Survival analysis (Advanced Biostatistics) 2022

IMPORTANT NOTICE: Due to the current situation with COVID, the LUMC policy with respect to internal events and activities has been updated. This course will no longer be provided at the LUMC, but will be set-up ONLINE. Registered students will receive updated information and log-in instructions in due course.

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 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, stratification, time and prediction will be introduced. Techniques to be used to assess the validity of the hazard regression model will be discussed. Alternative to Cox model will be illustrated and predictive models will be introduced. The last part of the course focus on more advanced models like competing risks and multi-states.

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. The course ends with a discussion about sample size calculations.

Practicals
Participants are requested to use their own workspace / laptop for following this course. SPSS or R software is required, for the practical assignments. 

This course is for beginners and does not require any pre-knowledge about survival data. Advanced survival models will be discussed on the last day of the course.

The course puts a lot on emphasis on the interpretation of the analysis, on the well-known mistakes often occurring while working with survival data and provide inputs on how to report results in scientific publications. It is not the aim of the course to discuss about data preparation, data cleaning for the statistical analysis. 

SPSS and R codes to solve the afternoon exercise will be provided at the end of each day. 

Requirements
Basic knowledge of statistics (e.g. the Boerhaave course 'Basic methods and reasoning in Biostatistics') and of regression models (e.g. the Boerhaave course 'Regression Analysis')

Teaching environment
Morning lectures, video’s, self-study assignments and daily plenary discussions with the teacher.

Proof of participation / exam / ECTS
In order to obtain a proof of participation, all lectures should be attended. A practical assignment/exam must be submitted at the end of the course for those who need ECTS. 
This course is 1,5 ECTS.

Course material
All study materials are supplied electronically only, and will be made available about 1 week prior to the course. 

Target group
Master-, PhD students, postdocs and researchers in the bio-medical sciences.

Organizing committee

• Prof. dr. Marta Fiocco, Mathematical Institute Leiden University and Biomedical Data Science Medical Statistical Section (m.fiocco@math.leidenuniv.nl)

* Limited places available. In order to validate your student registration, you must register with your student e-mail address and submit your student number on the registration form. In addition, a scan of your student pass will have to be submitted to boerhaavenacholing@lumc.nl. Please note that a € 45,- cancellation fee will be charged to students who do not attend the course (no show), or cancel their registration.