Course description

Course Contents

Many medical informatics are working with large and complex epidemiological databases and are trying to reconstruct knowledge from such sources. Almost always this requires statistical data-analyses which will be complicated through multi-dimensionality, non-linearity and confounding factors. In this course some modern statistical techniques will be discussed, studied and applied. Aim is that students are capable of analyzing complex data with minimal guidance: they will recognize how data were sampled and which consequences the sampling design has for the data-analysis; they will realize which assumptions are made with specific statistical techniques and how those can be checked; and students are aware of the instability of estimated statistical models and how such instability can be quantified.

 

Course lay-out

In this course we will discuss and study four different subjects (maximum likelihood theory, modern regression, multilevel analysis and bayesian models): one subject per week. Each subject will be introduced in plenary sessions and studied further by selfstudy assignments (including data-analysis). At the end of the week the results of the assignments are discussed and elaborated upon in a plenary session.

 

Educational goals

• Recognizing, using and manipulating the mathematical and statistical fundamentals of modern data-analysis techniques.
• Applying these techniques critically with R and other computer programs to specific datasets.

 

Involved departments

• Clinical Epidemiology and Bio-Statistics

 

Evaluation

Evaluation of the course and assignments

Statistics will always be one of my weaknesses; however thanks to the good explanation of the coordinator of all the topics, it was a lot easier to understand the matter. It was useful to discuss some advanced data-analysis techniques, because research is more than SPSS packages. We had to learn to work with R; R is a statistical package and can be extended by adding plugins called packages. With R you can do some advanced data-analyses which are not possible to do with SPSS. This course would be particular useful when we are doing our Scientific Research Project. I am glad that this course was given by the coordinator who could explain everything really good. The assignments were very good and it was useful to discuss the results of the assignments, this way you will learn a lot more than when you are just following lectures. During this course I have improved my statistical skills and have a lot more knowledge about advanced data-analyses.