A scoping review of causal methods enabling predictions under hypothetical interventions

A scoping review of causal methods enabling predictions under hypothetical interventions

Abstract Background The methods with which prediction models are usually developed mean that neither the parameters nor the predictions should be interpreted causally. For many applications, this is perfectly acceptable. However, when prediction models are used to support decision making, there is o...

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Bibliographic Details
Main Authors: Lijing Lin, Matthew Sperrin, David A. Jenkins, Glen P. Martin, Niels Peek
Format: Article
Language:English
Published: BMC 2021-02-01
Series:Diagnostic and Prognostic Research
Subjects:
Clinical prediction models
Statistical modeling
Causal inference
Counterfactual prediction
Online Access:https://doi.org/10.1186/s41512-021-00092-9

Internet

https://doi.org/10.1186/s41512-021-00092-9

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