Quantcast
Channel: Ph.D. Network » Stata Press
Viewing all articles
Browse latest Browse all 2

Introduction to Survival Analysis

$
0
0

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Andrea Schäfer (University of Bremen)

Date:

30.09.2013, 14:00 – 17:30
01.10.2013, 14:00 – 17:30
02.10.2013, 14:00 – 17:30

Room: n.s.

Max. number of participants: 20

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:

The goal of this course is to give an introduction to the topic of survival (or time to event) analysis and describes selected methods used for modeling and evaluating survival data. General statistical concepts and methods discussed in this course include survival and hazard functions, Kaplan-Meier estimator and graph, Cox proportional hazards model and parametric models. Accordingly, we will explore the different types of censoring and truncation and, discover the properties of the survival and hazard function. You will learn the derivation and use of Kaplan-Meier non-parametric estimates and learn how to plot the KM and test for differences between groups. Further, we explore the motivation, strength and limits of Cox’s semi-parametric proportional hazard model and know how to fit the model. Finally we will recap the basis of parametric models. For our computer sessions we will be using a sample of the SOEP (Socio-economic Panel) data set. The course requires participants to use STATA to analyze survival analysis data.
In this course, you will learn about:

  • The goal, problem and strengths of survival analysis
  • Differences of survival analysis methods
  • Censoring and truncation (concepts and types)
  • The distribution of failure times (functions, rates and ratio, data layout, descriptive statistics)
  • Basics of non-parametric analysis (estimating Kaplan Meier estimator and comparing curves, graphing)
  • Basics of semi-parametric analysis (model definition and features, understanding and estimating Cox’s PH model)
  • Basics of parametric analysis (forms of distributions)

Literature

Cleves, Mario; William Gould, Roberto G. Gutierrez, and Yulia V. Marchenko (2010): An Introduction to Survival Analysis Using Stata, (3nd ed), Stata Press.

Kleinbaum, David G. and Klein, Mitchel (2005): Survival analysis: a self-learning text (2nd ed), Springer.

You have to register for the 7th International Research Workshop to participate in this course.


Viewing all articles
Browse latest Browse all 2

Latest Images

Trending Articles





Latest Images