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Bayesian estimation of log odds ratios from R × C and 2 × 2 × K contingency tables

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  • Haydar Demirhan
  • Canan Hamurkaroglu

Abstract

In this paper, Bayesian estimation of log odds ratios over R × C and 2 × 2 × K contingency tables is considered, which is practically reasonable in the presence of prior information. Likelihood functions for log odds ratios are derived for each table structure. A prior specification strategy is proposed. Posterior inferences are drawn using Gibbs sampling and Metropolis–Hastings algorithm. Two numerical examples are given to illustrate the matters argued.

Suggested Citation

  • Haydar Demirhan & Canan Hamurkaroglu, 2008. "Bayesian estimation of log odds ratios from R × C and 2 × 2 × K contingency tables," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(4), pages 405-424, November.
    • Handle: RePEc:bla:stanee:v:62:y:2008:i:4:p:405-424
    DOI: 10.1111/j.1467-9574.2008.00387.x
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    References listed on IDEAS

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    1. Michael J. Daniels, 2002. "Bayesian analysis of covariance matrices and dynamic models for longitudinal data," Biometrika, Biometrika Trust, vol. 89(3), pages 553-566, August.
    2. Zhen Chen & David B. Dunson, 2003. "Random Effects Selection in Linear Mixed Models," Biometrics, The International Biometric Society, vol. 59(4), pages 762-769, December.
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    Cited by:

    1. Demirhan, Haydar, 2013. "Bayesian estimation of order-restricted and unrestricted association models," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 109-126.
    2. Dickhaus Thorsten & Stange Jens & Demirhan Haydar, 2015. "On an extended interpretation of linkage disequilibrium in genetic case-control association studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(5), pages 497-505, November.
    3. Haydar Demirhan & Kamil Demirhan, 2016. "A Bayesian approach for the estimation of probability distributions under finite sample space," Statistical Papers, Springer, vol. 57(3), pages 589-603, September.

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