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Review
. 2015 Oct 8:6:1549.
doi: 10.3389/fpsyg.2015.01549. eCollection 2015.

From pre-registration to publication: a non-technical primer for conducting a meta-analysis to synthesize correlational data

Daniel S Quintana  1
Affiliations
Review

From pre-registration to publication: a non-technical primer for conducting a meta-analysis to synthesize correlational data

Daniel S Quintana. Front Psychol. .

Abstract

Meta-analysis synthesizes a body of research investigating a common research question. Outcomes from meta-analyses provide a more objective and transparent summary of a research area than traditional narrative reviews. Moreover, they are often used to support research grant applications, guide clinical practice, and direct health policy. The aim of this article is to provide a practical and non-technical guide for psychological scientists that outlines the steps involved in planning and performing a meta-analysis of correlational datasets. I provide a supplementary R script to demonstrate each analytical step described in the paper, which is readily adaptable for researchers to use for their analyses. While the worked example is the analysis of a correlational dataset, the general meta-analytic process described in this paper is applicable for all types of effect sizes. I also emphasize the importance of meta-analysis protocols and pre-registration to improve transparency and help avoid unintended duplication. An improved understanding this tool will not only help scientists to conduct their own meta-analyses but also improve their evaluation of published meta-analyses.

Keywords: meta-analysis; methods; pre-registration; primer; publication bias; statistics.

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Figures

FIGURE 1
FIGURE 1
Meta-analysis in the psychological sciences. An illustration of the increasing interest in performing meta-analyses in the psychological sciences. PubMed data was collected on the number of articles containing the search terms “psychology” and “meta-analysis” published between 1980 and 2014 per 100,000 PubMed articles. Data was collected using the ‘RISmed’ R package.
FIGURE 2
FIGURE 2
Psychology journals that publish the greatest number of meta-analyses. The number of publications containing the keywords “psychology” and “meta-analysis” for the 25 journals with the most meta-analysis in psychology. Data was collected using the ‘RISmed’ R package.
FIGURE 3
FIGURE 3
Baujat plot to identify studies contributing to heterogeneity. Each study is represented by a study id number. Studies located in the top right quadrant have both a greater influence on the overall result and contribute most to study heterogeneity.
FIGURE 4
FIGURE 4
Forest plot of example data. Summary of example data investigating the relationship between conscientiousness and medication adherence. Each study included in the meta-analysis is represented by a point estimate, which is bounded by a 95% CI. The summary effect size is displayed as a polygon at the bottom of the plot, with the width of the polygon representing the 95% CI.
FIGURE 5
FIGURE 5
Funnel plots to illustrate publication bias. Funnel plot (A) includes all 16 studies from Molloy et al. (2014). This plot illustrates symmetry (i.e., points fall on both sides of the summary effect size). Egger’s regression test (p = 0.31) was consistent with this data, as the p-value was above 0.05. Funnel plot (B) simulates the removal of three studies with small effect sizes and large standard error from the Molloy et al. (2014) dataset. The plot is no longer symmetrical, demonstrating evidence of publication bias. Egger’s regression test (p = 0.01) was also consistent with this data, as the p-value was below 0.05. The trim and fill procedure imputes missing studies (hollow circles) to create a more symmetrical funnel plot (C).
See this image and copyright information in PMC

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