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Tuesday, June 28 • 10:30am - 10:48am
bamdit: An R Package for Bayesian meta-analysis of diagnostic test data

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In this work we present the R package bamdit, its name stands for "Bayesian meta-analysis of diagnostic test-data". bamdit was developed with the aim of simplifying the use of models in meta-analysis, that up to now have demanded great statistical expertise in Bayesian meta-analysis. The package implements a series of innovative statistical techniques including: the Bayesian Summary Receiver Operating Characteristic curve, the use of prior distributions that avoid boundary estimation problems of component of variance and correlation parameters, analysis of conflict of evidence and robust estimation of model parameters. In addition, the package comes with several published examples of meta-analysis that can be used for illustration or further research in this area.

Moderators
avatar for Ben Goodrich

Ben Goodrich

Lecturer in the Discipline of Political Science, Columbia University
Ben Goodrich is a core developer of Stan, which is a collection of statistical software for Bayesian estimation of models, and is the maintainer of the corresponding rstan and rstanarm R packages. He teaches in the political science department and in the Quantitative Methods in the Social Sciences master's program at Columbia University.

Speakers
avatar for Pablo Emilio Verde

Pablo Emilio Verde

Senior Researcher, University of Düsseldorf
I am an R user since June 1998. I translated the R messages to Spanish and I have been maintaining this translation during several years. My main interest in R is in the use of Bayesian data analysis and Bayesian meta-analysis in clinical research.


Attendees (53)