#2 Introduction to MAS: Meta-Analysis Simplified Software

In my previous post, I presented some basic insights about systematic reviews. Here, I am starting from the tip of the SLR mountain by introducing my newly developed software for conducting meta-analysis—completely FREE of charge!" A meta-analysis is an essential tool in research, enabling scholars and practitioners to synthesize findings from multiple studies to draw more robust conclusions. However, traditional meta-analysis can be complex, requiring extensive statistical knowledge and proficiency in specialized software. That’s where MAS: Meta-Analysis Simplified comes in—a user-friendly, efficient, and powerful software designed to make meta-analysis accessible to everyone.

MAS is an application developed using R programming and hosted on Shinyapps.io. It currently supports Excel .csv files, providing a seamless experience for researchers looking to conduct a meta-analysis with minimal effort.

MAS online software

Why MAS?

MAS was developed to bridge the gap between advanced meta-analysis techniques and researchers who may not have a deep statistical background. It provides an intuitive interface, automates calculations, and includes visualization tools to simplify data interpretation.

Here are a few key benefits of MAS:

• Ease of Use – No advanced statistical knowledge is required.

• Comprehensive Features – Includes summarized effect size calculation, forest plots, publication bias detection, and more.

• Automation – Reduces manual data entry and eliminates the need for complex coding.

• Transparency & Reproducibility – Ensures results can be verified and easily replicated.

• It is completely free. Last but not least, an important point to mention.

Key Features of MAS

MAS includes a range of powerful features that facilitate the entire meta-analysis process:

1. Data Input & Management

MAS enables users to load data in an Excel .csv data frame, making it easy to import study datasets for analysis.

2. Fixed and Random Effects Meta-Analysis

Users can conduct both fixed and random effects meta-analysis models, allowing flexibility in handling different types of research data.

3. Sensitivity Analysis

MAS supports sensitivity analysis, enabling users to exclude specific studies from the analysis to assess their impact on the overall results.

4. Forest Plot Visualization

A forest plot feature is included for visual representation of meta-analysis results, making it easier to interpret and communicate findings.

5. Publication Bias Assessment

MAS includes funnel plots and Egger’s regression test to help detect and assess potential publication bias in the studies being analyzed.

6. Downloadable Outputs

Users can download all graphical outputs (forest plots, funnel plots) in JPG, PNG, and TIFF formats, while meta-analysis results and Egger’s regression test results can be saved as CSV files for further use.

Step-by-Step Guide to Using MAS

To help users get started, here’s a step-by-step guide:

1. Load Your Data: Upload your Excel .csv file to MAS. In my personal repository, you can find and download the Excel (.csv) data frame file for initial testing of the MAS software.
   

   
   

   

   This is how your data set should look after loading.

   
   

2. Choose Analysis Type: Select between fixed and random effects models and Run Meta-analysis. Then download your results in Excel.csv format.

Choose between fixed-Effect or Random-Effects (REML) and click Run Meta-Analysis.

3. Conduct Sensitivity Analysis: Exclude studies as needed to observe their impact.

4. Generate Forest Plot: Visualize results for better interpretation.

5. Assess Publication Bias: Use funnel plots and Egger’s test.
   

   

   Publication Bias Assessment page.

1. Download Your Results: Save outputs in your preferred format (JPG, PNG, TIFF, CSV).

   
   

Who Can Benefit from MAS?

MAS is ideal for:

• Researchers conducting systematic reviews and meta-analyses.

• Graduate students new to meta-analysis.

• Professionals in healthcare, psychology, education, and other research-intensive fields.

• Organizations need a reliable tool for evidence synthesis.

  
  

Getting Started with MAS

If you’re ready to streamline your meta-analysis process, MAS is here to help. Stay tuned for our next blog post, where we will walk you through a detailed tutorial on using MAS for your first meta-analysis.

Future Updates

In upcoming updates, MAS will introduce sub-analysis and meta-regression analysis of continuous variables, further expanding its capabilities.

Explore the power of MAS today and take your research to the next level! 🚀 A future post will cover the algorithms behind MAS and feature video demonstrations of its capabilities. Stay tuned!" ✏️Author: Assist. Prof. Armin Paravlić, PhD