关于
This skill facilitates the rigorous validation of quasi-experimental models, such as Interrupted Time Series, Difference-in-Differences, and Synthetic Control, by simulating interventions at times when no actual change occurred. By implementing a factory pattern to decouple experiment logic from the testing framework, it allows data scientists to systematically execute placebo-in-time tests across multiple data folds, helping to confirm the absence of pre-intervention effects and the overall robustness of causal claims within the CausalPy ecosystem.
