Performing Causal Analysis
by pymc-labs
Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.
Skill Details
Repository Files
4 files in this skill directory
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:
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