Estimating treatment effects using parametric models as counter-factual evidence

Estimating treatment effects using parametric models as counter-factual evidence

Abstract Randomisation controlled trial are the gold standard for causal inference, however the rapidly increasing development of new treatments and the movement towards personalised medicine mean there is a need to measure efficacy outside of the costly and time-consuming RCT. Here we propose a met...

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Bibliographic Details
Main Authors: Richard Jackson, Philip Johnson, Sarah Berhane, Ruwanthi Kolamunnage-Dona, David Hughes, Susanna Dodd, John Neoptolemos, Daniel Palmer, Trevor Cox
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Medical Research Methodology
Subjects:
Causal Inference
Synthetic Controls
Efficacy
Parametric Models
Counter-Factual Evidence
Online Access:https://doi.org/10.1186/s12874-025-02540-2
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