| name | performing-causal-analysis |
|---|---|
| description | Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD. |
Performing Causal Analysis
Executes causal analysis using CausalPy experiment classes.
Workflow
- Load Data: Ensure data is in a Pandas DataFrame.
- Initialize Experiment: Use the appropriate class (see References).
- Fit & Model: Models are fitted automatically upon initialization if arguments are provided.
- Analyze Results: Use
summary(),print_coefficients(), andplot().
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