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#3 🚀 MAS V2: Now with Meta-Regression Analysis!

Updated: Feb 28

Great news! 🎉

As promised in my last post, Introduction to MAS: Meta-Analysis Simplified Software, I’ve been working on an exciting new featureMeta-Regression Analysis with continuous covariates!

🔍 What Does This Mean for You?

With this update, you can now explore the influence of continuous variables on your meta-analysis results, adding deeper insights to your research!

📌 How to Use It?

To use this feature, structure your dataset so that your covariate variable starts with the prefix “COV”. This allows the software to automatically detect it and suggest it for inclusion in the meta-regression model.

💡 Example: In my case, I named my covariate: “COV_Intervention_Duration_weeks”.

Here’s what your datasheet should look like in the MAS window with the newly added variable:

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Step-by-Step Guide to Running Meta-Regression:

✅ Step 1: Before running the meta-regression analysis, first perform a pairwise meta-analysis in the “Data Analysis” window. DO NOT FORGET THIS STEP AS MRA will not work.

✅ Step 2: Navigate to the fifth MAS app window, “Meta-Regression Analysis”, where you will see an option to select your covariate. 


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✅ Step 3: Choose your covariate and click RUN META-REGRESSION ANALYSIS!



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🎯 And that’s it! Enjoy the results, which can be downloaded as a CSV file, along with a Meta-Regression plot for easy interpretation!

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🎉 In the next update, MASimplified will support both "lm" (linear model) and "loess" (locally estimated scatterplot smoothing) regression plots in the Meta-Regression Analysis feature!

📊 What does this mean for you? With these enhancements, you'll have even more flexibility in visualizing trends within your meta-analysis data. Whether you prefer a straight-line fit (lm) or a smooth curve capturing nuanced patterns (loess), MASimplified will provide the tools you need!

🔔 Stay tuned for the update! More details coming soon—so keep an eye out! 👀

💬 I’d love to hear your feedback! What do you think of this new feature? Let’s keep improving MAS together! Drop your thoughts in the comments! 💡🙌

 

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