Survival Analysis
Team members: Yehenew Getachew (Jimma University, Ethiopia), Befekadu Gashaw (Hawassa University, Ethiopia), Fentaw Abegaz (Addis Ababa University, Ethiopia), Paul Janssen (UHasselt, Belgium), Ingrid Van Keilegom (Universit\'e Catholique de Louvain, Belgium), Luc Duchateau (Universiteit Gent, Belgium)
Topic: Survival analysis techniques are used in a variety of disciplines including human and veterinary medicine, epidemiology, engineering, biology and economy. The specific feature that makes survival analysis different from classical statistical analysis is data censoring. Typically, the survival time is unknown for some of the subjects; the only information available being that the subject has survived up to a certain time. Thereafter, the subject is no longer followed up.
In this course, basic techniques for handling survival data are studied. In the first part, it is assumed that event times are independent of each other. Both parametric and semiparametric models are studied. In the second part, these techniques are extended to cope with clustered survival data, where event times within a cluster are correlated.History: This course and its sylabus is based on the coursenotes of Ingrid Van Keilegom (Part I) and Luc Duchateau (Part II), that were developed in the context of the Survival Analysis course taught at the Masters of Biostatistics Of Hasselt University, Belgium
Sylabus
| File name | File Size |
| ./sylabus/survivalcourseNSS.pdf | 2132836 |
Slides
Datasets
| File name | File Size |
| ./datasets/insemtvc.dat | 12013934 |
| ./datasets/Schizophrenia.csv | 6454 |
| ./datasets/ARTCohort.csv | 2776 |
| ./datasets/paget.csv | 807 |
| ./datasets/StandardizedActuarialTables.csv | 4393 |