title: Metaplot: a novel stata graph for assessing heterogeneity at a glance.
abstract: BACKGROUND
  Heterogeneity is usually a major concern in meta-analysis. Although there are some statistical approaches for assessing variability across studies, here we present a new approach to heterogeneity using "MetaPlot" that investigate the influence of a single study on the overall heterogeneity.
  
  
  METHODS
  MetaPlot is a two-way (x, y) graph, which can be considered as a complementary graphical approach for testing heterogeneity. This method shows graphically as well as numerically the results of an influence analysis, in which Higgins' I(2) statistic with 95% (Confidence interval) CI are computed omitting one study in each turn and then are plotted against reciprocal of standard error (1/SE) or "precision". In this graph, "1/SE" lies on x axis and "I(2) results" lies on y axe.
  
  
  RESULTS
  Having a first glance at MetaPlot, one can predict to what extent omission of a single study may influence the overall heterogeneity. The precision on x-axis enables us to distinguish the size of each trial. The graph describes I(2) statistic with 95% CI graphically as well as numerically in one view for prompt comparison. It is possible to implement MetaPlot for meta-analysis of different types of outcome data and summary measures.
  
  
  CONCLUSIONS
  This method presents a simple graphical approach to identify an outlier and its effect on overall heterogeneity at a glance. We wish to suggest MetaPlot to Stata experts to prepare its module for the software.
authors.affiliation: Dept. of Epidemiology and Biostatistics, School of Public Health, Hamedan University of Medical Sciences, Iran.
authors.forename: J
authors.initials: J
authors.lastname: Poorolajal
authors.forename: M
authors.initials: M
authors.lastname: Mahmoodi
authors.forename: R
authors.initials: R
authors.lastname: Majdzadeh
authors.forename: A
authors.initials: A
authors.lastname: Fotouhi
keywords: Heterogeneity; Meta-Analysis; Stata graph; Systematic review