MEDFL5580 – Epidemiological methods, beyond the basics
Course description
Course content
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.
Learning outcome
The course has five main subjects:
- Causal graphs (DAGs)
- Modern Designs
- Multiple Imputation
- Splines in regressions
- Multilevel models
Also included are three minor subjects:
- Interaction
- Register epidemiology
- 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.
Admission to the course
The course is reserved for students at the Medical Student Research Programme at the Faculty of Medicine and the Faculty of Dentistry, UiO.
Students sign up for?classes and exam to this course in StudentWeb
Applicants will upon registration receive an immediate reply in StudentWeb?as to whether a seat at this course is granted or not.
Recommended previous knowledge
The course is intended for students with knowledge of basic epidemiological methods, and possibly some experience with analysis of data.
MEDFL5230 Course in Clinical, Epidemiological and Community Medicine or other introductory courses in epidemiology.
Recommended reading prior to the course: Epidemiology - An Introduction. Ed. Kenneth J. Rothman.
Overlapping courses
- 4 credits overlap with MF9580 – Epidemiological methods, beyond the basics.
- 3 credits overlap with MF9580 – Epidemiological methods, beyond the basics.
Teaching
The course is organized as a full-time course over five days.
The three last sessions will include workshops using Stata. Student should bring own laptops.?
You have to participate in at least 80 % of the teaching to be allowed to take the exam. Attendance will be registered.
Examination
Home exam to be submitted after the course.
Language of examination
The examination text is given in English. You may submit your response in Norwegian, Swedish, Danish or English.
Grading scale
Grades are awarded on a pass/fail scale. Read more about the grading system.
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