Calculating Pooled Mean and SD from Subgroup Data: Meta-Analysis Guide

Mayta
Jun 9
1 min read

🎯 Purpose

In clinical research and meta-analysis, it's common to have results from subgroups (e.g., age strata, treatment arms, centers). When each subgroup reports its mean, standard deviation (SD), and sample size, we need to aggregate these into a total (pooled) mean and SD to summarize overall effect or baseline characteristics.

This method is precise and accounts for both the group sizes and spread of data (variance), rather than simply averaging group means.

🧩 When to Use

You are synthesizing subgroups (e.g., males and females) into one group summary.
You are pooling data across centers or study sites.
The overall mean and SD are not directly reported, but you have per-group mean, SD, and n.

📌 Required Inputs

These are entered into light blue cells in the spreadsheet.

🧮 Step-by-Step Calculations

🔢 Example

Suppose you have 2 groups:

Group A: n = 30, mean = 100, SD = 15
Group B: n = 20, mean = 110, SD = 20

🧭 Usage Notes

The spreadsheet automates all calculations. Just fill in light blue boxes with subgroup data.
Leave unused rows blank; the sheet ignores them.
Useful in descriptive tables, forest plots, or protocol summaries.