Metaplot: A new Stata module for assessing heterogeneity in a meta-analysis

被引:9
|
作者
Poorolajal, Jalal [1 ,2 ]
Noornejad, Shahla [3 ]
机构
[1] Hamadan Univ Med Sci, Sch Publ Hlth, Dept Epidemiol, Hamadan, Hamadan, Iran
[2] Hamadan Univ Med Sci, Modeling Noncommunicable Dis Res Ctr, Sch Publ Hlth, Hamadan, Hamadan, Iran
[3] Hamadan Univ Med Sci, Sch Publ Hlth, Hamadan, Hamadan, Iran
来源
PLOS ONE | 2021年 / 16卷 / 06期
关键词
D O I
10.1371/journal.pone.0253341
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:12
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