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

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 traditional mode...

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Detalles Bibliográficos
Autores principales: Carver, Scott, Beatty, Julia A., Troyer, Ryan M., Harris, Rachel L., Stutzman-Rodriguez, Kathryn, Barrs, Vanessa R., Chan, Cathy C., Tasker, Séverine, Lappin, Michael R., VandeWoude, Sue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4690417/
https://www.ncbi.nlm.nih.gov/pubmed/26701692
http://dx.doi.org/10.1186/s13071-015-1274-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4690417/
https://www.ncbi.nlm.nih.gov/pubmed/26701692
http://dx.doi.org/10.1186/s13071-015-1274-7

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