Applied Prognostic Research – How to make sense of longitudinal health data

Prognostic health research studies relationships between patient characteristics and outcomes. There is much confusion in prognostic research because studies of associations, prediction models and causation are often mixed up. They do not have to be, as they are conceptually and methodologically distinct.

Aim: This course provides a theoretical framework for the fundamentals of understanding, conducting and analysing prognostic studies. It addresses the investigation of prognostic factors and prediction models, and highlights differences between studying causality and prediction.

The course is relevant to PhD students and researchers who work with prediction or prognostic factors and would like to gain a better understanding of fundamental concepts and methods applied in prognostic studies.

We will work with critical appraisal of papers on prognostic factors from different fields of health research and use exercises in STATA to illustrate practical implications of statistical methods with a focus on interpretation of the analyses. Model data will be provided for the workshops.

Lecturers: Alice Kongsted (course leader). Professor in the Department of Sports Science and Clinical Biomechanics, SDU

Peter Kent. Associate Professor in the School of Physiotherapy and Exercise Science, Curtin University, Perth, Australia

Eleanor Boyle. Associate Professor in in the Department of Sports Science and Clinical Biomechanics, SDU

Course fee: 
The course is free of charge for PhD students enrolled at the Faculty of Health Sciences at SDU. The course fee for PhD students enrolled in other Universities that have joined the "Open market agreement" is 
DKK 990,-.
For other participants there is a course fee of DKK 5955,48,-

Credits: 2,8 ECTS.                         


To give you the best possible experience, this site uses cookies Read more about cookies

Accept cookies