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 analyzing 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.
Teaching is a mixture of online lectures with room for questions and discussions, participants doing critical appraisals of prognostic papers, and exercises (demonstrated in STATA) to illustrate practical implications of statistical methods with a focus on interpretation of the analyses. Model data will be provided.
Readings of course materials, appraisal of papers and exercises are performed individually and discussed in online sessions.
Dates: 14/9, 16/9, 17/9, 21/9, 23/9, 24/9, 28/9, 30/9, 1/10, 5/10, 7/10, 8/10.
Lectures are scheduled 9-11 am
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 and PhD students enrolled in other Universities that have joined the "Open market agreement".
For other participants there is a course fee of DKK 5109,98,-
Credits: 2,2 ECTS.
Please note: This is an online course. You will need Zoom to access.