Introduction
This course will give a broad overview of topics in meta-analysis. Most standard topics in meta-analysis will be covered, such as risk of bias analysis, searching studies, fixed versus random effect models, heterogeneity, publication bias, differences between meta-analysis of randomized trials and meta-analysis observational studies. The course will briefly cover some more advanced topics (bivariate meta-analysis, combining different metrics, network analysis).
Course material
All study materials are supplied electronically only in the Boerhaave Learning Environment, and will be made available about 2 weeks prior to the course.
Prerequisites
Basic knowledge of statistics (equivalent to the Boerhaave course "Basic methods and reasoning in Biostatistics").
A computer / laptop with proper internet access for all participants is mandatory. Students also need the STATA software or R software (R and R studio) pre-installed. No pre-knowledge of the software is required. A temporary Stata license will be provided. In practical sessions, students will perform a standard meta-analysis by themselves.
Teaching environment
Lectures and practical sessions
Certificate of attendance
In order to obtain a proof of participation, all lectures should be attended. If you have participated for the full 3 days, you will receive a certificate of attendance within two weeks. Those who are enrolled in the Epidemiology-B programme of the department of clinical epidemiology, should make an extra post-course assignment, which will be graded.
Language
Course material (PowerPoint, exercises etc.) are all in English. Lectures are also in English.
Target group
Master and PhD students in the bio-medical sciences.
Organizing committee
- Prof. dr. Olaf Dekkers
- Prof. dr. Saskia le Cessie
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WEDNESDAY 19 APRIL 2023 |
08.45 |
Registration |
09:00 |
Introduction to the course
Prof. dr. Olaf Dekkers |
09:10 |
Meta-analysis: Why & how?
Prof. dr. Olaf Dekkers |
10:15 |
Break |
10:30 |
The statistical approach
Prof. dr. Saskia le Cessie |
11:30 |
Heterogeneity and risk of bias
Prof. dr. Olaf Dekkers |
12:45 |
Lunch break |
13:15 |
Pooling effect estimates I
Prof. dr. Saskia le Cessie |
14:15 |
Practical 1: Pooling effects
Prof. dr. Saskia le Cessie |
15:15 |
End of day 1 |
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|
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THURSDAY 20 APRIL 2023 |
08:45 |
Registration |
09:00 |
Heterogeneity: Statistical
Prof. dr. Saskia le Cessie |
10:00 |
Publication bias
Prof. dr. Olaf Dekkers |
10:30 |
Break |
10:45 |
Meta-analysis of observational studies
Prof. dr. Olaf Dekkers |
11:30 |
Practical 2: Risk of bias analysis
Prof. dr. Olaf Dekkers |
12:30 |
Lunch break |
13:15 |
Publication bias: Statistical
Prof. dr. Saskia le Cessie |
14:45 |
Break |
15:00 |
Practical 3: Publication bias and meta regression
Prof. dr. Saskia le Cessie |
16:00 |
End of day 2 |
|
FRIDAY 21 APRIL 2023 |
08:45 |
Registration |
09:00 |
Pooling different effect measures
Prof. dr. Olaf Dekkers |
09:45 |
Break |
10:00 |
Pooling effect estimates : binary outcomes
Prof. dr. Saskia le Cessie |
11:15 |
Practical 4: Publication bias and meta regression
Prof. dr. Saskia le Cessie |
12:00 |
Lunch break |
13:00 |
Tips and tricks for data-extraction
Prof. dr. Saskia le Cessie |
14:00 |
Network meta analyses + practical
Prof. dr. Saskia le Cessie |
15:00 |
Final remarks
Prof. dr. Saskia le Cessie |
15:30 |
End of course |
Prof. dr. Cessie, S. Le (EPI)
LUMC, Hoogleraar Epidemiologie
Prof. Dr. O.M. Dekkers
Endocrinoloog en klinisch epidemioloog, LUMC
LUMC
Albinusdreef 2, 2333 ZA Leiden
Regular course fee |
€ 550,- |
Reduced fee for PhD students LUMC |
€ 150,- |
Reduced fee for employees LUMC |
€ 150,- |
BA/MA students of the Leiden University |
Free of charge * |
BA/MA students of other universities (non Leiden University) |
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€ 75,-* |
* Limited places available. In order to validate your student registration, you must register with your student e-mail address and submit your student number on the registration form. In addition, a scan of your student pass will have to be submitted to boerhaavenacholing@lumc.nl. Please note that a € 45,- cancellation fee will be charged to students who do not attend the course (no show), or cancel their registration.