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The role of conceptual frameworks in epidemiological analysis: a hierarchical approach.

Victora, C. G., Huttly, S. R., Fuchs, S. C., Olinto, M. T.·1997·International Journal of Epidemiology

Abstract

BACKGROUND: This paper discusses appropriate strategies for multivariate data analysis in epidemiological studies. METHODS: In studies where determinants of disease are sought, it is suggested that the complex hierarchical inter-relationships between these determinants are best managed through the use of conceptual frameworks. Failure to take these aspects into consideration is common in the epidemiological literature and leads to underestimation of the effects of distal determinants. RESULTS: An example of this analytical approach, which is not based purely on statistical associations, is given for assessing determinants of mortality due to diarrhoea in children. CONCLUSIONS: Conceptual frameworks provide guidance for the use of multivariate techniques and aid the interpretation of their results in the light of social and biological knowledge.

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Metadata

Authors
Victora, C. G., Huttly, S. R., Fuchs, S. C., & Olinto, M. T.
Venue
International Journal of Epidemiology
Published
1997-02-01
Volume
26
Issue
1
Pages
224-227
ISSN
  • 0300-5771 (ISSN-L)
  • 1464-3685
OpenAlex
W2127625194
Cited by
2,402
References
0
FWCI
17.95
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. https://app.cochat.ai/papers/10.1093/ije/26.1.224
The paper
Victora, C. G., Huttly, S. R., Fuchs, S. C., & Olinto, M. T. (1997). The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. International Journal of Epidemiology. https://doi.org/10.1093/ije/26.1.224

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.