Background The proposed sequential and combinatorial algorithm, suggested as a standard tool for assessing, exploring, and reporting heterogeneity in the meta-analysis, is useful but time-consuming particularly when the number of included studies is large. Metaplot is a novel graphical approach that facilitates performing sensitivity analysis to distinguish the source of substantial heterogeneity across studies with ease and speed. Method Metaplot is a Stata module based on Stata's commands, known informally as "ado". Metaplot presents a two-way (x, y) plot in which the x-axis represents the study codes and the y-axis represents the values of I-2 statistics excluding one study at a time (n-1 studies). Metaplot also produces a table in the 'Results window' of the Stata software including details such as I-2 and chi(2) statistics and their P-values omitting one study in each turn. Results Metaplot allows rapid identification of studies that have a disproportionate impact on heterogeneity across studies, and communicates to what extent omission of that study may reduce the overall heterogeneity based on the I-2 and chi(2) statistics. Metaplot has no limitations regarding the number of studies or types of outcome data (binomial or continuous data). Conclusions Metaplot is a simple graphical approach that gives a quick and easy identification of the studies having substantial influences on overall heterogeneity at a glance.
机构:
Univ Santiago Compostela, Fac Med, Sch Med,Area Med Prevent, Dept Prevent Med, Santiago De Compostela 15705, SpainUniv Santiago Compostela, Fac Med, Sch Med,Area Med Prevent, Dept Prevent Med, Santiago De Compostela 15705, Spain
Takkouche, B
Cadarso-Suárez, C
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机构:Univ Santiago Compostela, Fac Med, Sch Med,Area Med Prevent, Dept Prevent Med, Santiago De Compostela 15705, Spain
Cadarso-Suárez, C
Spiegelman, D
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机构:Univ Santiago Compostela, Fac Med, Sch Med,Area Med Prevent, Dept Prevent Med, Santiago De Compostela 15705, Spain