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Increasing the capacity of conceptual diagrams to embrace contextual complexity

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  • David Britt
  • Yung-Chou Chen

Abstract

Conceptual models or diagrams have been used for many years to visually convey information, and they represent a subset of graphic presentation more generally. Historically, they have been used to describe, interpret and explain relationships among concepts deemed relevant to the understanding of some phenomena. This paper makes specific recommendations for increasing the capacity of models to clearly convey a particular form of complexity, that involving multiple contexts or levels of analysis. In particular, the inclusion of negotiated or constructed contexts as contexts, the use of small multiples to create a dialog with orienting models around specification decisions, and the representation of alternate scenarios are recommended. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • David Britt & Yung-Chou Chen, 2013. "Increasing the capacity of conceptual diagrams to embrace contextual complexity," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 567-576, January.
  • Handle: RePEc:spr:qualqt:v:47:y:2013:i:1:p:567-576
    DOI: 10.1007/s11135-011-9479-0
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    References listed on IDEAS

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    2. Rothman, K.J. & Greenland, S., 2005. "Causation and causal inference in epidemiology," American Journal of Public Health, American Public Health Association, vol. 95(S1), pages 144-150.
    3. Diez-Roux, A.V., 1998. "Bringing context back into epidemiology: Variables and fallacies in multilevel analysis," American Journal of Public Health, American Public Health Association, vol. 88(2), pages 216-222.
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