TBR Documentation

Time-Based Regression (TBR) is a Python package for estimating treatment effects in before-after studies using treatment and control group time series data.

Use this documentation to get started with TBR, understand common analysis patterns, interpret result objects, and review the mathematical methodology behind the package.

User Guide

• TBR Quick Start Guide
  • Installation
  • Basic Usage
  • Complete Example
  • One-Liner Analysis
  • Next Steps
  • Key Concepts
  • Common Use Cases
  • Tips
  • Getting Help
• Common Patterns and Best Practices
  • Table of Contents
  • Data Preparation
  • Model Configuration
  • Analysis Patterns
  • Result Interpretation
  • Performance Tips
  • Common Pitfalls
  • Domain-Specific Guidance
  • See Also
• TBR Result Objects
  • Overview
  • Result Object Types
  • Common Patterns
  • Result Object Comparison
  • Tips and Best Practices
  • See Also

Reference

• TBR Mathematical Methodology
  • Table of Contents
  • Overview
  • Statistical Model
  • Prediction and Uncertainty
  • Treatment Effect Estimation
  • Statistical Inference
  • Subinterval Analysis
  • Model Diagnostics
  • Assumptions and Limitations
  • Notation Reference
  • References
• TBR API Reference
  • Table of Contents
  • TBRAnalysis
  • Result Objects
  • Functional API
  • Utility Functions
  • See Also