Prognostic Research
Master
Online
Description
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Type
Master
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Methodology
Online
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Duration
3 Weeks
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Online campus
Yes
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Delivery of study materials
Yes
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Support service
Yes
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Virtual classes
Yes
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.
About this course
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.
Reviews
Subjects
- Prognostic
- Interpretation
- Analysis
- Data analysis
- Data
- Assumptions
- Consequences
- Underlying
- Statistical
- Techniques
- Data sets
Course programme
- The principles of prognostic research and the interpretation of its results
- The issue of missing values and data analysis in prognostic research, including the underlying assumptions and their statistical consequences, and the evaluation of model performance
- The practical application of prognostic research and its clinical consequences
- • Modelling techniques for small data sets
- 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.
Prognostic Research