Abstract
Meta-analysis of diagnostic test accuracy (DTA) studies differs from meta-analysis of intervention studies in a number of respects. In this chapter, we explain the issues raised by meta-analysis of diagnostic accuracy studies and how these may be addressed. Alongside the statistical models, we present the R package mada [5] written for fitting these models and graphing the results.
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Notes
- 1.
To install the R package mada use the R command install.packages("mada") . This will automatically install the package R package mvmeta which it depends on.
- 2.
Confidence limits would be still different if we used the argument correction. control="none" as different methods are used to calculate these.
- 3.
We use R object oldpar in order to restore the settings of the graphics windows. This is recommended after changing these settings for a specific plot; however, from now on we do not display this command.
- 4.
R code to generate the figure is given in the web-appendix.
- 5.
R code to generate the ROC curve is given in the web-appendix.
- 6.
Note that this parameter should not be confused with the parameter \(\lambda\) of the hierarchical model.
- 7.
Even though we are only interested in an estimate of parameter \(\lambda\), the rsSROC command generates a plot.
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Schwarzer, G., Carpenter, J.R., Rücker, G. (2015). Meta-Analysis of Diagnostic Test Accuracy Studies. In: Meta-Analysis with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-21416-0_9
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