Prognosis is a key concept in patient care. However, although prognostic research is becoming increasingly important in clinical medicine, the actual methodology behind it is relatively underdeveloped.
The purpose of this course is to redress this imbalance. We will therefore discuss the principles and methods of non-experimental prognostic research, together with the practice of prognostic research in a clinical setting. The emphasis will be on learning about the design and statistical analysis of prognostic studies, the construction and estimation of prediction rules, the various approaches to validation, and the generalization of research results. You will also learn how to address the challenges of dealing with small data sets.
By the end of the course, you should be able to:
- Understand the key characteristics and different types of prognostic research
- Set out the various steps involved in performing prognostic research
In particular, you should be able to:
- Demonstrate an insight into different types of missing values
- Understand different ways of handling missing values in prognostic research
- Propose different modelling approaches for prognostic research, including non-linear models
- Make a prognostic model
- Show how to derive a prognostic score, and choose adequate score cut-offs
- Know how to apply modelling techniques to deal with over-fitting in small data sets.