In this paper we present the R package bamdit. The name of the package 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 variances and correlations of random effects, 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 illustrati...
Numerous meta-analyses in healthcare research combine results from only a small number of studies, f...
Numerous meta-analyses in healthcare research combine results from only a small number of studies, f...
In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayes...
This paper introduces the R package meta4diag for implementing Bayesian bivariate meta-analyses of d...
This paper introduces the R package meta4diag for implementing Bayesian bivariate meta-analyses of d...
BACKGROUND: Random-effects meta-analysis within a hierarchical normal modeling framework is commonly...
Meta-analysis refers to the collection and subsequent statistical analysis of results from numerous ...
We introduce an R package, bspmma, which implements a Dirichlet-based random effects model specific ...
With the growing number of studies looking at the performance of diagnostic tests, combining the st...
Abstract Background Several reviews have noted shortc...
Although measures such as sensitivity and specificity are used in the study of diagnostic test accur...
The R-package mada is a tool for the meta-analysis of diagnostic accuracy. In con-trast to univariat...
Use of historical data in clinical trial design and analysis has shown various advantages such as re...
We outline a Bayesian model-averaged (BMA) meta-analysis for standardized mean differences in order ...
BackgroundThe statistical models developed for meta-analysis of diagnostic test accuracy studies req...
Numerous meta-analyses in healthcare research combine results from only a small number of studies, f...
Numerous meta-analyses in healthcare research combine results from only a small number of studies, f...
In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayes...
This paper introduces the R package meta4diag for implementing Bayesian bivariate meta-analyses of d...
This paper introduces the R package meta4diag for implementing Bayesian bivariate meta-analyses of d...
BACKGROUND: Random-effects meta-analysis within a hierarchical normal modeling framework is commonly...
Meta-analysis refers to the collection and subsequent statistical analysis of results from numerous ...
We introduce an R package, bspmma, which implements a Dirichlet-based random effects model specific ...
With the growing number of studies looking at the performance of diagnostic tests, combining the st...
Abstract Background Several reviews have noted shortc...
Although measures such as sensitivity and specificity are used in the study of diagnostic test accur...
The R-package mada is a tool for the meta-analysis of diagnostic accuracy. In con-trast to univariat...
Use of historical data in clinical trial design and analysis has shown various advantages such as re...
We outline a Bayesian model-averaged (BMA) meta-analysis for standardized mean differences in order ...
BackgroundThe statistical models developed for meta-analysis of diagnostic test accuracy studies req...
Numerous meta-analyses in healthcare research combine results from only a small number of studies, f...
Numerous meta-analyses in healthcare research combine results from only a small number of studies, f...
In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayes...