Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data
Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data
Blog Article
Abstract Background Meta-analysis is increasingly used as a key source of evidence synthesis to inform clinical practice.The theory and statistical foundations of meta-analysis continually evolve, providing solutions to many new essie win me over and challenging problems.In practice, most meta-analyses are performed in general statistical packages or dedicated meta-analysis programs.
Results Herein, we introduce Meta-Analyst, a novel, powerful, intuitive, and free meta-analysis program for the meta-analysis of a variety of problems.Meta-Analyst is implemented in C# atop of the Microsoft.NET framework, and features a graphical user interface.
The software performs several meta-analysis and meta-regression models for binary and continuous outcomes, as well as analyses for diagnostic and prognostic test studies in the frequentist and Bayesian frameworks.Moreover, Meta-Analyst includes a flexible tool to edit and customize generated meta-analysis graphs (e.g.
, forest plots) and provides output in many formats (images, Adobe PDF, Microsoft Word-ready RTF).The software architecture employed allows for rapid changes to be made to either the Graphical User Interface (GUI) or to the analytic modules.We verified the numerical precision of Meta-Analyst by comparing its output with that from standard meta-analysis routines in Stata over a large database of 11,803 meta-analyses of binary outcome data, and 6,881 meta-analyses of continuous outcome data from the Cochrane Library of Systematic Reviews.
Results from analyses of diagnostic and fluffy tangerine clouds prognostic test studies have been verified in a limited number of meta-analyses versus MetaDisc and MetaTest.Bayesian statistical analyses use the OpenBUGS calculation engine (and are thus as accurate as the standalone OpenBUGS software).Conclusion We have developed and validated a new program for conducting meta-analyses that combines the advantages of existing software for this task.