Introduction to Applied Survival Analysis and Time-to-Events Models

Name of the PhD course
Introduction to Applied Survival Analysis and Time-to-Events Models (2021)

Dates/Time
Week 45, 2021 - please see detailed course schedule

Venue
Online

Coordinator
Morten Hesse

Teacher(s)
Morten Hesse, Abdu Kedir Seid  

Language
English

ECTS points
5

Course description
Time-to-events models are a family of approaches to statistical analysis that are useful for estimating the occurrence of events during observation of a group of units, such as natural persons. In medicine, an example could be the time from treatment begins until a pre-specified level of improvement is observed. In social science, an example could be the time from a person graduates from university until he or she obtains her first fulltime job.

In such situations, unless all subjects experience the event, standard models will produce misleading results. A family of models has been developed to analyze such data, including the log-rank test, the Wilcoxon test, Cox regression, Weibull regression, and exponential regression. However, these models share a strong underlying and appealing intuitive logic that can easily be shown using graphical presentations. Learning these models will allow the researcher to analyze data in ways that can increase the statistical power to observe meaningful effects without collecting additional data

Requirements for participation
The student must have a master’s degree that involves introductory statistics, and be familiar with basic concepts concerning bivariate and multivariate modelling at the conceptual level. Familiarity with Stata will be an advantage.

Learning objectives
• Understanding situations in which survival models apply
• Setting up data for survival analysis, including data that are not obviously organized for survival models
• Inspecting survival graphs for signs of data anomalies and errors
• Running survival models • Checking for violation of the proportional hazards assumption
• Describing the outcomes of a survival analysis in the context of a scientific paper

Competences
• Understand survival models in the scientific literature
• Understand and explain when survival analyses methods are relevant
• Analyze and report time to events models in practical settings within the candidate’s field
• Engage in collaborative work with other researchers in the context of survival analysis

Evaluation form
The course participants will be evaluated by submitting a paper presenting data from the participants’ own data or simulated data

Target group
PhD students

Applying for the course
Please complete online application form

Deadline for applying
Wednesday 13 October 2021

Maximal number of participants
25