Graphical displays for meta‐analysis: An overview with suggestions for practice

  title={Graphical displays for meta‐analysis: An overview with suggestions for practice},
  author={Judith Anzures‐Cabrera and Julian P.T. Higgins},
  journal={Research Synthesis Methods},
Meta-analyses are fundamental tools for collating and synthesizing large amounts of information, and graphical displays have become the principal tool for presenting the results of multiple studies of the same research question. [] Key Method We start with forest plots and funnel plots, and proceed to Galbraith (or radial) plots, L'Abbé (and related) plots, further plots useful for investigating heterogeneity, plots useful for model diagnostics and plots for illustrating likelihoods and Bayesian meta…

Graphics and Statistics for Cardiology: Data visualisation for meta-analysis

This report presents guidance to authors wishing to submit graphical displays as part of their meta-analysis to a clinical cardiology journal, such as Heart.

Graphics for Meta-Analysis

This work prepared programs and graphs using GenStat™, R, RevMan™, SAS™ and Stata™, and these are available from the website.

A further use for the Harvest plot: a novel method for the presentation of data synthesis

An important development is described that allows researchers to display evidence in a flexible way and means readers can follow an argument in a clear and efficient manner without the need for large volumes of descriptive text.

Visual representations of meta-analyses of multiple outcomes: Extensions to forest plots, funnel plots, and caterpillar plots

Extensions to the funnel plot, forest plot and caterpillar plot are described to adapt them to three-level meta-analyses to improve the detection of both publication bias and/or selective outcome reporting bias.

Charting the landscape of graphical displays for meta-analysis and systematic reviews: a comprehensive review, taxonomy, and feature analysis

A comprehensive overview of available graphs allows researchers to make better-informed decisions on which graphs suit their needs and therefore facilitates using the meta-analytic tool kit of graphs to its full potential.

Graphical Tools for Network Meta-Analysis in STATA

This paper provides a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

‘Cross hairs’ plots for diagnostic meta‐analysis

This paper explores the standard displays of diagnostic test accuracy data and proposes and explains an alternative approach to summarizing key data, and suggests 'cross-hairs' plots that are more easily interpreted, and are a more informative graphical form than common approaches.

A re‐evaluation of fixed effect(s) meta‐analysis

Meta‐analysis is a common tool for synthesizing results of multiple studies. Among methods for performing meta‐analysis, the approach known as ‘fixed effects’ or ‘inverse variance weighting’ is

Graphical Augmentations to the Funnel Plot to Assess the Impact of a New Study on an Existing Meta-Analysis

The implementation of a new range of overlay augmentations to the funnel plot are described, many described in detail recently by Langan et al. (2012), 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.

Considerations and recommendations for figures in Cochrane reviews : graphs of statistical data

  • Art
  • 2008
RevMan can perform and display meta-analyses of dichotomous data, continuous data and ‘O – E’ statistics and estimates and standard errors (Deeks 2001, Higgins 2008). It also allows graphical

Using the normal quantile plot to explore meta-analytic data sets.

In a meta-analysis, graphical displays can be used to check statistical assumptions for numerical procedures and they can be used to discover important patterns in the data. The authors propose the

A graphical display useful for meta-analysis

Graphical methods are frequently used in meta-analysis to summarize their results and to explore potential sources of heterogeneity across studies. In this paper, we illustrate a graphical method for

Graphical methods for detecting bias in meta-analysis.

The L'Abbé plot displays the outcomes in both the treatment and control groups of included studies and helps to decide whether the studies are too heterogeneous to appropriately combine into a single measure of effect.

More than numbers: the power of graphs in meta-analysis.

Ratings of the forest plot and the standardized residual histogram were best associated with parameter heterogeneity, and meta-analysts should be selective in the graphs they choose for the exploration of their data.

Trim and Fill: A Simple Funnel‐Plot–Based Method of Testing and Adjusting for Publication Bias in Meta‐Analysis

These are simple rank-based data augmentation techniques, which formalize the use of funnel plots, which provide effective and relatively powerful tests for evaluating the existence of publication bias.

The radial plot in meta‐analysis: approximations and applications

Summary.  Fixed effects meta‐analysis can be thought of as least squares analysis of the radial plot, the plot of standardized treatment effect against precision (reciprocal of the standard

Misleading funnel plot for detection of bias in meta-analysis.

A graphical method for exploring heterogeneity in meta‐analyses: application to a meta‐analysis of 65 trials

The proposed graphical method identifies trials that account for most of the heterogeneity without having to explore all possible sources of heterogeneity by subgroup analyses and can be applied to identify types of patients that explain heterogeneity in the treatment effect.

Evaluating the statistical conclusion validity of weighted mean results in meta-analysis by analysing funnel graph diagrams.

  • R. Elvik
  • Mathematics
    Accident; analysis and prevention
  • 1998