Incorporating spontaneous reporting system data to aid causal inference in longitudinal healthcare data

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Incorporating spontaneous reporting system data to aid causal inference in longitudinal healthcare data

Inferring causality using longitudinal observational databases is challenging due to the passive way the data are collected. The majority of associations found within longitudinal observational data are often non-causal and occur due to confounding. The focus of this paper is to investigate incorpo...

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Bibliographic Details
Main Authors:	Reps, Jenna M., Aickelin, Uwe
Format:	Conference or Workshop Item
Published:	2014
Online Access:	https://eprints.nottingham.ac.uk/28260/

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