tuma: A graphical user interface for teaching univariate meta-analysis
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README.org

tuma: A graphical user interface for teaching univariate meta-analysis

Overview

tuma is an add-on package for R http://www.r-project.org and provides a graphical user interface (GUI) to visualize univariate fixed effect (FEM) and random effects model (REM) meta-analysis. By interactively manipulating effect sizes and standard errors, it is possible to better understand their relationship with summary (FEM and REM) and heterogeneity related statistics (Q, I^2 and tau^2). Additionally, two plots are created which show a typical forest plot as well as a density plot with N(hat{theta}, tau^2). These plots also change if the individual effects sizes or standard errors are manipulated.

Screenshot

f_screenshot.png

Installation

The easiest way to install the package is to use the install_github() function. The install_github() function is provided by the devtools package.

tuma also makes use of the Bwidget library. To install the Bwidget library under Windows, go to http://www.stat.berkeley.edu/users/spector/s133/Bwidget.html and follow the instructions. Linux users should be able to install the package bwidget via their package manager (e.g., under Debain/Ubuntu just use sudo apt-get install bwidget).

If you are on MS Windows, it also seems that you need to have Rtools installed. So, you first have to install the package devtools (via install.packages("devtools"), don’t get confused by the message “Rtools not installed.”) and then run:

  1. install_github("tuma", "berndweiss")
  2. library(tuma)

Binaries for MS Win (.zip) or Linux (.tar.gz) can be found in /build

Usage

The tuma GUI can be started by typing tumaGUI().

Unfortunateley, the package does not work well with RStudio! So, do not call the tuma package from within RStudio.

TODOs

  • fix layout of summary stats
  • add save-plot-button
  • change color of “effect size squares” to gray
  • allow user to plot FEM or REM forest plot; or maybe both…
  • button to increase ssample size (e.g. double,

triple sample size)

Acknowledgements

This work was supported by a fellowship within the “Postdoc-Programme” of the German Academic Exchange Service (DAAD).