BaseExperiment.effect_summary#

abstractmethod BaseExperiment.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.

Parameters:

  • window (Union[Literal['post'], tuple, slice]) –

    Time window for analysis (ITS/SC only, ignored for DiD/RD):

    • ”post”: All post-treatment time points (default)

    • (start, end): Tuple of start and end times (handles both datetime and integer indices)

    • slice: Python slice object for integer indices

  • direction (Literal['increase', 'decrease', 'two-sided']) –

    Direction for tail probability calculation (PyMC only, ignored for OLS):

    • ”increase”: P(effect > 0)

    • ”decrease”: P(effect < 0)

    • ”two-sided”: Two-sided p-value, report 1-p as “probability of effect”

  • alpha (float) – Significance level for HDI/CI intervals (1-alpha confidence level). For Bayesian models the effective HDI probability is hdi_prob = 1 - alpha. Note that this is independent of the project-wide HDI_PROB constant (currently 0.94) used by plot() and get_plot_data_bayesian(), so the same experiment may report a 95% HDI in effect_summary() and a 94% HDI in plot() with default settings.

  • cumulative (bool) – Whether to include cumulative effect statistics (ITS/SC only, ignored for DiD/RD)

  • relative (bool) – Whether to include relative effect statistics (% change vs counterfactual) (ITS/SC only, ignored for DiD/RD)

  • min_effect (float | None) – Region of Practical Equivalence (ROPE) threshold (PyMC only, ignored for OLS). If provided, reports P(|effect| > min_effect) for two-sided or P(effect > min_effect) for one-sided.

  • treated_unit (str | None) – For multi-unit experiments (Synthetic Control), specify which treated unit to analyze. If None and multiple units exist, uses first unit.

  • period (Optional[Literal['intervention', 'post', 'comparison']]) – For experiments with multiple periods (e.g., three-period ITS), specify which period to summarize. Defaults to None for standard behavior.

  • prefix (str) – Prefix for prose generation (e.g., “During intervention”, “Post-intervention”). Defaults to “Post-period”.

  • kwargs (Any)

Returns:

Object with .table (DataFrame) and .text (str) attributes. The .text attribute contains a detailed multi-paragraph narrative report.

Return type:

EffectSummary