ONLINE - Survival analysis (Advanced Biostatistics) 2021

ONLINE - Survival analysis (Advanced Biostatistics) 2021
Doelgroep:
 
Organisatie:
LUMC - Boerhaave Nascholing
Locatie:
 
Inlichtingen:
 
Accreditatie:
 
Due to the current times it has been decided that this course will be organised online this spring. Therefore the set-up of the course is different than usual, with limited online lectures and mainly self-study (see program)

Do you prefer live lectures and interaction? Save the date and wait for the physical course which will take place from 8-12 November 2021.

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Introduction
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 laptop for following this course. SPSS, R or Stata software is required, for the practical assignments.  

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 question hours 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 and PhD students in the bio-medical sciences

Organizing committee

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