Course catalogue doctoral education - VT24
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Title | Causal Inference: emulating a Target Trial to Assess Comparative Effectiveness |
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Course number | 3046 |
Programme | Epidemiology |
Language | English |
Credits | 1.5 |
Date | 2024-04-02 -- 2024-04-05 | Responsible KI department | The institute of Environmental Medicine |
Specific entry requirements | Courses "Epidemiology I: Introduction to epidemiology", "Epidemiology II: Design of epidemiological studies", "Biostatistics I: Introduction for epidemiologists", "Biostatistics II: Logistic regression for epidemiologists" or corresponding courses. |
Purpose of the course | This course focuses on a general framework for the assessment of comparative effectiveness and safety research, which can be applied to both observational data and randomized trials. |
Intended learning outcomes | After successful completion of this course, the student should be able to:
- Formulate sufficiently well-defined causal questions for comparative effectiveness research - Specify the protocol of the target trial - Design analyses of observational data that emulate the protocol of the target trial - Identify key assumptions for a correct emulation of the target trial - Decide when g-methods are required for data analysis - Critique observational studies and randomized trials for comparative effectiveness research |
Contents of the course | The course introduces students to a general framework for the assessment of comparative effectiveness and safety research. The framework, which can be applied to both observational data and randomized trials with imperfect adherence to the protocol, relies on the specification of a (hypothetical) target trial. The course explores key challenges for comparative effectiveness research and critically reviews methods proposed to overcome those challenges. The methods are presented in the context of several case studies for cancer, cardiovascular, renal, and infectious diseases. |
Teaching and learning activities | Lectures, group sessions and self-studies of the course literature. |
Compulsory elements | The individual written examination (summative assessment). |
Examination | A written individual take-home examination will be carried out after the course. 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 | Mandatory course literature:
Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC. Prior to the course days, read chapters 1-3. The book can be downloaded (for free) from https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ |
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 | Pre-course reading is required: Chapters 1-3 of the book: Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC. The book can be downloaded (for free) from https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/. The individual examination will be performed as a take-home examination. The course is given on-site at Campus Solna. |
Additional course leader | Additional main teacher: Miguel Hernán, Director of the CAUSALab, Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health, Boston, USA, Principal Reseacher at CAUSALab IMM, Karolinska Institutet. Faculty website: https://www.hsph.harvard.edu/miguel-hernan/ |
Latest course evaluation | Course evaluation report |
Course responsible |
Anthony Matthews The institute of Environmental Medicine anthony.matthews@ki.se |
Contact person |
Johanna Bergman Institutet för miljömedicin johanna.bergman@ki.se Nobels väg 13 17177 Stockholm |