Studienhandbuch | KV Survival Analysis

Inhalt

Workload	Education level	Study areas	Responsible person	Hours per week	Coordinating university
4 ECTS	M2 - Master's programme 2. year	Statistics	Helga Wagner	2 hpw	Johannes Kepler University Linz

Detailed information
Original study plan	Master's programme Statistics 2015W
Objectives	Students are familiar with the basic concepts of survival analysis and are able to analyse survival data using statistical software, e.g. R
Subject	Basic concepts (censoring, truncation, survial function, hazard rate) Estimation of survival functions: Life tables, Kaplan Meier estimator Comparing survival function: Log-Rank test, Wilcoxon test, stratified tests Accelarated failure time model: specification, parametric survival distributions, estimation, hypothesis testing, evaluating model fit Proportional hazards model: specification of the Cox model, estimation of regression coefficients and survival function, model checks, stratified Cox model
Criteria for evaluation	Exam Project report
Methods	Lecture Computer Lab
Language	English
Study material	Broström G. (2012). Event History Analysis, Taylor & Francis Hosmer D. W. and Lemeshow S. (2003). Applied Survival Analysis, Wiley Klein J. P. and Moeschberger M. L. (1997). Survival Analysis, Springer
Changing subject?	No
Corresponding lecture	in collaboration with 951STCOCSTK14: KV Computational Statistics (4 ECTS) equivalent to 4MSCVDPR: PR Computerintensive Verfahren in der Datenanalyse (6 ECTS)

On-site course
Maximum number of participants	40
Assignment procedure	Assignment according to priority