Closing the gap on causal processes of infection risk from cross-sectional data: structural equation models to understand infection and co-infection

Closing the gap on causal processes of infection risk from cross-sectional data: structural equation models to understand infection and co-infection

Abstract Background Epidemiological studies of disease exposure risk are frequently based on observational, cross-sectional data, and use statistical approaches as crucial tools for formalising causal processes and making predictions of exposure risks. However, an acknowledged limitation of traditio...

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Bibliographic Details
Main Authors: Scott Carver, Julia A. Beatty, Ryan M. Troyer, Rachel L. Harris, Kathryn Stutzman-Rodriguez, Vanessa R. Barrs, Cathy C. Chan, Séverine Tasker, Michael R. Lappin, Sue VandeWoude
Format: Article
Language:English
Published: BMC 2015-12-01
Series:Parasites & Vectors
Subjects:
Latent Variable
Infection Status
Feline Immunodeficiency Virus
Causal Process
Risk Factor Analysis
Online Access:https://doi.org/10.1186/s13071-015-1274-7

Internet

https://doi.org/10.1186/s13071-015-1274-7

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