Statistical analysis of survival data
Graduate School of Health and Medical Sciences at University of Copenhagen
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH.
Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.
The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee
Learning objectives
After completing the course the student is expected to:
• Distinguish methods for analysis of time-to-event data from other types of measurements
• Understand the concepts of censoring and truncation.
• Explain central survival analysis concepts such as hazard, survival and cumulative incidence and their relationships.
• Describe and compare models for time-to-event data. Illustrate how the models can be applied to epidemiological or health data.
• Understand and recognize common pitfalls specific to time-to-event data.
• Determine the proper statistical method to address a specific scientific question from a given time-to-event data set. This includes understanding the underlying assumptions of the method and identifying violations of these.
• Perform time-to-event analysis with using the statistical software R. Assess the fit of the model.
• Interpret the results reported by statistical software. Communicate the results and conclusions of a time-to-event analysis in a clear and precise way.
• Take active part in collaborations where decisions are based on the statistical analysis of time-to-event data.
Content
The course introduces statistical concepts and methods for analyzing time-to-event (survival) data obtained from following individuals until a particular event occurs, or they are lost to follow-up. We will illustrate the use of modern tools for time-to-event analysis and discuss interpretation and communication of results. The course provides practical experience with health science data using the statistical software R through computer labs and home assignments.
Prerequisites
The course is tailored for Ph.D.-students in health sciences who already have taken the Ph.D.-course “Basic Statistics for Health Researchers” or have a similar knowledge about statistics, and who wish to have more knowledge and deeper understanding of statistical methods for censored time-to-event data. In terms of mathematical theory, basic exposure to calculus is expected.
If you are not familiar with R programming, we recommend that you complete the free access e-learning course at http://r.sund.ku.dk/ before starting on this course.
Participants
PhD-students. In case of vacant seats also other medical researchers. Max. 20 participants.
Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:
All graduate programmes
Language
Danish or English.
Form
The course consists of lectures and computer sessions (bring your own laptop) illustrating the implementation and interpretation, as well as self-study preparation and weekly mandatory home assignments (quizzes) in Absalon (UCPH's teaching platform) supported by discussion threads. The exercises are based on the statistical software R. The course requires active homework and preparation, and will be passed by answering at least 80% of the online home assignments and satisfactorily responding to a take-home exam. The course assumes prior knowledge about basic statistics on the level achieved in the PhD course “Basic Statistics for Health Researchers'”.
Course director
Professor Thomas Scheike, Section of Biostatistics.
Teachers
Members of the staff at Section of Biostatistics.
Dates
Wednesdays 3, 10, 17, 24 September, 1, 8, 22 October 2025, all days 8-12. Online exercises between these dates. Take-home exam hand in deadline 5 November 2025.
Course location
CSS
Registration
Please register before 4 August 2025
Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrollment.
Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.