Copyright
©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Meta-Anal. Aug 28, 2020; 8(4): 345-347
Published online Aug 28, 2020. doi: 10.13105/wjma.v8.i4.345
Published online Aug 28, 2020. doi: 10.13105/wjma.v8.i4.345
Integrating contextual variables in meta-analyses
Haitham Jahrami, Ministry of Health, Kingdom of Bahrain; College of Medicine and Medial Sciences, Arabian Gulf University, Manama P.O Box 26671, Bahrain
Author contributions: Jahrami H wrote this letter.
Conflict-of-interest statement: No conflict of interest.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Haitham Jahrami, PhD, Assistant Professor, College of Medicine and Medial Sciences, Arabian Gulf University, Road 2904 Building 293 Manama, Manama PO Box 26671, Bahrain. hjahrami@health.gov.bh
Received: May 20, 2020
Peer-review started: May 20, 2020
First decision: July 4, 2020
Revised: July 4, 2020
Accepted: August 15, 2020
Article in press: August 15, 2020
Published online: August 28, 2020
Processing time: 113 Days and 6.6 Hours
Peer-review started: May 20, 2020
First decision: July 4, 2020
Revised: July 4, 2020
Accepted: August 15, 2020
Article in press: August 15, 2020
Published online: August 28, 2020
Processing time: 113 Days and 6.6 Hours
Core Tip
Core Tip: This letter call for the use of contextual variables, that are typically not in use for covariate analyses. Contextual variables are introduced and defined as variables not immediately/directly measured by the original studies in the meta-analysis but rather can be estimated knowing the background of each study. For example in a meta analysis of clinical trails one might want to adjust for studies from high income vs low income countries or studies that were funded vs independent.