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Diffusion Processes and Event History Analysis

  • Norman Braun
  • Henriette Engelhardt
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    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 generalised 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.

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    File URL: http://epub.oeaw.ac.at/0xc1aa500d_0x00062018
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    Article provided by Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna in its journal Vienna Yearbook of Population Research.

    Volume (Year): 2 (2004)
    Issue (Month): 1 ()
    Pages: 111-132

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    Handle: RePEc:vid:yearbk:v:2:y:2004:i:1:p:111-132
    Contact details of provider: Web page: http://www.oeaw.ac.at/vid/

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    1. Courgeau, Daniel & Lelievre, Eva, 1993. "Event History Analysis in Demography," OUP Catalogue, Oxford University Press, number 9780198287384, March.
    2. Josef Brãœederl & Andreas Diekmann, 1995. "The Log-Logistic Rate Model," Sociological Methods & Research, , vol. 24(2), pages 158-186, November.
    3. Barbara Petrongolo & Christopher A. Pissarides, 2000. "Looking Into the Black Box: A Survey of the Matching Function," CEP Discussion Papers dp0470, Centre for Economic Performance, LSE.
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