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.
This research output has an Altmetric Attention Score of 81. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 December 2023.
All research outputs
#569,723
of 26,726,803 outputs
Outputs from Frontiers in Psychology
#1,199
of 35,581 outputs
Outputs of similar age
#7,674
of 290,650 outputs
Outputs of similar age from Frontiers in Psychology
#19
of 532 outputs
Altmetric has tracked 26,726,803 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 35,581 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 290,650 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 532 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.
