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Using Copulas for Bayesian Meta-analysis

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Abstract

Specific bivariate classes of distributions with given marginals can be used for contribution of the linking distribution between conditional and unconditional effectiveness using copulas. In this paper, a Bayesian model is proposed for meta-analysis of treatment effectiveness data which are generally discrete Binomial and sparse. A bivariate class of priors is imposed to accommodate a wide range of heterogeneity between the multicenter clinical trials involved in the study. Applications to real data are provided.

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Acknowledgements

The first author is grateful to Department of Science and Technology, Govt. of India for providing financial assistance for carrying out this work. All the authors also acknowledge the support provided by DST under PURSE grants.

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Authors and Affiliations

  1. Department of Statistics, Panjab University, Chandigarh, 160014, India

    Savita Jain, Suresh K. Sharma & Kanchan Jain

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  1. Savita Jain
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  2. Suresh K. Sharma
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  3. Kanchan Jain
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Correspondence to Savita Jain.

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Jain, S., Sharma, S.K. & Jain, K. Using Copulas for Bayesian Meta-analysis. Stat Biosci 14, 23–41 (2022). https://doi.org/10.1007/s12561-021-09312-8

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  • DOI: https://doi.org/10.1007/s12561-021-09312-8

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