The page contains links to the most recent version of courses that I’m currently teaching.
Many modern research projects collect data and use experimental designs that require advanced statistical methods beyond what is taught as part of the curriculum in introductory statistical courses. This course covers some of the more general statistical models based on ideas from Bayesian statistics. These methods suitable for analyzing complex data and experimental designs encountered in health research such as supervised and non-supervised machine learning methods, neural networks, support-vector machines, and network analysis.
The course will contain equal parts theory and applications and consists of four full days of teaching and computer lab exercises. It is the intention that the participants will have a good understanding of the statistical methods presented and are able to apply them in practice after having followed the course. This course is aimed at health researchers with previous knowledge of statistics and the computer language R who need of an overview about appropriate analytical methods and discussions with statisticians to be able to solve their problem.
Note that there are two courses entitled “Advanced Statistical Topics in Health Research”. They have no overlap and can be taken independently of each other.
Created by Claus Thorn Ekstrøm 2018