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Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data

Jeruza L Neyeloff¹, Sandra C Fuchs, Leila B Moreira

¹Post Graduate Program of Cardiology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. jeruza_med@yahoo.com.br.

BMC Research Notes

|January 24, 2012

Summary

This guide provides a step-by-step method for conducting meta-analyses using Microsoft Excel. It also details how to create customized, visually appealing forest plots for descriptive data.

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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

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Published on: January 2, 2011

Area of Science:

Biostatistics
Medical Research Methodology

Background:

Meta-analyses are crucial for synthesizing research data, especially from observational studies.
Existing statistical software often requires coding or is costly, with limitations in handling descriptive data and graphical representation.
Microsoft Excel offers a viable platform for meta-analysis, but a comprehensive guide was previously lacking.

Purpose of the Study:

To provide a detailed guide for performing meta-analyses within Microsoft Excel.
To develop a method for generating customized and statistically sound forest plots using Excel.
To address the limitations of existing software for descriptive data meta-analysis.

Main Methods:

A step-by-step guide was developed for conducting meta-analyses in Microsoft Excel.
Fixed-effect and random-effects models were implemented within the Excel framework.
A separate Excel spreadsheet was created for generating customized forest plots.

Main Results:

A functional guide for meta-analysis using Microsoft Excel was successfully constructed.
A novel method for creating customized forest plots summarizing descriptive data was developed.
The developed method produces statistically adequate and graphically appealing visualizations.

Conclusions:

Meta-analyses can be effectively performed using only Microsoft Excel.
This work presents the first known method for generating high-quality forest plots for descriptive data with accessible software.
The developed Excel-based approach enhances the accessibility and visual presentation of meta-analysis results.