leads to loss of power. Instead, non-linear effects can be handled by using splines. We will provide Stata commands and examples of use.
Multilevel models gives an introduction to studies that lead to hierarchical data, what problem this gives in the analysis, and how to solve them. Focus is more on the interpretation of results than on the technical aspects of multi-level analysis.
The three last sessions will include workshops using Stata. Please bring your own laptops. Students associated with UiO will get access to Stata (via kiosk). We can work 2-3 persons per computer.
PhD candidates at UiO will have first priority at admission to the course. The maximum number of participant is 40.
PhD candidates admitted to a PhD programme at UiO apply in StudentWeb
Applicants who are not admitted to a PhD programme at UiO must apply for a right to study in SøknadsWeb before they can apply for PhD courses in medicine and health Sciences.
Formal prerequisite knowledge
The course is intended for students with knowledge of basic epidemiological methods, and possibly some experience with analysis of data.
Recommended previous knowledge
MF9230 Course in Clinical, Epidemiological and Community Medicine or other introductory courses in epidemiology.
Epidemiology – An Introduction. Ed. Kenneth J. Rothman, 2002.
The course last for 5 days, every day from 9:00 to 16:00
Note that you have to participate in at least 80 % of the teaching to be allowed to take the exam. Attendance will be registered.
A take-home exam will be given at the end of the course.
Use of sources and citation
Grades are awarded on a pass/fail scale. Read more about the grading system.
Explanations and appeals
Resit an examination
Withdrawal from an examination
It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.
Special examination arrangements
Application form, deadline and requirements for special examination arrangements.
The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation.