pystatpower.models.proportion.independent.ci ¶

Functions:

Name	Description
`solve_distance`	Calculate the confidence interval width or the distance from the proportion to the confidence bound for the difference between two independent proportions.

solve_distance ¶

solve_distance(
    *,
    treatment_proportion: float,
    reference_proportion: float,
    treatment_size: int,
    reference_size: int,
    conf_level: float = 0.95,
    interval_type: Literal[
        "two-sided", "lower one-sided", "upper one-sided"
    ] = "two-sided",
    method: Literal["chisq", "chisq_cc"] = "chisq",
) -> float

Calculate the confidence interval width or the distance from the proportion to the confidence bound for the difference between two independent proportions.

Parameters:

Name	Type	Description	Default
`treatment_proportion`	`float`	Actual proportion in the treatment group (\(p_1\)). Must be between 0 and 1.	required
`reference_proportion`	`float`	Actual proportion in the reference group (\(p_2\)). Must be between 0 and 1.	required
`treatment_size`	`int`	Sample size in the treatment group (\(n_1\)). Must be greater than 0.	required
`reference_size`	`int`	Sample size in the reference group (\(n_2\)). Must be greater than 0.	required
`conf_level`	`float`	Confidence level.	`0.95`
`interval_type`	`Literal['two-sided', 'lower one-sided', 'upper one-sided']`	Type of the confidence interval. `two-sided`: Two-sided confidence interval. `lower one-sided`: Lower one-sided confidence interval. `upper one-sided`: Upper one-sided confidence interval.	`'two-sided'`
`method`	`Literal['chisq', 'chisq_cc']`	Method to calculate the confidence interval width or the distance from the proportion to the confidence bound. `chisq`: Pearson's chi-square method. `chisq_cc`: Yate's chi-square with continuity correction method.	`'chisq'`

Returns:

Type	Description
`float`	The confidence interval width or the distance from the proportion to the confidence bound.