Repeated Measurements [CE08]
Online modules, class days: Mon 06/04, Thu 09/04, Tue 14/04, Thu 16/04, Mon 20/04, Thu 23/04. Assignment deadline 8 May 2020.
Prof. Dimitris Rizopoulos, PhD
Erasmus MC, Rotterdam NL
The introduction to R course of NIHES and Using R for Statistics in Medical Research (BST02), previously part of Courses for the Quantitative Researcher (SC17) or equivalent knowledge. Familiarity with standard regression models such as the multiple linear regression and logistic regression model. No previous experience of repeated measurements analysis is required.
Detailed information about this course:
This course covers statistical methods to be used when one or more variables are repeatedly measured in time on the same experimental unit. For instance, in a clinical trial, the outcome variable can be measured at baseline and at different times during the treatment period. In a meta-analysis, the study can be regarded as the experimental unit and the observations of patients within the same study as repeated measurements.
In the last 10 or 15 years much progress has been made in the development of new methods of analysis. In recent years several of these new methods have been implemented in a wide variety of computer packages.
The course starts with a short overview of simple methods for analyzing repeated measurements data, followed by a short recap of the most basic concepts of linear algebra needed for the presentation of the most advanced models.
Then the main focus turns on more advanced methods. For approximately normally distributed repeated measurements outcomes marginal and linear mixed models are introduced. For non-normal responses, first the generalized estimating equations (GEE) approach for marginal inferences is presented, followed by extensions of random effects models to categorical outcomes. All these methods are exemplified using data from of clinical and epidemiological studies.
Computer practicals in the statistical programming language R will be used to acquire hands on experience in applying these techniques to real data. All code used during the course will be live demonstrated using a web app, which will be made avaliable to participants.
Participants need to bring their own laptop with certain pre-installed software (instructions will be given before start of the course). The assignment for this course needs to be handed in two weeks after the ending of the course on Friday 8 May 2020.
Please note that this courses has a blended design, which means that it includes both online modules and in-class meetings. The first meeting lasts 1 hour, the following meetings last 2 hours. The meetings are planned on the following days:
- Mon 6 April
- Thu 9 April
- Tue 14 April
- Thu 16 April
- Mon 20 April
- Thu 23 April
- Assignment deadline Fri 8 May
Ability to use statistical methods where one or more variables are repeatedly measured in time on the same experimental unit.
For everybody using repeated measurements in their (clinical) research.
Reduction on fees
PLEASE NOTE THIS DOES NOT APPLY TO THE RESEARCH MASTERS (120 EC points)
50% reduction on our fees for participating institutes of NIHES
This 50% reduction is offered to participants formally appointed at the departments or sections participating in NIHES.
University Medical Center Rotterdam/Erasmus University Rotterdam:
- Department of Epidemiology
- Department of Public Health
- Department of Psychiatry, Section of Medical Psychology and Psychotherapy
- Department of Child and Adolescent Psychiatry/Psychology
- Department of Medical Informatics
- Department of General Practice
- Erasmus School of Health Policy & Management
- Generation R
50% reduction on our fees for NIHES affiliated partners
This 50% reduction is offered to participants formally appointed at the following NIHES affiliated partners:
University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:
- General Paediatrics
- Plastic and Reconstructive Surgery
- Rehabilitation Medicine
UMIT, Department of Public Health, Health Services Research and Health Technology Assessment.
25% reduction on our fees for Erasmus MC employees
For participants formally appointed at all departments of Erasmus MC (except the departments mentioned above).
25% reduction for all (international) PhD students
Please upload proof of enrollment as a PhD student in the application form and state the name of your tutor on the application form (remarks field).
25% reduction on our course fees (maximum 3 EC points per academic year) for all NIHES alumni
Please state that you are a NIHES alumnus/alumna and the academic year you graduated (remarks field). Please note that the reduction on fees for alumni does not apply to the Erasmus Summer Programme.