An introduction to risk prediction and prognostic models
This talk provides a gentle introduction to risk prediction and prognostic models for healthcare research. They are introduced in the context of the PROGRESS framework, with examples given of their role, impact, and statistical basis. Phases of prediction model research are outlined, and current problems and limitations discussed. Signposts are then provided for better practice, including key articles and textbooks, training courses and our new website (www.prognosisresearch.com).
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thanks for share, great presentation!
Very helpful information
Wonderful presentation Sir. thanks for sharing!!
Why is causation not important in prediction modelling? Wouldn't the inclusion of potentially spurious factors be problematic when trying to apply the model in other samples?
@jekamito
Жыл бұрын
that is why you need external validation for your models. To determine the causality of a factor, you need to know the causal model, which we do not many times. Check Miguel Hernan's lectures on the topic.
@Marteenez_
Жыл бұрын
@@jekamito Isn't that just implicitly saying we do need to know causal factors, whether they are obtained from external validation or causal modelling.
thanks for share, great presentation!