During this online medical course, offered by the MSc Epidemiology program of the UMC Utrecht and Utrecht University, you will learn to use statistical methods to study the association between (multiple) determinants and the occurrence of an outcome event.
The course will begin with an introduction to likelihood theory, using simple examples and a minimum of mathematics. You will then move to learning about the most important regression models used in medical research. These include logistic regression, Poisson regression, analysis of event history data, and the Cox proportional hazards regression model. In addition, you will become familiar with model validation and regression diagnostics, as well as with the basic principles of re-sampling methods and longitudinal data analysis.
The course is aimed at professionals who are interested in to learn more about statistics for medical research. However, a medical education is not a requirement to successfully participate in this course.
By the end of the course, you should be able to:
• Explain the principles of the likelihood theory and maximum likelihood methods
• Explain the principles of the following statistical analysis techniques: Logistic regression analysis, Poisson regression analysis, Analysis of event history data, including the Cox proportional hazards regression model
• Explain model validation and regression diagnostics
• Describe the basic principles of longitudinal data analysis
• Apply the above-mentioned techniques using statistical package R
• Name the situations in which these techniques can be applied and the conditions that should be met to obtain reliable results using these techniques
• Explain and interpret the results obtained with these techniques, and apply these results in practice (e.g. to answer a research question)
• Linear models
• Likelihood and logistic regression
• Poisson models and generalized linear models
• Survival analysis
• Resampling methods
• Longitudinal data analysis
This course includes an exam that primarily consists of essay questions, which is the only part of the course that is not online.
Exam edition September 2023
The exam will take place on November 3th, 2023 from 14:15 – 17:15 CET. The re-examination will take place on December 22th, 2023 from 14:15 – 17:15 CET. Note: these times might be subject to change. The exact time and place will be announced as soon as possible in the learning environment and any changes announced there will overrule the information here.
Exam edition March 2024
The exam will take place on May 24th, 2024 from 14:15 – 17:15 CET. The re-examination will take place on July 12th, 2024 from 14:15 – 17:15 CET. Note: these times might be subject to change. The exact time and place will be announced as soon as possible in the learning environment and any changes announced there will overrule the information here.
The exams are, by default, online using online proctoring. If you wish to take the exam on-site in Utrecht, the Netherlands, this is possible as well.
The exam is not compulsory. However, if you want to receive the Course Certificate and the credits, it is obligatory to take the exam. You are allowed to redo the exam once.
It might be that, due to a force majeure situation, you cannot be present during the first exam moment.
• MSc Epidemiology Postgraduate students must then, preferably prior to the first exam option, ask the academic counsellor for permission to be absent. Please note that the academic counsellor can ask for some form of proof of your absence (e.g. in case of illness) to establish if you are applicable for authorized absence. Jaco de Fockert-Koefoed, MSc is the academic counsellor you need to turn to through email@example.com.
• All other participants should contact the MSc Epidemiology Office instead, through MSc-Epidemiology@umcutrecht.nl.
In short, as of now, it is no longer possible to skip the first exam option and -automatically- enroll in the second (re-sit) exam. Unauthorized absence during the first exam period results in no longer being able to finish the course that college year.
To enroll in this course, you need:
• A BSc degree
• Access to the program R
• Sufficient understanding of statistics and data analysis. Elevate courses offering this knowledge include Introduction to Statistics and Classical Methods in Data Analysis
• Sufficient proficiency in English reading and writing