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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...
| Autores principales: | , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2015
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| Materias: | |
| 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 |