Course catalogue doctoral education - VT24

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Title Transporting Treatment Effects from Randomized Trials to Target Populations
Course number 5649
Programme Epidemiologi
Language English
Credits 1.5
Date 2023-04-17 -- 2023-04-21
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", and "Biostatistics II: Logistic regression for epidemiologists" or corresponding courses.
Purpose of the course The course will provide participants with understanding of why and how one should undertake transportability analyses to estimate treatment effectiveness and safety in populations that are not included in randomized trials.
Intended learning outcomes After successfully completing this course, the student is expected to be able to:
- Define and explain the importance of external validity
- Identify suitable target populations using observational data
- Use data visualization techniques to inform methodological decisions
- Interpret and communicate results that have been transported from a randomized trial to several target populations
- Motivate why these methods fit into the Swedish research landscape
Contents of the course We will discuss the theory underlying external validity, present several methods used for transporting treatment effects from randomized trials to defined target populations (weighting and outcome modelling), and consider where and how these methods fit into the Swedish health research landscape. Participants will be provided with analytic R or SAS code to create output from transportability analyses that use data from a randomized trial and various simulated target populations. We will also show how to effectively use data visualization to guide decisions about transport model specification and performance and discuss how to interpret results.
Teaching and learning activities Lectures, computer labs, and individual and group work involving analysis of real-life research problems related to the external validity of treatment effects estimated in randomized trials.
Compulsory elements Individual written examination (summative assessment).
Examination To pass the course, the student must show that the intended learning outcomes have been achieved. The assessment methods used in this course are individual and group assignments (formative assessments) and an individual take-home examination (summative assessment). The focus will be to understand transportability methods to address specific research questions and interpret analytic results, rather than a detailed focus on mathematical principles. 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
Number of students 8 - 25
Selection of students Eligible doctoral students are prioritized according to 1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation), 2) date for registration as a doctoral student. 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. Prior knowledge in any software, e.g. Stata, R or SAS is recommended.
More information
Additional course leader Additional course leaders will be Jennifer L. Lund, PhD, Associate Professor, Dept. of Epidemiology, University of North Carolina at Chapel Hill (jennifer.lund@unc.edu), and Michael Webster-Clark, PharmD, PhD, Postdoctoral Fellow, McGill University (mawc@live.unc.edu).
Latest course evaluation Not available
Course responsible Anthony Matthews
Institutet för miljömedicin

anthony.matthews@ki.se
Contact person Johanna Bergman
Institutet för miljömedicin

johanna.bergman@ki.se

Nobels väg 13

17177
Stockholm