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[ 951STMOSANK14 ] KV Survival Analysis
Versionsauswahl
Es ist eine neuere Version 2025W dieser LV im Curriculum Master's programme Statistics and Data Science 2025W vorhanden.
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