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Paper Information

Journal:   IRANIAN JOURNAL OF PUBLIC HEALTH   2010 , Volume 39 , Number 2; Page(s) 102 To 104.
 
Paper: 

METAPLOT: A NOVEL STATA GRAPH FOR ASSESSING HETEROGENEITY AT A GLANCE

 
 
Author(s):  POURALAJAL J.*, MAHMOUDI M., MAJDZADEH R., FOTOUHI A.
 
* DEPT. OF EPIDEMIOLOGY AND BIOSTATISTICS, SCHOOL OF PUBLIC HEALTH, HAMEDAN UNIVERSITY OF MEDICAL SCIENCES, IRAN
 
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' I2 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 "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 the overall heterogeneity. The precision on x-axis enables us to distinguish the size of each trial. The graph describes I2 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.
Conclusion: 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.
 

 
Keyword(s): HETEROGENEITY, META-ANALYSIS, SYSTEMATIC REVIEW, STATA GRAPH
 
References: 
 
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