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Reading this page will give you a bird’s eye view on the free statistical software Jamovi.
Jamovi is an open source free graphical user interface for the R programming language. Jamovi comes with a basic library of statistical and graphical procedures. In addition, users can install modules from a library of community created open source add-on modules to extend the package’s capabilities. These modules are written in the R programming language.
Brief overview of Jamovi
Jamovi is made by the scientific community, for the scientific community (and you can contribute if you want). Jamovi can be run as a cloud software without any download. Jamovi can also be downloaded as a desktop applicantion for Windows, MacOS, Linux and ChromeOS.
At its core, Jamovi is built on top of R and is a graphical interface (GUI) that simplifies the use of R programming. Jamovi is a hybrid that bridges the gap between a spreadsheet program (like Excel/SPSS) and the R coding language. Every time you click a button in Jamovi (e.g., to run a t-test), Jamovi generates and executes R code in the background. It uses the R statistical engine to perform all the math. This guarantees that Jamovi is just as accurate and robust as R. You are using the same professional-grade algorithms, just without typing the commands yourself. Jamovi has a unique feature called Syntax Mode that proves this connection. If you turn this mode on, Jamovi will show you the actual R code it is writing for you in real-time. You can copy that code, paste it into R (or RStudio), and it will run perfectly. This makes Jamovi an excellent tool for learning R. You can click the buttons to see what happens, then study the code to understand how to do it manually.
Jamovi is essentially a user-friendly wrapper around R. It hides the complexity of the R code but preserves the power of the R-engine. While R does the math, Jamovi adds a few features that R does not have natively:
- Dynamic Spreadsheet: It feels like SPSS or Excel. If you change a data point in the grid, all your tables and graphs update instantly. R does not do this (you have to re-run the script).
- APA Formatting: Jamovi automatically formats its output tables to meet APA (scientific publication) standards. In raw R, you often have to write extra code to make tables look presentable.
The relationship goes both ways. The developers created an R package called jmv. You can install this package inside standard R. This allows you to use Jamovi’s simplified functions inside RStudio, giving you the same easy-to-read results without leaving the coding environment. Below is a set of videos providing further instroduction to various procedures in Jamovi (and there are lots of more videos about Jamovi on YouTube).
Starting with Jamovi
Descriptive statistics with Jamovi
Inferential statistics with Janovi
Increase the functionality in Jamovi by adding modules
After you installed Jamovi it comes with a basic set of functions. You can add more functionality by adding more modules. There is no official webpage that presents a complete, user-friendly list with descriptions for all available modules. The “living” list exists instead directly inside the program under the “jamovi library”, as the selection is continuously updated by the community. The closest alternative to a web-based list is Jamovi’s developer page on GitHub, but it is technical and not very easy to read since it mixes source code with modules, making it difficult to get an overview). The absolute easiest way to see what is available and what the modules do is to browse inside the program:
- Start Jamovi.
- Click the plus sign (+) in the top right corner of the menu bar.
- Select “jamovi library”.
- Here you can scroll through all available modules. Clicking on a module provides a short description of its functions before you choose to install it.
Here is a summary of some of the modules most commonly used to extend Jamovi’s functionality, and what they add:
Advanced Statistics & Modeling
- GAMLj (General Analyses for Linear Models): One of the most essential modules. It adds support for Linear Mixed Models, Generalized Linear Models (GLM), and GEE. Indispensable if you have clustered data or need more advanced regression.
- medmod: For mediation and moderation analysis.
- jsq (JASP to jamovi): Adds a complete menu for Bayesian statistics (t-test, ANOVA, regression, etc.), similar to what is found in the statistical software JASP.
- walrus: Contains robust statistical tests (e.g., robust t-tests and ANOVAs) that handle deviations from normal distribution better than standard tests.
Medicine & Survival Analysis
- Death Watch: Adds Survival Analysis, including Kaplan-Meier curves and Cox regression.
- ClinicoPath: Tools specifically designed for clinical research and pathology, including decision analysis and diagnostic tests.
Visualization & Data Management
- scatr: Expands the capabilities of scatterplots, for example by adding density plots or boxplots along the axes.
- Rj (Editor to run R code): Allows you to write and execute pure R code directly inside Jamovi using Jamovi’s data. Perfect if you need a specific function from R that is not available as a button in Jamovi.
- jpower: Used for calculating statistical power and sample size.