Graphical augmentations to the funnel plot to assess the impact of a new study on an existing meta-analysis

Michael J. Crowther (), Dean Langan () and Alex J. Sutton ()
Additional contact information
Michael J. Crowther: University of Leicester
Dean Langan: University of Leeds
Alex J. Sutton: University of Leicester

Stata Journal, 2012, vol. 12, issue 4, 605-622

Abstract: Funnel plots are currently advocated to investigate the presence of publication bias (and other possible sources of bias) in meta-analysis. A previously described augmentation to the funnel plot—to aid its interpretation in assessing publication biases—is the addition of statistical contours indicating regions where studies would have to be for a given level of significance, as implemented in the Stata package confunnel by Palmer et al. (2008, Stata Journal 8: 242–254). In this article, we describe http://www.stata-journal.com/software/the implementation of a new range of overlay aug- mentations to the funnel plot, many described in detail recently by Langan et al. (2012, Journal of Clinical Epidemiology 65: 511–519). The purpose of these over- lays is to display the potential impact a new study would have on an existing meta-analysis, providing an indication of the robustness of the meta-analysis to the addition of new evidence. Thus these overlays extend the use of the funnel plot beyond assessments of publication biases. Two main graphical displays are described: 1) statistical significance contours, which define regions of the funnel plot where a new study would have to be located to change the statistical signifi- cance of the meta-analysis; and 2) heterogeneity contours, which show how a new study would affect the extent of heterogeneity in a given meta-analysis. We present the extfunnel command, which implements the methods of Langan et al. (2012, Journal of Clinical Epidemiology 65: 511–519), and, furthermore, we extend the graphical displays to illustrate the impact a new study has on lower and upper confidence interval values and the confidence interval width of the pooled meta-analytic result. We also describe http://www.stata-journal.com/software/overlays for the impact of a future study on user-defined limits of clinical equivalence. We implement inverse- variance weighted methods by using both explicit formulas for contour lines and a simulation approach optimized in Mata. Copyright 2012 by StataCorp LP.

Keywords: extfunnel; funnel plots; meta-analysis; graphs (search for similar items in EconPapers)
Date: 2012
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