Bivariate Random-Effects Meta-analysis of Sensitivity and Specificity with the Bayesian SAS PROC MCMC
Jan Menke
Medical Decision Making, 2013, vol. 33, issue 5, 692-701
Abstract:
Background and Objective: Meta-analysis allows for summarizing the sensitivities and specificities from several primary diagnostic test accuracy studies quantitatively. This article presents and evaluates a full Bayesian method for bivariate random-effects meta-analysis of sensitivity and specificity with SAS PROC MCMC. Methods: First, the formula of the bivariate random-effects model is presented. Then its implementation with the Bayesian SAS PROC MCMC is empirically evaluated, using the published 2 × 2 count data of 50 meta-analyses. The convergence of the Markov chains is analyzed visually and qualitatively. The results are compared with a Bayesian WinBUGS approach, using the Bland-Altman analysis for assessing agreement between 2 methods. Results: The 50 meta-analyses covered broad ranges of pooled sensitivity (17.4% to 98.8%) and specificity (60.0% to 99.7%), and the between-study heterogeneity varied as well. In all meta-analyses, the Markov chains converged well. The meta-analytic results from the SAS PROC MCMC and the WinBUGS random-effects approaches were nearly similar, showing close 95% limits of agreement for the pooled sensitivity (–0.06% to 0.05%) and specificity (–0.05% to 0.05%) without significant differences (P > 0.05). This indicates that the bivariate model is well implemented with both different statistical programs, without systematic differences arising from program attributes. Conclusions: As alternative to a WinBUGS approach, the Bayesian SAS PROC MCMC is well suited for bivariate random-effects meta-analysis of sensitivity and specificity.
Keywords: diagnostic test evaluation; Bayesian meta-analysis; Bayesian statistical methods; hierarchical models; systematic reviews; meta-analysis (search for similar items in EconPapers)
Date: 2013
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X13475719 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:33:y:2013:i:5:p:692-701
DOI: 10.1177/0272989X13475719
Access Statistics for this article
More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().