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A semi‐Markov model of disease recurrence in insured dogs

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  • Xikui Wang
  • Jeffrey S. Pai
  • Kevin J. Shand

Abstract

We use a semi‐Markov model to analyse the stochastic dynamics of disease occurrence of dogs insured in Canada from 1990 to 1999, and the probability pattern of death from illness. After statistically justifying the use of a stochastic model, we demonstrate that a stationary first‐order semi‐Markov process is appropriate for analysing the available data set. The probability transition function is estimated and its stationarity is tested statistically. Homogeneity of the semi‐Markov model with respect to important covariates (such as geographic location, insurance plan, breed and age) is also statistically examined. We conclude with discussions and implications of our results in veterinary contents. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Xikui Wang & Jeffrey S. Pai & Kevin J. Shand, 2007. "A semi‐Markov model of disease recurrence in insured dogs," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 23(5), pages 429-437, September.
    • Handle: RePEc:wly:apsmbi:v:23:y:2007:i:5:p:429-437
    DOI: 10.1002/asmb.681
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    1. Delia Montoro-Cazorla & Rafael Pérez-Ocón & Alicia Pereira das Neves-Yedig, 2021. "A Longitudinal Study of the Bladder Cancer Applying a State-Space Model with Non-Exponential Staying Time in States," Mathematics, MDPI, vol. 9(4), pages 1-19, February.

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