The course was last conducted in 2019.
Course description
The statistical computing environment R is today one of the major statistical programming languages. Its versatility allows treating all major statistical analysis tasks and it is one of the leading environments for which algorithms of new approaches are published.
The Advanced usage of "R" in Biomedicine gives an overview of advanced tools in R to enable students to tackle complex analysis tasks.
The courses goal is to give you a good working knowledge to implement analyses methods from four chosen topics.
The course assumes that a student masters the basics concepts of R such as dealing with its data-structures, reading and writing data and simple statistical and data manipulative calculations.
The course runs over two successive days. It will have a structure where a lecture introducing to the main methodological aspects is followed by exercises for implementing the modelling ideas with R.
The following four themes will be covered
- Survival analysis From simple modelling as Kaplan-Meier survival curves and Cox-models to analysis of competing risk, time varying covariates and effects
- Analysis of correlated measurements: repeated measurements, longitudinal data, Structural equation modelling
- Advanced graphics (trellis graphics providing insight for multivariate dependencies in your data (ggplot2)
- Development and evaluation of predictive models Describe and understand the predictive quality of a regression model especially in the few observations but many potential predictors situation
Fundamental requirement for participating in the course
You should have a working knowledge of R as for example provided by our course ‘Basic Introduction to R’ .
Expected learning outcomes
Participants will acquire working knowledge to implement advanced statstistifal analysis method with the software R and
Course fee
The course is free of charge for PhD students enrolled in Universities that have joined the "Open market agreement".
For other participants there is a course fee of DKK 3823,-