User Guide

This comprehensive user guide covers everything you need to know about using Causal Agent effectively in your research and analysis workflows.

Whether you’re conducting a single analysis or processing multiple datasets, this guide provides detailed instructions, best practices, and configuration options to help you get the most out of Causal Agent.

Guide Overview

Basic Usage: Learn the fundamental workflows for conducting causal analysis with Causal Agent, including data preparation, method selection, and result interpretation.
Advanced Usage: Explore advanced features like custom method selection, assumption validation, and integration with existing analysis pipelines.
Batch Processing: Process multiple datasets efficiently with automated workflows and parallel processing capabilities.
Configuration: Customize Causal Agent behavior, configure LLM providers, and set up your analysis environment for optimal performance.

Common Workflows

Single Dataset Analysis: Standard workflow for analyzing one dataset
Comparative Analysis: Comparing results across different methods
Sensitivity Analysis: Testing robustness of causal conclusions
Production Integration: Embedding Causal Agent in automated analysis pipelines

Best Practices

Always validate your data quality before analysis
Understand the assumptions of your chosen method
Use diagnostic tests to validate causal identification
Document your analysis decisions for reproducibility