Introduction, comparison, and validation of Meta-Essentials: A free and simple tool for meta-analysis.
Robert Suurmond, Henk van Rhee, Tony Hak
December 2017 Res Synth MethodsSynopsis of Social media discussions
The discussions reflect a generally favorable attitude towards the article, with comments like 'a legit excel spreadsheet' and references to the tool being 'user-friendly but limited.' The tone suggests interest in improving research workflows, with examples comparing the tool to other software like R, emphasizing practicality over high-end capabilities.
Agreement
Moderate agreementMost discussions express a positive view of the publication, especially comparing it favorably to previous tools and highlighting its usefulness.
Interest
Moderate level of interestThe topics are of moderate interest, as participants discuss practical tools and compare features, but without overly enthusiastic language.
Engagement
Moderate level of engagementThe posts show a basic level of engagement, including sharing personal experiences with tools and brief evaluations.
Impact
Moderate level of impactThe conversations indicate that the publication could influence research practices by providing accessible tools, though the tone remains practical rather than revolutionary.
Social Mentions
YouTube
4 Videos
3 Posts
Blogs
2 Articles
Metrics
Video Views
3,740
Total Likes
35
Extended Reach
23,987
Social Features
9
Timeline: Posts about article
Top Social Media Posts
Posts referencing the article
Meta-Essentials for Efficient Meta-Analysis Tools
This video shows how to get MetaEssentials workbooks for doing meta-analysis quickly. Meta-Essentials is a free and user-friendly tool that simplifies effect size calculations and supports subgroup, moderator, and publication bias analyses, ideal for general meta-analysis tasks.
Meta-Analysis Using Meta-Essentials: Practical Examples and Validation
This tutorial explains how to perform meta-analysis with Meta-Essentials, a free and user-friendly tool for combining measures between independent groups for binary and continuous data. It covers effect size calculations, subgroup, moderator, and publication bias analyses.
Meta-Essentials for Meta-Analysis: A User-Friendly Statistical Tool
This tutorial explains statistical procedures in MetaEssentials workbooks for quick meta-analysis. Meta-Essentials is a free, easy-to-use tool that automates effect size calculations and supports subgroup and bias analyses.
Meta-Essentials for Efficient Meta-Analysis: Features and Validation
This video shows how to learn MetaEssentials workbooks for doing meta-analysis quickly. Meta-Essentials is a free, user-friendly tool for automatic effect size calculation, subgroup analysis, moderator analysis, and publication bias assessments.
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RT @NL_Wetenschap: Ik heb ook een set Excel-tools voor meta-analyse mede-ontwikkeld die volop worden gebruik in onderzoek en onderwijs: htt…
view full postFebruary 25, 2022
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@NL_Wetenschap
@NL_Wetenschap (Twitter)Ik heb ook een set Excel-tools voor meta-analyse mede-ontwikkeld die volop worden gebruik in onderzoek en onderwijs: https://t.co/PxIzYHnqda. Vrij simpel te gebruiken maar ook beperkt in functionaliteit. De tool zelf introduceren en vergelijken we hier https://t.co/7SUOIijH81
view full postFebruary 25, 2022
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Michael Noetel
@mnoetel (Twitter)@DanielGucciardi @roxannefelig +1 for @DanielGucciardi's paper and this book is gold if you have a handle on R: https://t.co/e7sxdFULqg This paper has a legit excel spreadsheet that does a lot of work, but without all the bells and whistles you can use in R https://t.co/sEYPyyUp4p
view full postJuly 6, 2021
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Abstract Synopsis
- Meta-Essentials is a free and user-friendly meta-analysis tool that simplifies the process by automatically calculating effect sizes from various statistics.
- The tool provides features for subgroup analysis, moderator analysis, and publication bias analyses, while also incorporating the Knapp-Hartung adjustment for confidence intervals.
- However, it does not support more complex methods like meta-analytical structural equation modeling or meta-regression with multiple covariates, making it best suited for general meta-analysis tasks.
Dr. Paula Mommersteeg
@PaulaUvT (Twitter)