Please use this identifier to cite or link to this item: http://hdl.handle.net/11054/2102
Title: How to apply structural equation modelling to infectious diseases concepts.
Author: Hurley, James C.
Issue Date: 2022
Publication Title: Clinical Microbiology and Infection
Volume: 28
Issue: 12
Start Page: 1567
End Page: 1571
Abstract: Background Structural equation modelling (SEM) can address causation questions of great interest to infectious disease physicians and infection control practitioners that would elude techniques based on tests of association. These models address questions such as the size of intervention effects mediated on entities that cannot be easily measured, questions that cannot be studied in randomized controlled trials and question arising from ‘big data.’ Objectives To outline the computational and, moreover, conceptual differences between SEM methods versus the traditional tests of association. Sources Google scholar search for “structural equation modelling” and “infection." Content Several examples of SEM applications to infectious diseases topics are used to illustrate. The SEM technique enables postulated causation models to be confronted with data. With this, the candidate models emerge as either ‘importantly wrong’ or potentially useful for enabling empiric predictions from the one identified as optimal. Implications Applications of SEM techniques and related modelling techniques to infectious diseases research will likely continue to emerge, especially so with the availability of ‘big data.’
URI: http://hdl.handle.net/11054/2102
DOI: https://doi.org/10.1016/j.cmi.2022.05.028
Internal ID Number: 02076
Health Subject: BIG DATA
CANDIDA
CAUSATION
PSEUDOMONAS
STRUCTURAL EQUATION MODELLING
STUDY DESIGN
Type: Journal Article
Article
Appears in Collections:Research Output

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