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). Associate Professor in the Department of Sports Science and Clinical Biomechanics and a senior researcher at the Nordic Institute of Chiropractic and Clinical Biomechanics.
Peter Kent. Associate Professor School of Physiotherapy and Exercise Science, Curtin University in Perth, Australia and Adjunct Professor at SDU.
Eleanor Boyle. Associate Professor in the Department of Sports Science and Clinical Biomechanics and an Assistant Professor in the Epidemiology division of Dalla Lana School of Public Health, University of Toronto.
Credits: 3 ECTS.