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Course description

This course provides statistical methods to study the association between (multiple) determinants and the occurrence of an outcome event. The course starts with an introduction to likelihood theory, using simple examples and a minimum of mathematics. Next, the most important regression models used in medical research are introduced. Topics are: maximum-likelihood methods, multiple linear and logistic regression, model validation and regression diagnostics, Poisson regression, and analysis of `event-history´ data, including an extensive discussion of the Cox proportional hazards regression model. Also, the basic principles of resampling methods (bootstrapping and permutation tests) and of longitudinal data analysis are taught.

This course can best be followed in the first half of the PhD track. It helps participants to identify the correct analyses for their research, carry out these analyses and interpret and report the results.

Learning objectives

At the end of the course you can identify the situations in which the aforementioned modelling techniques can be applied and the conditions that should be met to obtain reliable results using these techniques. You are also able to explain and interpret the results obtained with the techniques, and apply these results in practice (e.g., to answer a research question).

In particular, you will 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 common statistical packages (e.g. SPSS or 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)

Course program

The online course is a 9 weeks part-time course with a study load of 14 hrs/w. Web lectures, assignments and discussions are the learning methods that will be used. There are interim deadlines and the course ends with an exam.

Start: 6 September 2021

End: 5 November 2021

Course material

You need to have access to and working knowledge of the freeware statistical program R.

Group size

8 to 30 participants

Number of credits

4.5 EC

Course certificate

Participants will receive a certificate when they completed the practical exercises (self-study), attended at least 80% of the classes and passed the exam.

Course fee

We offer 5 places for free for PhD candidates registered with the Graduate School of Life Sciences via MyPhD. Be quick, these 5 places tend to be taken soon. Important: you can only use one of these places for 1 course organised by the Julius Center (Introduction to Epidemiology, Introduction to Statistics, Modern Methods in Data Analysis, Study Design in Etiologic Research).

More information and registration

For more information please send an e-mail to msc-epidemiology@umcutrecht.nl.

Registration is closed. Course fully booked.