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Diffusion processes and event history analysis

Author

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  • Norman Braun
  • Henriette Engelhardt

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

Several authors (e.g., Brüderl, Diekmann, Yamaguchi) derive hazard rate models of event history analysis from social diffusion processes. This paper also focuses on the integration of diffusion research and survival analysis. After a discussion of Diekmann's flexible diffusion model, we present an alternative approach which clarifies theoretical differences between popular rate models (e.g., the exponential model, log-logistic model, sickle model). Specifically, this approach provides a new rationale for the generalized log-logistic model in the sense of a flexible infection process. In cases with bell-shaped duration dependence, it thus allows a test for social contagion as a result of random contacts between actual and potential adopters. An application to divorce data serves as an illustration.

Suggested Citation

  • Norman Braun & Henriette Engelhardt, 2002. "Diffusion processes and event history analysis," MPIDR Working Papers WP-2002-007, Max Planck Institute for Demographic Research, Rostock, Germany.
    • Handle: RePEc:dem:wpaper:wp-2002-007
    DOI: 10.4054/MPIDR-WP-2002-007
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    References listed on IDEAS

    as
    1. Courgeau, Daniel & Lelievre, Eva, 1993. "Event History Analysis in Demography," OUP Catalogue, Oxford University Press, number 9780198287384.
    2. David Strang, 1991. "Adding Social Structure to Diffusion Models," Sociological Methods & Research, , vol. 19(3), pages 324-353, February.
    3. Josef Brãœederl & Andreas Diekmann, 1995. "The Log-Logistic Rate Model," Sociological Methods & Research, , vol. 24(2), pages 158-186, November.
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    More about this item

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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