MedModr
Mediation & Moderation Software · v1.0
Path Diagram
Simple Slopes
MedModr/Home
Statistical Analysis Software

Mediation & Moderation,
done right.

Browser-based statistical analysis for simple mediation, serial mediation, moderation, and moderated mediation. Full OLS with both unstandardized and standardized coefficients, exact CIs, bootstrapping, interactive path diagrams, annotated simple slopes plots, and APA reporting.

4
Analysis Types
OLS
Matrix Regression
b + β
Both Coefficients
Bootstrap
Indirect Effect CIs
Key Features
Simple Mediation
X → M → Y with full path coefficients (b and β), Sobel test, indirect effect CIs, and interactive path diagram.
Serial Mediation
X → M1 → M2 → Y with specific indirect paths, total indirect effects, and bootstrapped CIs.
Moderation
X × W → Y with both unstandardized and standardized coefficients in every table. Simple slopes at ±1 SD and mean.
Moderated Mediation
Conditional indirect effects, index of moderated mediation.
Annotated Slopes Plot
Slopes plot with b and p-value embedded inside each line label. Toggle annotations on/off. Full screen + hi-res download.
Export & APA Reporting
APA-formatted summaries, Word document export, and copy-to-clipboard for manuscripts.

MedModr © - Present
Free, browser-based. All computations run entirely client-side. Your data never leaves your device.
Site built in Ghana by Mudasir Mohammed Ibrahim
View Source Code

Mediation & Moderation Analysis

Paste one value per line (no header). All variables must have equal N. Interactions, mean-centering, and standardized coefficients are computed automatically.

Analysis Type
Each column = one covariate. Mean-centered automatically.
Confidence level: Bootstrap samples:

Documentation

Statistical methodology, coefficient definitions, CI notes, and contributing.

Statistical Methodology

MedModr uses Ordinary Least Squares (OLS) regression via matrix algebra. Every table reports both unstandardized (b) and standardized (β) coefficients for all predictors.

β = (X'X)⁻¹X'y  |  SE(β) = √[MSE · diag(X'X)⁻¹]  |  t = b/SE  |  CI = b ± t*(df,α/2) × SE
  • Unstandardized b: Raw regression coefficient. Interpreted in original units.
  • Standardized β: Computed by running the identical regression on z-scored variables.
  • Indirect effects: Product of path coefficients (a×b). Bootstrap CIs use the percentile method.
  • Simple Slopes Plot: Each slope line legend label (Low/Mean/High) includes the slope coefficient b and p-value directly within it.

Full documentation is available at: https://shinyopensource.github.io/documentation/

Open Source & Contributing

MedModr is a free, open-source project and is actively maintained.

Get Involved

Whether you want to add a new analysis type, improve the visualisation engine, fix a bug, or translate the interface, contributions of all sizes are appreciated.

Fork the repository
Make your changes
Submit a pull request
Feature ideas, bug reports, and discussion are all welcome via the GitHub Issues tracker.

Developer

Connect with the developer of MedModr.

👨‍💻
Mudasir Mohammed Ibrahim

MedModr was built to provide researchers with a free, accurate, and accessible tool for mediation and moderation analysis entirely in the browser.

Connect with me
mudasiribrahim.com ResearchGate ORCID Google Scholar Contact
Citation

If you use MedModr in your research, please cite it as:

Ibrahim, M. M. (). MedModr: A browser-based mediation and moderation analysis suite (Version 1.0) [Software]. Available from https://medmodr.vercel.app

About MedModr

Free, browser-based statistical software for mediation and moderation analysis.

About This Tool

MedModr is a free web application for mediation and moderation analysis. All statistical computations run entirely in your browser — no data is sent to any server, ever.

  • No login required — use it directly in your browser
  • Privacy-first — all computation is client-side
  • Both b and β — every regression table shows unstandardized and standardized coefficients side by side
  • Annotated simple slopes — b and p-value shown inside each slope label; toggle on/off
  • Automatic interactions — mean-centering and X×W are handled behind the scenes
  • Built in Ghana 🇬🇭 — by Mudasir Mohammed Ibrahim

Full documentation: https://shinyopensource.github.io/documentation/