An empirical study using permutation-based resampling in meta-regression.

Systematic Reviews
Joel J GagnierJoseph Beyene

Abstract

In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared fin...Continue Reading

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Citations

Aug 1, 2012·BMC Medical Research Methodology·Joel J GagnierClaire Bombardier
Sep 6, 2013·BMC Medical Research Methodology·Joel J GagnierUNKNOWN Ann Arbor Clinical Heterogeneity Consensus Group
Jul 26, 2013·BMC Public Health·Lynne RushDaniel MacKay
Dec 12, 2012·General Hospital Psychiatry·Zhongheng ZhangHongying Ni
Jul 24, 2015·Journal of Cardiac Surgery·Fabrizio SettepaniGiuseppe Tarelli
Apr 24, 2017·American Journal of Obstetrics and Gynecology·Joemer C MaravillaRosa Alati

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