CART-GUI

A comprehensive GUI tool for analyzing Simple Reaction Time (SRT) data with support for multiple datasets, statistical analyses, and visualization options.

Table of Contents

• Features
  • Data Management
  • Visualization Options
  • Statistical Analysis
  • Data Filtering
• Installation
  • App Installation
  • Using Conda (Recommended)
  • Manual Installation
• Data Format Requirements
• Usage Guide
  • Basic Workflow
  • Advanced Features
    • Race Model Analysis
    • Statistical Analysis
    • Data Exclusion and Filtering
    • Scatter Plot Analysis
• Contributing
• License
• Support

Features

Data Management

• Load Multiple Datasets: Manage and analyze multiple datasets simultaneously.
• Supported Formats: Import data from CSV and Excel files.
• Dataset Combination: Combine multiple datasets for comprehensive analysis.
• Data Formatting: Format raw data files to the required structure with ease.
• Undo Modifications: Track dataset modifications with undo capabilities.

Visualization Options

• Mean and Median Reaction Times: Visualize mean and median reaction times across modalities and datasets.
• Boxplot Distributions: Compare distributions using boxplots.
• Participant Distributions: Analyze individual participant distributions.
• Race Model Analysis: Visualize race model predictions and violations.
• Scatter Plot Analysis: Explore relationships between various factors using scatter plots.

Statistical Analysis

• T-tests and Bayesian Analysis: Perform statistical tests within and between datasets.
• ANOVA Analysis: Conduct ANOVA for more complex comparisons.
• Race Model Violation Statistics: Analyze race model violations statistically.
• Correlation Analysis: Examine relationships between variables.

Data Filtering

• Participant Exclusion Tools: Exclude specific participants based on criteria.
• Trial-level Filtering: Filter out trials based on reaction time ranges, z-scores, or deviation from median.
• Demographic-based Filtering: Filter data based on demographic variables.
• Percentile-based Analysis Ranges: Focus on specific percentile ranges of the data.

Installation

App Installation

A self-contained Mac and Windows Application of the GUI can be found here: https://drive.google.com/drive/u/0/folders/1-9Q1lAr3J_TuC20k3hZWmOzC08LtW_hj. Note that you will need to allow the program to run through the control panel (windows) or settings (mac). The instructions in the sections below are for users who'd like to edit the source code. We also include a a program build_app_mac.py for those who want to convert their modifications into apps.

Using Conda (Recommended)

1. Clone the repository
2. Create the environment: conda env create -f environment.yml
3. Activate the environment: conda activate cart-gui

Manual Installation

1. Ensure Python 3.10+ is installed
2. Install required packages

Data Format Requirements

Required Columns

• participant_number (int): Unique identifier for each participant
• modality (int): Stimulus type
  • 1 = Audio
  • 2 = Visual
  • 3 = Audiovisual
• reaction_time (float): Response time in milliseconds

Optional Demographics

• age or SubjectAge
• gender or SubjectSex
• Additional demographic columns will be auto-detected

File Formats

• CSV (comma-separated values)
• Excel (.xlsx, .xls)
• First row must contain column headers

Usage Guide

Basic Workflow

1. Load Data:
   • Click "Load Dataset" button
   • Select CSV/Excel file
2. Configure dataset appearance
3. Data Preprocessing
4. Analysis Options
5. Export Results

Advanced Features

Race Model Analysis

• Supports multiple model types
• Configurable parameters
• Comprehensive analysis options

Statistical Analysis

• Multiple test options
• Various comparison types
• Effect size metrics

Data Exclusion and Filtering

• Participant exclusion options
• Trial filtering capabilities
• Preview and undo options

Scatter Plot Analysis

• Multiple factor analysis
• Customization options
• Statistical integration

Contributing

Please submit pull requests.

License

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

Support

• Issues: Submit through GitHub Issues
• Questions: Ask in Discussions