Copyright
©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Meta-Anal. Aug 28, 2018; 6(3): 21-28
Published online Aug 28, 2018. doi: 10.13105/wjma.v6.i3.21
Published online Aug 28, 2018. doi: 10.13105/wjma.v6.i3.21
Improving the conduct of meta-analyses of observational studies
Peter N Lee, P.N. Lee Statistics and Computing Ltd., Sutton SM2 5DA, Surrey, United Kingdom
Author contributions: Lee PN wrote this editorial.
Conflict-of-interest statement: The author has no relevant conflict of interest to declare.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/
Correspondence to: Peter N Lee, MA, MSc, Senior Statistician, Director, P.N. Lee Statistics and Computing Ltd., 17 Cedar Road, Sutton SM2 5DA, Surrey,United Kingdom. peternlee@pnlee.co.uk
Telephone: +44-20-6428265 Fax: +44-20-8642135
Received: June 8, 2018
Peer-review started: June 8, 2018
First decision: July 11, 2018
Revised: July 16, 2018
Accepted: August 4, 2018
Article in press: August 4, 2018
Published online: August 28, 2018
Processing time: 81 Days and 17.6 Hours
Peer-review started: June 8, 2018
First decision: July 11, 2018
Revised: July 16, 2018
Accepted: August 4, 2018
Article in press: August 4, 2018
Published online: August 28, 2018
Processing time: 81 Days and 17.6 Hours
Core Tip
Core tip: The author has published many meta-analyses of epidemiological studies, particularly on smoking, and the editorial comments on various aspects of their conduct. Areas covered include the definition of the hypothesis to be tested, literature searching and data entry, as well as methods to test for heterogeneity and investigate such issues as confounding, misclassification and publication bias. The need for well conducted meta-analyses and the difficulty in determining whether a “statistically significant” association is actually indicative of a causal relationship are discussed. The editorial should be helpful to readers inexperienced with the conduct of meta-analyses.