Survival Analysis (online)

This online medical course will give an introduction to survival analysis and cover many of the types of survival data and analysis techniques regularly encountered in epidemiologic research. The necessary statistical theory will be presented, but the course will focus on practical examples, with an emphasis on matching data analysis to the research question at hand. Lab sessions will give students the opportunity to apply the theory to real datasets using the free statistical software R.

By the end of the course, you should be able to:

• recognize or describe the type of problem addressed by a survival analysis
• define and recognize censored data
• define and interpret a survivor function and a hazard function, and describe their relation
• recognize the computer printout from a Cox proportional hazards model, a stratified Cox model, and a Cox model extended for time-dependent covariates
• state the meaning of the proportional hazards assumption and know how to check this assumption
• recognize which survival analysis technique is appropriate for a given research question and dataset
• interpret the computer printout for survival models, including hazard ratios, hypothesis testing, and confidence intervals

Our courses are aimed at clinical researchers, nurses, general practitioners, and other health professionals who want to improve their skills in epidemiology, statistics and (clinical) research.

5 weeks - 9 hours per week

Please note, even though you can manage your own time our courses are not intended as individual education. By learning together you will gain depth in your learning process, which is very important. Therefore flexibility from students, a positive attitude towards teachers and peers and the willingness to learn together and help each other is invaluable to our courses