At the end of this course, the student:
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has insight in the principles of the likelihood theory and maximum likelihood methods;
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understands the principles of the following statistical analysis techniques:
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Logistic regression analysis;
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Poisson regression analysis;
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Analysis of event history data, including the Cox proportional hazard regression model;
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has insight in model validation and regression diagnostics;
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has insight in the basic principles of longitudinal data analysis;
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is able to apply the above mentioned techniques using common statistical packages (SPSS, R);
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knows in which situations these techniques can be applied and the conditions that should be met to obtain reliable results using these techniques;
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understands the results obtained with these techniques, and is able to apply these results in practice (e.g. in answering a study question).
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Period (from-till): This course is taught several times per year, during fulltime weekdays according to the following Schedule (Face-2-Face in Period A, Online in Period B):
| Education form |
Startdate |
Enddate |
Registration period |
| Face-2-Face |
08-01-2024 |
26-01-2024 |
BMS_P2_A |
| Online* |
04-09-2023 |
03-11-2023 |
BMS_P1_B |
| Online* |
25-03-2024 |
24-05-2024 |
BMS_P3_B |
*Online courses are only available for Epidemiology students following a full online programme.
Contact details: Educational Office Epidemiology
E-mail: msc-epidemiology@umcutrecht.nl
Registration:
Single courses — MSc Epidemiology (msc-epidemiology.nl)
Course coordinator
C.L.J.J. Kruitwagen, MSc
Julius Center, UMC Utrecht, Utrecht the Netherlands
Faculty
C.L.J.J. Kruitwagen, MSc
Julius Center, UMC Utrecht, Utrecht the Netherlands
J. van den Broek, PhD
UU, Faculty of Veterinary Medicine, Department of Farm Animal Health.
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, 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 longitudinal data analysis are taught.
Literature/study material used:
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Mandatory for students in own Master’s programme:
Epidemiology & Epidemiology Postgraduate
Optional for students in other GSLS Master’s programme: Yes
Prerequisite knowledge:
Introduction to Statistics
Classical Methods in Data Analysis
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