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Probability Models for Duration: The Data Don′t Tell the Whole Story

Author

Listed:
  • Marc Vanhuele

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • Marnik G. Dekimpe
  • Sharma Sunil
  • Donald G. Morrison

Abstract

Probability models for duration have been applied to a wide range of individual-level and organizational phenomena. Interestingly, seemingly similar models may produce different results. Using divorce as an illustration, we discuss a hierarchy of duration models of different complexity and show how an analysis of the results across models helps explain why different studies may have come to different conclusions. This analysis also leads to substantive insights that even the most complete model by itself does not provide.

Suggested Citation

  • Marc Vanhuele & Marnik G. Dekimpe & Sharma Sunil & Donald G. Morrison, 1995. "Probability Models for Duration: The Data Don′t Tell the Whole Story," Post-Print hal-00457580, HAL.
    • Handle: RePEc:hal:journl:hal-00457580
    DOI: 10.1006/obhd.1995.1026
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    Cited by:

    1. ter Braak, Anne & Geyskens, Inge & Dekimpe, Marnik G., 2014. "Taking private labels upmarket: Empirical generalizations on category drivers of premium private label introductions," Journal of Retailing, Elsevier, vol. 90(2), pages 125-140.
    2. Meade, Nigel & Islam, Towhidul, 2010. "Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study," European Journal of Operational Research, Elsevier, vol. 200(3), pages 908-917, February.

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    Keywords

    probability model; duration;

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