Admission requirements
Prerequisites are introduction to probability theory and statistics (first and second year bachelor courses).
Description
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). This type of data 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. As a result 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 data will be introduced and techniques for estimating the survival function by employing parametric and non-parametric methods will be illustrated. Multiplicative hazards regression models, testing and inference techniques will be studied in great details. Special aspects as time-dependent covariates effects and stratification will be introduced. Techniques to be used to assess the validity of the hazard regression model will be discussed. The last part of the course focus on more advanced models: frailty, competing risks and multi-states models.
Frailty models are employed in survival analysis to account for unobserved heterogeneity in a population. These models are used to model the dependence among individuals in a cluster, such as families or hospitals, where subjects may be more similar to each other than to individuals in other clusters. A random effect is incorporated in a frailty model (the frailty term) which acts multiplicatively on the hazard.
A competing risks model is concerned with failure time data where each subject may experience one of the K different type of terminal events. Multi-states are employed when some intermediate events may occur before the final event of interest and one is interested in the effects of the occurrence of those intermediate events on the final events. Also for these more complex models estimation and prediction techniques will be discussed.
Course Objectives
At the end of this course, the student will be familiar with different types of censoring and truncation mechanism; will be able to write down the likelihood for different types of censored and truncated data and can maximize it for given parametric models. The student will be able to: estimate the survival in a parametric and non-parametric setting, estimate a Cox model, test its assumptions, interpret a hazard ratio, and derive model-based survival curves; fit frailty, competing risks and multi-state models and interpret the results from the analysis.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of instruction
Weekly lectures, and exercise classes
Assessment method
The final grade consists of a group presentation based on an article provided during the course (20%, no retake) and a written (retake) exam (80%).
Reading list
Odd O. Aalen • Ørnulf Borgan • Håkon K. Gjessing: Survival and Event History Analysis. A Process Point of View. Springer 2008
Slides and relevant material will be distributed to students during the course.
Registration
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
Note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.
Contact
By email: m.fiocco[at]math.leidenuniv.nl
Remarks
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.