Metaplot: A Novel Stata Graph for Assessing Heterogeneity at a Glance

Background: heterogeneity is usually a major concern in meta-analysis. although there are some statistical approaches forassessing variability across studies, here we present a new approach to heterogeneity using metaplot that investigate theinfluence 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 testingheterogeneity. this method shows graphically as well as numerically the results of an influence analysis, in which higgins'i2 statistic with 95% (confidence interval) ci are computed omitting one study in each turn and then are plotted againstreciprocal of standard error (1/se) or precision. in this graph, 1/se lies on x axis and i2 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 theoverall heterogeneity. the precision on x-axis enables us to distinguish the size of each trial. the graph describes i2 statisticwith 95% ci graphically as well as numerically in one view for prompt comparison. it is possible to implement metaplot formeta-analysis of different types of outcome data and summary measures.conclusion: this method presents a simple graphical approach to identify an outlier and its effect on overall heterogeneityat a glance. we wish to suggest metaplot to stata experts to prepare its module for the software.