causalkit.inference.conversion_z_test

causalkit.inference.conversion_z_test(data, confidence_level=0.95)

Perform a two-proportion z-test on a CausalData object with a binary outcome (conversion).

Parameters:

• data (CausalData) – The CausalData object containing treatment and outcome variables.

• confidence_level (float, default 0.95) – The confidence level for calculating confidence intervals (between 0 and 1).

Returns:

A dictionary containing: - p_value: Two-sided p-value from the z-test - absolute_difference: Difference in conversion rates (treated - control) - absolute_ci: Tuple (lower, upper) for the absolute difference CI - relative_difference: Percentage change relative to control rate - relative_ci: Tuple (lower, upper) for the relative difference CI

Return type:

Dict[str, Any]

Raises:

ValueError – If treatment/outcome are missing, treatment is not binary, outcome is not binary, groups are empty, or confidence_level is outside (0, 1).