Survival and Event History Analysis

After completing the course the student is expected to:

Knowledge

• Distinguish methods for analysis of time-to-event data from other types of measurements.
• Understand the concepts of censoring and truncation.
• Explain central survival analysis concepts such as hazard, survival and cumulative incidence and their relationships.
• Describe and compare models for time-to-event data. Illustrate how the models can be applied to epidemiological or public health data.
• Understand and recognize common pitfalls specific to time-to-event data.

Skills

• Determine the proper statistical method to address a specific scientific question from a given time-to-event data set. This includes understanding the underlying assumptions of the method and identifying violations of these.
• Perform time-to-event analysis with modern techniques using the statistical software R. Assess the fit of the model.
• Interpret the results reported by statistical software. Communicate the results and conclusions of a time-to-event analysis in a clear and precise way.
• Write a statistical report with a well-defined problem statement, method and result presentations, discussion and conclusion.
• Critically read and review reports or articles addressing epidemiological and public health questions by time-to-event analysis.

Competencies

• Identify and conceptualize questions encountered in the professional life of a public health researcher that can be addressed by time-to-event studies.
• Independently design, carry out and communicate time-to-event studies.
• Give advice and take active part in collaborations where decisions are based on the statistical analysis of time-to-event data.