Survival Analysis for Clinicians [EWP24]
Online modules, class days: Mon 01/03, Thu 04/03, Mon 08/03, Thu 11/03, Mon 15/03, Thu 18/03. Assignment deadline 01/04.
Prof. Dimitris Rizopoulos, PhD
Erasmus MC, Rotterdam NL
Knowledge of statistics and regression models.
Detailed information about this course:
This course will not be offered in 2021.
Survival analysis is the study of the distribution of life times, i.e. the times from an initiating event (birth, diagnosis, start of treatment) to some terminal event (relapse, death). Survival analysis is most prominently (but not only) used in the biomedical sciences. A special feature of survival data is that it takes time to observe the event of interest. A result of this seemingly innocent observation is that for a number of subjects the event is not observed, but instead it is known that it has not taken place yet. This phenomenon is called censoring and it requires special statistical methods. During the course different types of censored and truncated data will be introduced and techniques for estimating the survival function by employing both parametric and non-parametric methods will be illustrated. Also techniques for testing equality of survival functions (the log-rank test and alternatives) are discussed. Finally regression models for survival analysis, based on the hazard function (most notably the Cox proportional hazards model), will be studied in great detail. Special aspects such as time-dependent covariates and stratification will be introduced. Techniques to be used to assess the validity of the proportional hazards regression model will be discussed. The last part of the course touches on models for multivariate survival analysis, including competing risks and multi-state models and frailty models. Finally, aspects of the planning of clinical trials with lifetime data will be discussed.
All aspects of the course will be illustrated with real data examples and will be practiced. In order to cater to a larger range of participants, this Survival Analysis course has had an update! Starting in 2020, the course has a blended design, which means it includes both online modules and in-class meetings. The first meeting lasts 1 hour, the following meetings last 2 hours. The course is assessed using an assignment.
Survival Analysis (EWP24) is equivalent to the Survival Analysis course (ESP28) in the Erasmus Summer Programme and the part about survival analysis in Biostatistical Methods II: classical regression models (EP03).
After completing the course, the student should:Understand the concept of censoring and its implications for statistical analysis;
- Be familiar with the most important techniques in survival analysis, such as the Kaplan-Meier estimate, the log-rank test and proportional hazards regression;
- Understand the underlying assumptions and limitations of these techniques;
- Be able to perform statistical analysis of time-to-event data and interpret the results.
Clinicians who are involved in clinical research with time-to-event data or want to learn the concepts and techniques for the analysis of such data.
Reduction on fees
PLEASE NOTE THIS DOES NOT APPLY TO THE RESEARCH MASTERS (120 EC points)
50% reduction on our fees for participating institutes of NIHES
This 50% reduction is offered to participants formally appointed at the departments or sections participating in NIHES.
University Medical Center Rotterdam/Erasmus University Rotterdam:
- Department of Epidemiology
- Department of Public Health
- Department of Psychiatry, Section of Medical Psychology and Psychotherapy
- Department of Child and Adolescent Psychiatry/Psychology
- Department of Medical Informatics
- Department of General Practice
- Erasmus School of Health Policy & Management
- Generation R
50% reduction on our fees for NIHES affiliated partners
This 50% reduction is offered to participants formally appointed at the following NIHES affiliated partners:
University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:
- General Paediatrics
- Plastic and Reconstructive Surgery
- Rehabilitation Medicine
UMIT, Department of Public Health, Health Services Research and Health Technology Assessment.
25% reduction on our fees for Erasmus MC employees
For participants formally appointed at all departments of Erasmus MC (except the departments mentioned above).
25% reduction for all (international) PhD students
Please upload proof of enrollment as a PhD student in the application form and state the name of your tutor on the application form (remarks field).
25% reduction on our course fees (maximum 3 EC points per academic year) for all NIHES alumni
Please state that you are a NIHES alumnus/alumna and the academic year you graduated (remarks field). Please note that the reduction on fees for alumni does not apply to the Erasmus Summer Programme.