Course catalogue doctoral education - VT24
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Title | Design and Analysis of Twin and Family-Based Studies |
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Course number | 2893 |
Programme | Epidemiologi |
Language | English |
Credits | 1.5 |
Date | 2022-03-28 -- 2022-04-01 | Responsible KI department | Institutionen för medicinsk epidemiologi och biostatistik |
Specific entry requirements | 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 |
Purpose of the course | This course focuses on potential designs and analyses using twin- and family-data. Methods to estimate within-family associations and heritability are covered. |
Intended learning outcomes | After successfully completing this course you as a participant are expected to be able to:
- discuss the difference between a within-family analysis and a more standard (e.g. between-family) statistical analysis, - select an appropriate within-family/heritability analysis for a given dataset, based on a specific research question, - discuss how to perform within-family/heritability analyses using the statistical software R, - interpret the output from a within-family/heritability analysis, and compare with a more standard statistical analysis, - discuss assumptions made in heritability analysis, and how violations may affect the results. |
Contents of the course | 1. In this course we will focus on the theory and practice of within-family analyses.
The aim of empirical research is often to estimate the causal effect of a particular exposure on a particular outcome. A complicating feature of observational studies is that the exposure-outcome association is typically confounded, and cannot be given a causal interpretation. The standard approach to deal with confounding is to control for confounders in the analysis, e.g. by regression modelling. However, many confounders may be difficult to measure, or unknown to the investigator. An appealing solution is to study within-family associations, which are automatically controlled for all factors that are shared within the family (e.g. socioeconomic status, genetic factors). 2. In this course we will cover the concept of heritability, its underlying assumptions, and applications in the classic twin method. In many studies, the research question is to what extent a phenotype is caused by genetic factors. Frequently though, there may be no obvious candidate gene, and financial limitations may prohibit a genome wide scan. An appealing solution is to study whether the phenotype tends to run in families; the stronger genetic influence, the larger familial heredity. A commonly used design to estimate the fraction of variation in an outcome which may be attributable to genes and environment is the classic twin methodology. 3. In this course we will also compare and contrast within-family and bivariate heritability analysis (i.e., quantitative genetic analysis of two phenotypes), two methods that complement each other. Although within-family analyses require fewer assumptions, bivariate heritability analyses may yield additional information. |
Teaching and learning activities | Different strategies for teaching and learning, such as interactive lectures, small group discussions and exercises on selected topics, will be used. |
Compulsory elements | The individual examination. |
Examination | The individual examination will be a written take-home exam.
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. Students who do not obtain a passing grade at the first two examinations will be given top priority for admission the next time the course is offered. If the course is not offered during the following two academic semesters, then a third examination will be scheduled within 12 months of the final day of the course. |
Literature and other teaching material | Suggested reading:
Allison PD. (2009). Fixed effects regression models, Quantitative Applications in the Social Sciences, Vol. 160. SAGE: Los Angeles. Neale & Maes (2004). Methodology for Genetic Studies of Twins and Families. Kluwer Academic Publishers B.V. Dordrecht, The Netherlands. Available at http://ibgwww.colorado.edu/workshop2004/cdrom/HTML/book2004a.pdf |
Number of students | 8 - 25 |
Selection of students | Eligible doctoral students will be prioritized according to 1) the relevance of the course syllabus for the applicant’s doctoral project (according to written information), 2) date for registration as a doctoral student (priority given to earlier registration date). To be considered, submit a completed application form. Give all information requested, including a short description of current research training and motivation for attending, as well as an account of previous courses taken. |
More information | |
Additional course leader | |
Latest course evaluation | Course evaluation report |
Course responsible |
Ralf Kuja-Halkola Institutionen för medicinsk epidemiologi och biostatistik Ralf.Kuja-Halkola@ki.se |
Contact person |
Gunilla Nilsson Roos Institutionen för medicinsk epidemiologi och biostatistik 08-524 822 93 gunilla.nilsson.roos@ki.se |
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