JTNA - Jamovi Transition Network Analysis Module

A comprehensive Jamovi plugin for performing Transition Network Analysis (TNA) to study relational dynamics and behavioral patterns in sequential data. This module provides an intuitive graphical interface for transition network analysis techniques within the Jamovi statistical software environment.

🎯 Features

Core TNA Analysis

• Build TNA Models: Create transition networks from sequential behavioral data
• Centrality Measures: Calculate betweenness, closeness, degree, and eigenvector centrality
• Network Visualization: Generate publication-ready transition network plots
• Statistical Validation: Bootstrap and permutation tests

🆕 Sequence Analysis

• Sequence Visualization: Plot behavioral sequences with multiple display options
• Flexible Geometry: Choose between bar charts and area plots
• Scaling Options: Display as distributions or proportions
• Customizable Styling: Full control over colors, themes, and appearance

Group Analysis

• Multi-group Comparisons: Analyze TNA patterns across different groups
• Comparative Visualizations: Side-by-side network and sequence comparisons
• Group-specific Statistics: Separate centrality measures and network metrics

Advanced Features

• Interactive Plotting: Network visualizations with customizable layouts
• Export Options: High-quality publication-ready outputs
• Comprehensive Statistics: Detailed network metrics and behavioral insights
• User-friendly Interface: Intuitive GUI designed for researchers

📊 Analysis Types

Analysis	Description	Key Features
TNA	Individual transition network analysis	Network plots, centrality measures, histograms, sequences
Group TNA	Multi-group comparison analysis	Comparative networks, group statistics, side-by-side visualizations

🚀 Installation

Method 1: Direct Installation (Recommended)

1. Download the latest .jmo file from the releases page
2. Open Jamovi
3. Navigate to Modules → Jamovi library → Sideload
4. Select the downloaded JTNA_1.2.0.jmo file
5. Restart Jamovi to activate the module

Method 2: Development Installation

# Install jmvtools if not already installed
install.packages('jmvtools', repos=c('https://repo.jamovi.org', 'https://cran.r-project.org'))

# Load library and set Jamovi path
library(jmvtools)
options(jamovi_home="/path/to/your/jamovi")

# Navigate to module directory and install
setwd("path/to/TNAModule")
jmvtools::install()

📁 Project Structure

JTNA/
├── TNAModule/                    # Main module directory
│   ├── R/                       # R processing scripts
│   │   ├── TNA.b.R             # TNA analysis implementation
│   │   ├── TNA.h.R             # TNA interface definitions
│   │   ├── GroupTNA.b.R        # Group TNA implementation
│   │   └── GroupTNA.h.R        # Group TNA interface
│   │
│   ├── jamovi/                  # UI definition files
│   │   ├── TNA.a.yaml          # TNA analysis options
│   │   ├── TNA.u.yaml          # TNA user interface
│   │   ├── GroupTNA.a.yaml     # Group TNA options
│   │   └── GroupTNA.u.yaml     # Group TNA interface
│   │
│   ├── DESCRIPTION             # Package metadata
│   ├── NAMESPACE               # Function exports
│   └── JTNA_1.4.0.jmo         # Compiled module file
│
└── README.md                   # This file

🎮 Quick Start

1. Load Your Data

• Import your sequential behavioral data into Jamovi
• Ensure data includes participant IDs, timestamps, and behavioral codes

2. Run TNA Analysis

• Go to Analyses → JTNA → TNA
• Select your variables (participant, time, behavior)
• Configure analysis options
• Generate network plots and statistics

3. Explore Sequence Analysis

• In the same analysis, navigate to Sequence Analysis
• Choose visualization type (bar/area)
• Customize colors and styling
• Generate sequence plots

4. Compare Groups (Optional)

• Use Analyses → JTNA → Group TNA for multi-group analysis
• Specify grouping variable
• Compare networks and sequences across groups

📖 Documentation & Tutorials

• TNA Basics: Introduction to Transition Network Analysis
• Frequency-based TNA: Advanced TNA Techniques
• Clustering with TNA: Pattern Discovery Methods

📚 Citation

If you use JTNA in your research, please cite:

@inproceedings{saqr2024transition,
  title={Transition Network Analysis: A Novel Method for Analyzing Sequential Data},
  author={Saqr, Mohammed and López-Pernas, Sonsoles and Tikka, Santtu},
  booktitle={Proceedings of the Conference},
  year={2024},
  doi={10.1145/3706468.3706513}
}

👥 Authors & Contributors

• Mohammed Saqr - Development & Research
• Dylan Girault - Lead Developer
• Santtu Tikka - Statistical Methods
• Sonsoles López-Pernas - Research & Development

Maintainer: Mohammed Saqr (saqr@saqr.me)

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🐛 Bug Reports & Feature Requests

• Issues: GitHub Issues
• Discussions: GitHub Discussions

🔄 Version History

Version 1.4.0 (Latest)

• ✨ New: Sequence Analysis feature with bar and area plot options
• ✨ New: Enhanced customization options for plots
• 🔧 Improved: User interface and workflow
• 🐛 Fixed: Various stability improvements