Survival data, or more generally, time-to-event data (where the “event” can be death, disease, recovery, relapse or another outcome), is frequently encountered in epidemiologic studies. Censoring is a problem characteristic to most survival data, and requires special data analytic techniques.
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.
- 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
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- Survival Data and Analysis
- Checking the Cox Model
- Advanced Cox regression, more on censoring and truncation
- Competing risks and informative censoring
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- 35 days
- 9 hrs/week
Start dates & application deadlines
- Apply before
Enrollment deadline 3 Jan
DisciplinesHuman Medicine Health Management Health Sciences View 12 other Short Courses in Health Management in Netherlands
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We are not aware of any academic requirements for this programme.
We are not aware of any English requirements for this programme.
To enroll in this course, you need:
- A BSc degree
- At least one course in basic statistical methods, up to and including simple and multiple linear regression, such as: Classical Methods in Data Analysis, Introduction to Biostatistics for Researchers, or their equivalent.
- Note: R will be used during lectures and computer labs. Most techniques require the use of R (or another package, such as Stata or SAS). Those unfamiliar with the (free) statistical package R are strongly encouraged to practice with it before beginning the course.
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International870 EUR/fullTuition FeeBased on the tuition of 870 EUR for the full programme during 35 days.
EU/EEA870 EUR/fullTuition FeeBased on the tuition of 870 EUR for the full programme during 35 days.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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Apply and win up to €10000 to cover your tuition fees.