@@ -463,18 +463,6 @@ class DifferenceInDifferences(ExperimentalDesign):
463463 ... }
464464 ... )
465465 ... )
466- >>> result.summary() # doctest: +NUMBER
467- ===========================Difference in Differences============================
468- Formula: y ~ 1 + group*post_treatment
469- <BLANKLINE>
470- Results:
471- Causal impact = 0.5, $CI_{94%}$[0.4, 0.6]
472- Model coefficients:
473- Intercept 1.0, 94% HDI [1.0, 1.1]
474- post_treatment[T.True] 0.9, 94% HDI [0.9, 1.0]
475- group 0.1, 94% HDI [0.0, 0.2]
476- group:post_treatment[T.True] 0.5, 94% HDI [0.4, 0.6]
477- sigma 0.0, 94% HDI [0.0, 0.1]
478466 """
479467
480468 def __init__ (
@@ -726,7 +714,7 @@ def _plot_causal_impact_arrow(self, ax):
726714 def _causal_impact_summary_stat (self ) -> str :
727715 """Computes the mean and 94% credible interval bounds for the causal impact."""
728716 percentiles = self .causal_impact .quantile ([0.03 , 1 - 0.03 ]).values
729- ci = "$CI_{94%}$" + f"[{ percentiles [0 ]:.2f} , { percentiles [1 ]:.2f} ]"
717+ ci = "$CI_{94\\ %}$" + f"[{ percentiles [0 ]:.2f} , { percentiles [1 ]:.2f} ]"
730718 causal_impact = f"{ self .causal_impact .mean ():.2f} , "
731719 return f"Causal impact = { causal_impact + ci } "
732720
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