PanelRegression.effect_summary#

PanelRegression.effect_summary(*, window='post', direction='increase', alpha=0.05, cumulative=True, relative=True, min_effect=None, treated_unit=None, period=None, prefix='Post-period', **kwargs)[source]#

Generate a decision-ready summary of causal effects.

Note

effect_summary() is not yet implemented for PanelRegression. Panel fixed-effects models estimate regression coefficients rather than time-varying causal impacts, so the standard ITS/SC-style effect summary does not directly apply. Use summary() for coefficient-level inference.

Parameters:

  • window (Union[Literal['post'], tuple, slice]) – Time window for analysis (placeholder; not consumed).

  • direction (Literal['increase', 'decrease', 'two-sided']) – Direction for tail probability calculation.

  • alpha (float) – Significance level for HDI/CI intervals.

  • cumulative (bool) – Whether to include cumulative effect statistics.

  • relative (bool) – Whether to include relative effect statistics.

  • min_effect (float | None) – Region of Practical Equivalence (ROPE) threshold.

  • treated_unit (str | None) – Treated unit selector for multi-unit experiments.

  • period (Optional[Literal['intervention', 'post', 'comparison']]) – Period selector for three-period designs.

  • prefix (str) – Prefix for prose generation.

  • **kwargs (Any) – Reserved for forward-compatibility.

Raises:

NotImplementedError – Always raised; this method is a placeholder for future work.

Return type:

EffectSummary