Syllabus database for doctoral courses
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Syllabus database for doctoral courses
SYLLABI FOR DOCTORAL COURSES
| Swedish title | Metoder i livsförloppsepidemiologi |
|---|---|
| English title | Methods for Life Course Epidemiology |
| Course number | 2968 |
| Credits | 1.5 |
| Responsible KI department | Institutet för miljömedicin |
| Specific entry requirements | Knowledge equivalent to "Epidemiology I: Introduction to epidemiology", "Biostatistics I: Introduction for epidemiologists", "Epidemiology II: Design of epidemiological studies", "Biostatistics II: Logistic regression for epidemiologists" and "Biostatistics III: survival analysis for epidemiologists" or corresponding courses. |
| Grading | Passed /Not passed |
| Established by | The Committee for Doctoral Education |
| Established | 2020-02-26 |
| Purpose of the course | The course critically reviews life course theory and methods for analysis of longitudinal data with applications to life course epidemiology. A special focus is put on discussing and applying methods for mediation analysis. |
| Intended learning outcomes | After successfully completing this course, the student is expected to be able to:
- Discuss the most common life course models and their implications for health policy - Evaluate strengths and limitations in using register data for research in life course epidemiology - Explain the applicability of visualization techniques for research in life course epidemiology - Identify and apply appropriate methods for mediation analysis - Perform mediation analysis, and interpret and communicate the derived results - Critically appraise evidence from life course epidemiological studies. |
| Contents of the course | This course focuses on an overview and critical discussion of life course theory and methods for analysis of longitudinal data with applications to life course epidemiology. We shall review, discuss and apply different approaches to addressing common challenges in register-based, life course and intergenerational research through both methodological innovations and adaptation of existing statistical methods. Examples of techniques to be discussed and applied include methods for visualizing and modeling changes in categorical variables, modeling the effects of binary exposure variables over the life course, and techniques for mediation analyses. We shall also discuss and apply concepts and methods from the field of causal inference to life course studies. The statistical software used in the lectures and computer labs is Stata. |
| Teaching and learning activities | Lectures, computer labs and individual and group work involving analysis of real-life research problems using longitudinal data and a statistical software (Stata). |
| Compulsory elements | Individual written examination (summative assessment). |
| Examination | To pass the course, the student has to show that the intended learning outcomes have been achieved. The assessment methods used in this course are individual and group assignments (formative assessment) and an individual take-home examination (summative assessment). The focus will be on application of methods to research problems and interpretation of results, rather than mathematical detail. The examination is viewed as contributing to the development of knowledge, rather than a test of that knowledge. Students who do not obtain a passing grade in the first examination will be offered a second examination within two months of the final day of the course. |
| Literature and other teaching material | Suggested reading:
Ben Shlomo Y, Mishra G and Kuh D. Life course epidemiology. Pp. 1521-1549. In: W. Ahrens, I. Pigeot (eds.) Handbook of Epidemiology, 2nd edition, DOI 10.1007/978-0-387-09834-0 56, © Springer Science+Business Media New York 2014. http://link.springer.com/referenceworkentry/10.1007%2F978-0-387-09834-0_56 De Stavola BL, Daniel RM. Incorporating concepts and methods from causal inference into life course epidemiology (Commentary). Int J Epidemiol. 2016;45:1006-1010. doi: 10.1093/ije/dyw103 Miguel A. Hernán, John Hsu & Brian Healy (2019) A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks, CHANCE, 32:1, 42-49, DOI:10.1080/09332480.2019.1579578. Howe LD, Smith AD, Macdonald-Wallis C, Anderson EL, Galobardes B, Lawlor DA, Ben-Shlomo Y, Hardy R, Cooper R, Tilling K, Fraser A. Relationship between mediation analysis and the structured life course approach. Int J Epidemiol. 2016 Aug;45(4):1280-1294. DOI: 10.1093/ije/dyw254 Mishra GD, Chiesa F, Goodman A, De Stavola B, Koupil I. Socio-economic position over the life course and all-cause, and circulatory diseases mortality at age 50-87 years: results from a Swedish birth cohort. Eur J Epidemiol 2013;28(2),139-47. |
Course responsible |
Anita Berglund Institutet för miljömedicin Anita.Berglund@ki.se |
| Contact person |
Johanna Bergman Institutet för miljömedicin johanna.bergman@ki.se Nobels väg 13 17177 Stockholm |
