Info
Schedule: Monday 16.15-17.45,
- Lectures: J. Liivi 2 - 405
- Computer Labs: J. Liivi 2 - 004
Moodle page of the course: https://moodle.ut.ee/course/view.php?id=3410
Amount of credits: 3 ECTS (EAP)
Course code: MTMS.02.037
Lecturer: Meelis Käärik (associate professor, Institute of Mathematical Statistics, University of Tartu)
Target group: master students of actuarial and financial engineering / mathematics and statistics programmes
Recommended prerequisites:
- MTMS.01.001 Mathematical Statistics I (6 ECTS)
- MTMS.01.011 Generalized Linear Models (6 ECTS)
Brief description: The subject will cover general theory for survival models, including:
- survival function, its empirical estimates (Kaplan-Meier, Fleming-Harrington) and construction of confidence intervals
- fitting most common parametric distributions to survival data;
- Cox proportional hazards model, accelerated failure time model;
- multistate models, introduction to continuous-time Markov chains, Cox-Markov model.
Objectives of the course: The aim of the course is to provide a systematic overview of survival models used in life insurance.
Learning outcomes: By the end of the course a participant
- understands the concept of main functions used in survival analysis (survival function, hazard function, cumulative hazard, etc);
- knows most important survival models;
- can describe systems with several states in terms of Markov chains and estimate its transition probabilities.
Final assessment: non-differentiated (pass, fail)
Requirements to be met for final assessment: At least 60% of home assignments done.
Recommended study materials:
- Tableman, M. & Kim, J.S. (2003). Survival Analysis Using S - Analysis of Time-To-Event Data. Chapman & Hall / CRC.
- Meira-Machado, L., de Una-Alvarez, J., Cardarso-Suarez, C. & Andersen, P.K. (2009). Multi-state models for the analysis of time to event data. Statistical methods in medical research, 18(2), 195--222.
- Hougaard, P. (2012). Analysis of multivariate survival data. Springer.
Additional information: Meelis Käärik (meelis.kaarik@ut.ee)