In such cases, the algorithm that results in the maximum decrease in the I 2 statistic below the desired threshold is selected. In the last step, there is a possibility that more than one omitted study can result in I 2 dropping below the intended threshold. This sequential and combinatorial algorithm is repeated several times until the I 2 statistic drops below the desired threshold value of 50%. This process is repeated for a new set of n-1 studies. Then, the study that is responsible for the largest decrease in I 2 value should be dropped out.
This ‘one-out’ sensitivity analysis tells us to what extent the overall heterogeneity changes by excluding a particular study at a time. According to this algorithm, one study is excluded from the meta-analysis at a time and the impact of the excluded study on the between-study heterogeneity is evaluated based on I 2 statistic and χ 2 test. Ī common approach, which was proposed by Patsopoulos et al, is to perform a sensitivity analysis based on a sequential and combinatorial algorithm. When there is heterogeneity in a meta-analysis, the source of heterogeneity across studies should be carefully investigated on a case-by-case basis. The between-studies heterogeneity can be assessed by the chi-square test also written as χ 2 or Chi 2 and can be quantified by I 2 statistics. This variability across studies is called heterogeneity. The studies that are brought together in a meta-analysis inevitably differ in many aspects. However, the funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.
The work is made available under the Creative Commons CC0 public domain dedication.ĭata Availability: All relevant data are within the manuscript and its Supporting information files.įunding: The Vice-Chancellor of Research and Technology, Hamadan University of Medical Sciences funded this study (No.
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. Received: FebruAccepted: JPublished: June 28, 2021 PLoS ONE 16(6):Įditor: Mohammad Asghari Jafarabadi, Tabriz University of Medical Sciences, ISLAMIC REPUBLIC OF IRAN Citation: Poorolajal J, Noornejad S (2021) Metaplot: A new Stata module for assessing heterogeneity in a meta-analysis.
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