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Application of a continuous-time Markov chain to a preclinical study

Publication ,  Journal Article
Al-Khalidi, HR; Schnell, DJ
Published in: Drug Information Journal
1997

A continuous-time Markov model is used to analyze electrocardiogram data obtained from a preclinical study in rabbits of five antiarrhythmic compounds. The preclinical protocol and data are introduced briefly. Some theoretical background for finite-state continuous-time Markov chain models is presented. The electrocardiogram data are then modeled as a continuous- time Markov process with the states being five categories of arrhythmias. The Markov model used assumes that the dwell times in the states are independent and exponentially distributed according to a parameter which depends on the antiarrhythmic compound and the arrhythmia state. For the five antiarrhythmic compounds the transition probabilities from state-to-state and the limiting distributions of the process are calculated and compared.

Duke Scholars

Published In

Drug Information Journal

Publication Date

1997

Volume

31

Issue

2

Start / End Page

607 / 613

Related Subject Headings

  • Statistics & Probability
  • 1117 Public Health and Health Services
  • 0104 Statistics
 

Citation

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Al-Khalidi, H. R., & Schnell, D. J. (1997). Application of a continuous-time Markov chain to a preclinical study. Drug Information Journal, 31(2), 607–613.
Al-Khalidi, H. R., and D. J. Schnell. “Application of a continuous-time Markov chain to a preclinical study.” Drug Information Journal 31, no. 2 (1997): 607–13.
Al-Khalidi HR, Schnell DJ. Application of a continuous-time Markov chain to a preclinical study. Drug Information Journal. 1997;31(2):607–13.
Al-Khalidi, H. R., and D. J. Schnell. “Application of a continuous-time Markov chain to a preclinical study.” Drug Information Journal, vol. 31, no. 2, 1997, pp. 607–13.
Al-Khalidi HR, Schnell DJ. Application of a continuous-time Markov chain to a preclinical study. Drug Information Journal. 1997;31(2):607–613.

Published In

Drug Information Journal

Publication Date

1997

Volume

31

Issue

2

Start / End Page

607 / 613

Related Subject Headings

  • Statistics & Probability
  • 1117 Public Health and Health Services
  • 0104 Statistics