Study cover for Survival Analysis
Certificate Online

Survival Analysis

Utrecht University

35 days
Duration
870 EUR/full
870 EUR/full
Unknown
Tuition fee
Unknown
Apply date
Unknown
Start date

About

This online Survival Analysis course from Utrecht University will give an introduction to survival analysis and cover many of the types of survival data and analysis techniques regularly encountered in epidemiologic research. 

Visit the official programme website for more information

Overview

Survival data, or more generally, time-to-event data (where the “event” can be death,  disease, recovery, relapse or another outcome), is frequently encountered in epidemiologic studies. Censoring is a problem characteristic to most survival data, and requires special data analytic techniques.

The necessary statistical theory will be presented, but the course will focus on practical examples, with an emphasis on matching data analysis to the research question at hand. Lab sessions will give students the opportunity to apply the theory to real datasets using the free statistical software R.

Learning objectives

By the end of the Survival Analysis course from Utrecht University , you should be able to:

  • recognize or describe the type of problem addressed by a survival analysis
  • define and recognize censored data
  • define and interpret a survivor function and a hazard function, and describe their relation
  • recognize the computer printout from a Cox proportional hazards model, a stratified Cox model, and a Cox model extended for time-dependent covariates
  • state the meaning of the proportional hazards assumption and know how to check this assumption
  • recognize which survival analysis technique is appropriate for a given research question and dataset
  • interpret the computer printout for survival models, including hazard ratios, hypothesis testing, and confidence intervals

Programme Structure

Courses include:

  • Survival Data and Analysis
  • Checking the Cox Model
  • Advanced Cox regression, more on censoring and truncation
  • Competing risks and informative censoring

Key information

Duration

  • Part-time
    • 35 days
    • 9 hrs/week

Start dates & application deadlines

More details

Enrollment deadline 3 Jan

Language

English

Credits

1 ECTS

1.5 EC

Delivered

Online

Academic requirements

We are not aware of any academic requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

To enroll in this course, you need:

  • A BSc degree
  • At least one course in basic statistical methods, up to and including simple and multiple linear regression, such as: Classical Methods in Data Analysis, Introduction to Biostatistics for Researchers, or their equivalent.
  • Note: R will be used during lectures and computer labs. Most techniques require the use of R (or another package, such as Stata or SAS). Those unfamiliar with the (free) statistical package R are strongly encouraged to practice with it before beginning the course.

Tuition Fee

To alway see correct tuition fees
  • International

    870 EUR/full
    Tuition Fee
    Based on the tuition of 870 EUR for the full programme during 35 days.
  • EU/EEA

    870 EUR/full
    Tuition Fee
    Based on the tuition of 870 EUR for the full programme during 35 days.

Funding

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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Check the official programme website for potential updates.

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