(Meta-Analysis R Code and RevMan Figures) A Systematic Review and Meta-Analysis of the Association between E-Cigarette Use among Non-Tobacco Users and Initiating Smoking of Combustible Cigarettes
Creators: name: Kim, Mimi
Publisher: name: Zenodo
Year: 2024

description: In the early stages of designing this systematic review, it was recognized that there was a high probability of encountering significant heterogeneity across studies, given the diverse characteristics highlighted in numerous previous reviews. This foresight guided the choice of a statistical method that could handle variability effectively while simplifying the interpretation of the findings. Consequently, the DerSimonian and Laird method was used for its ability to meet these needs. The DerSimonian and Laird method stands out for its simplicity and efficiency, particularly with datasets that are not small (Jackson et al., 2010). Its appropriateness lies in its non-iterative approach for estimating variance between studies, which simplifies computations and clarifies result interpretation (DerSimonian & Laird, 1986). Additionally, its frequent application and proven effectiveness across various fields further affirm its appropriateness for the research question. While some criticisms exist regarding its simplicity, comparative studies have demonstrated that the DerSimonian and Laird method holds up well against more complex, computationally demanding techniques (DerSimonian & Kracker, 2017; Jackson et al., 2010; Kontopantelis E & Reeves D, 2012a; Kontopantelis E & Reeves D, 2012b). These studies suggest that in most situations, the method's simplicity does not compromise its adequacy, offering little benefit in opting for more intricate methods (DerSimonian & Laird, 2015). To ensure the reliability of the findings of this review’s meta-analysis, a validation analysis was conducted using the restricted maximum likelihood (REML) approach, and confirmed the results with almost identical pooled estimates (Viechtbauer 2005). This cross-validation underscores the DerSimonian and Laird method's applicability for the meta-analysis conducted in this review.

 

DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986 Sep;7(3):177-88. doi: 10.1016/0197-2456(86)90046-2.

Jackson D, Bowden J, Baker R. How does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts?. Journal of Statistical Planning and Inference. 2010 Apr 1;140(4):961-70.

DerSimonian R, Kacker R. Random-effects model for meta-analysis of clinical trials: an update. Contemporary Clinical Trials. 2007;28:105–114.

Kontopantelis E, Reeves D. Performance of statistical methods for meta-analysis when true study effects are non-normally distributed: A simulation study. Statistical Methods in Medical Research. 2012a;21(4):409–426.

Kontopantelis E, Reeves D. Performance of statistical methods for meta-analysis when true study effects are non-normally distributed: A comparison between DerSimonian-Laird and restricted maximum likelihood. Statistical Methods in Medical Research. 2012b;21(6):657–659.

DerSimonian R, Laird N. Meta-analysis in clinical trials revisited. Contemp Clin Trials. 2015 Nov;45(Pt A):139-45. doi: 10.1016/j.cct.2015.09.002. Epub 2015 Sep 4.

Viechtbauer, W. Bias and Efficiency of Meta-Analytic Variance Estimators in the Random-Effects Model. Journal of Educational and Behavioral Statistics. 2005; 30(3), 261-293.