Course - Epidemiology II - SMED8002
SMED8002 - Epidemiology II
Examination arrangement: Home examination
Grade: Passed / Not Passed
|Evaluation||Weighting||Duration||Grade deviation||Examination aids|
Study design, measures of disease occurrence, measures of effect, intern validity, Directed acyclic graphs (DAGs), interpretation of multivariable models, causal inference, causal interaction and effect measure modification, screening, instrumental variable estimation, family designs, case only designs.
- have basic knowledge of various study designs that are most common in population-based and clinical research (cross-sectional studies, cohort studies, case-control studies and randomized controlled trials).
- be able to interpret different measures of disease occurrence (prevalence, incidence proportion and incidence rate).
- be able to interpret different measures of the relationship between exposure / treatment and disease based on absolute and relative risk (risk difference, incidence rate difference, numbers needed to treat versus risk ratio, incidence ratio, odds ratio, hazard ratio)
- have basic knowledge of common challenges in observational studies (selection bias, information bias and confounding).
- have basic knowledge of and be able to interpret Directed asyclyc graphs (DAGs)
- have a basic understanding of assessment of precision in epidemiological studies with emphasis on interpretation and use of p-values and confidence intervals
- understand the principles and be able to interpret multivariable analyzes.
- be able to distinguish between and have knowledge of the concepts: causal effect (causality) and statistical association.
- be able to distinguish between causal interaction and effect measure modification
- have basic knowledge of screening
- know the principles of instrument variable analysis, different family designs and case only studies
Learning methods and activities
Teaching modalities: Lectures and problem solving.
- Practice tasks
- Mandatory attendance at lectures
Recommended previous knowledge
Recommended background knowledge: KLMED8009 Clinical Research, KLMED8004 Medical statistics 1, KLMED8005 Medical statistics 2 Introductory course in epidemiology (eg. master course in epidemiology)
Required previous knowledge
Admission requirements: Master degree or similar. Medical students at The Student Research Programme. Candidates with a lower degree will be assessed individually.
Hernan M, Robins J: Part I, Part II, chapter 16, https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/
Rothman K, Greenland S and Lash (2012): Chapter 2, 3, 5-10 in Modern epidemiology
Hernán MA, Hernández-Díaz S, Werler MM, Mitchell AA. Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology. Am J Epidemiol 2002;155:176-184
Hernán MA, Hernández-Díaz S, Robins JM (2004): A structural approach to selection bias. Epidemiology. 2004 Sep;15(5):615-25.
JanszkyI, Ahlbom A, Svensson AC (2010): The Janus face of statistical adjustment: confounders versus colliders. Eur J Epidemiol. 2010 Jun;25(6):361-3. Epub 2010 May 7.
Glymour M, Weuve J, Berkman L, Kawachi I, Robins J. When is baseline adjustement usuful in analysis of change? An example with education and cognitive change. Am J Epid 2005; 162:267-78
Krieger N, Davey Smith G. The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology. Int J Epidemiol 2016; 45: 1787-808.
Credits: 7.5 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: SPRING 2023
Language of instruction: English
- Bjørn Olav Åsvold
- Eva Skovlund
- Gunnhild Åberge Vie
- Imre Janszky
- Johan Håkon Bjørngaard
- Kristine Pape
- Signe Opdahl
Department with academic responsibility
Department of Public Health and Nursing
Examination arrangement: Home examination
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
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- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"