A professional web application for conducting Structural Equation Modeling (SEM) analyses directly in your browser. Designed for researchers and data analysts in social sciences.

• Broad File Support

  • CSV, Excel (XLS/XLSX), SAS (sas7bdat)
  • Automatic missing data handling with deletion option
  • Real-time data preview

• Modeling Capabilities

  • 12+ predefined model templates across 4 categories
  • Live syntax editor with intelligent code suggestions
  • Full SEM parameters estimation (β coefficients, SEs, p-values)

• Advanced Diagnostics

  • Comprehensive fit indices: χ², RMSEA, CFI, TLI, NFI, GFI, AGFI
  • APA-style results formatting
  • Interactive parameter tables

1. Clone Repository

   git clone https://github.com/yourusername/sem-analysis-app.git
   cd sem-analysis-app

2. Install Dependencies

   pip install -r requirements.txt

3. Launch Application

   streamlit run main.py

1. Data Preparation

   • Upload dataset through sidebar
   • Handle missing values with one click
   • Verify variables in preview table

2. Model Specification

   graph LR
   A[Select Model Category] --> B[Choose Template]
   B --> C[Edit Syntax]
   C --> D[Run Analysis]
   

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3. Key Features

   • Cross-lagged panel models
   • Multi-group invariance testing
   • Latent interaction models
   • Bifactor modeling

• Core Components

  • Streamlit 1.32+ frontend
  • semopy 2.3.1 SEM backend
  • Pandas 2.0+ data handling

• Performance

  • Handles datasets up to 100,000 cells
  • Real-time model fitting <60s for typical models
  • Cached data processing

If using this tool in research:

@software{DiCicco_SEM_Analysis_2024,
  author = {Di Cicco, Gabriele},
  title = {SEM Analysis Web App},
  year = {2025},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {https://github.com/yourusername/sem-analysis-app}
}

Developed by
Gabriele Di Cicco, PhD