Event history analysis

Subject description

  • Censoring
  • Survival curve, hazard function
  • Exponent and Weibull distribution
  • Nonparametric estimation of survival curve
  • Comparison of survival curves
  • Parametric regression models in survival analysis
  • Model of proportional hazards
  • Model definition and ssumptions, parameter interpretation
  • Parameter estimation, partial likelihood method
  • Stratification
  • Time dependent variables
  • Estimation of survival probability
  • Test statistics
  • Residuals
  • Goodness of fit
  • Model predictive value
  • Competing risks
  • Multistate models

The subject is taught in programs

Objectives and competences

Event history analysis (survival analysis) is a field of statistics that deals with times between the events. The times are often censored which means that the event does not happen (no death, no job loss, machine failure… ). That and the observed time variying factors require specific methods for the analysis.

 

The student gets aquainted to the methods of the survival analysis that cover most of the needs in practice (in biostatistics as well as humanities and technics).

Teaching and learning methods

Lectures, labs, homeworks, project

Part of the pedagogical process will be carried out with the help of ICT technologies and the opportunities they offer.

Expected study results

By the end of the course students should be able to  recognise the problems that censoring brings and understand why the more basic stastistical tecniques are insufficient with such data. They should be able to define the goals of their study, choose the appopriate method,  use it and  understand what  information it can and cannot give.

Basic sources and literature

  • Hosmer DW, Lemeshow S (1999): Applied Survival Analysis: Regression modelling of time to event data. New York: Wiley
  • Klein JP, Moeschberger ML (1997): Survival Analysis: Techniques for Censored and Truncated Data. New York: Springer.
  • Collett D (2003): Modelling Survival Data in Medical Research. Champan & Hall

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E:  dekanat@fe.uni-lj.si T:  01 4768 411