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A Bayesian approach to the analysis of asymmetric association for two-way contingency tables

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Listed:
  • Zheng Wei

    (University of Maine)

  • Daeyoung Kim

    (University of Massachusetts)

  • Erin M. Conlon

    (University of Massachusetts)

Abstract

Recently, a subcopula-based asymmetric association measure was developed for the variables in two-way contingency tables. Here, we develop a fully Bayesian method to implement this measure, and examine its performance using simulation data and several real data sets of colorectal cancer. We use coverage probabilities and lengths of the interval estimators to compare the Bayesian approach and a large-sample method of analysis. In simulation studies, we find that the Bayesian method outperforms the large-sample method on average, and provides either similar or improved results for the real data analyses.

Suggested Citation

  • Zheng Wei & Daeyoung Kim & Erin M. Conlon, 2022. "A Bayesian approach to the analysis of asymmetric association for two-way contingency tables," Computational Statistics, Springer, vol. 37(3), pages 1311-1338, July.
    • Handle: RePEc:spr:compst:v:37:y:2022:i:3:d:10.1007_s00180-021-01161-9
    DOI: 10.1007/s00180-021-01161-9
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    References listed on IDEAS

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    1. Alan Agresti & David B. Hitchcock, 2005. "Bayesian inference for categorical data analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(3), pages 297-330, December.
    2. Malay Ghosh & Li Zahng & Bhramar Mukherjee, 2006. "Equivalence of posteriors in the Bayesian analysis of the multinomial-Poisson transformation," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 19-28.
    3. Leena Choi & Jeffrey D Blume & William D Dupont, 2015. "Elucidating the Foundations of Statistical Inference with 2 x 2 Tables," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-22, April.
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