{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:49:50Z","timestamp":1792788590836,"version":"4.5.0"},"reference-count":14,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T00:00:00Z","timestamp":1624838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"funder":[{"name":"Vice-Chancellor of Research and Technology, Hamadan University of Medical Sciences","award":["9603161751"],"award-info":[{"award-number":["9603161751"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"\n Background<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Method<\/jats:title>\n \n Metaplot is a Stata module based on Stata\u2019s 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\n 2<\/jats:sup>\n statistics excluding one study at a time (n-1 studies). Metaplot also produces a table in the \u2019Results window\u2019 of the Stata software including details such as I\n 2<\/jats:sup>\n and \u03c7\n 2<\/jats:sup>\n statistics and their\n P<\/jats:italic>\n -values omitting one study in each turn.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n 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\n 2<\/jats:sup>\n and \u03c7\n 2<\/jats:sup>\n statistics. Metaplot has no limitations regarding the number of studies or types of outcome data (binomial or continuous data).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>","DOI":"10.1371\/journal.pone.0253341","type":"journal-article","created":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T13:28:25Z","timestamp":1624886905000},"page":"e0253341","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":14,"title":["Metaplot: A new Stata module for assessing heterogeneity in a meta-analysis"],"prefix":"10.1371","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3758-3006","authenticated-orcid":true,"given":"Jalal","family":"Poorolajal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahla","family":"Noornejad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2021,6,28]]},"reference":[{"key":"pone.0253341.ref001","doi-asserted-by":"crossref","DOI":"10.1002\/9781119536604","volume-title":"Cochrane handbook for systematic reviews of interventions","author":"JPT Higgins","year":"2019"},{"key":"pone.0253341.ref002","doi-asserted-by":"crossref","DOI":"10.1002\/9780470743386","volume-title":"Introduction to Meta-Analysis","author":"V. 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