Performing Causal Analysis

Executes causal analysis using CausalPy experiment classes.

Workflow

1. Load Data: Ensure data is in a Pandas DataFrame.
2. Initialize Experiment: Use the appropriate class (see References).
3. Fit & Model: Models are fitted automatically upon initialization if arguments are provided.
4. Analyze Results: Use summary(), print_coefficients(), and plot().

Core Methods

• experiment.summary(): Prints model summary and main results.
• experiment.plot(): Visualizes observed vs. counterfactual.
• experiment.print_coefficients(): Shows model coefficients.

References

Detailed usage for specific methods:

• Difference-in-Differences
• Interrupted Time Series
• Synthetic Control