pystatpower.proportion.independent.ci ¶

FUNCTION	DESCRIPTION
`solve_distance`	Calculate the confidence interval width or the distance from the proportion difference to the confidence limit.
`solve_size`	Estimate the required sample size.
`solve_treatment_proportion`	Estimate the required proportion in the treatment group.
`solve_reference_proportion`	Estimate the required proportion in the reference group.

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", "upper"] = "two-sided",
    method: Literal["chisq", "wilson", "farrington_manning", "fm", "miettinen_nurminen", "mn"],
    continuity_correction: bool = False,
) -> float

Calculate the confidence interval width or the distance from the proportion difference to the confidence limit.

PARAMETER	DESCRIPTION
`treatment_proportion`	Proportion in the treatment group. TYPE: `float`
`reference_proportion`	Proportion in the reference group. TYPE: `float`
`treatment_size`	Sample size in the treatment group. TYPE: `int`
`reference_size`	Sample size in the reference group. TYPE: `int`
`conf_level`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level is required. If `interval_type` is `'lower'` or `'upper'`, a one-sided confidence level is required. TYPE: `float` DEFAULT: `0.95`
`interval_type`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval. TYPE: `Literal['two-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`method`	The method used to construct the confidence interval. `'chisq'`: Pearson's chi-square method. `'wilson'`: Newcombe-Wilson method. `'farrington_manning'`, `'fm'`: Farrington and Manning's score method. `'miettinen_nurminen'`, `'mn'`: Miettinen and Nurminen's score method. TYPE: `Literal['chisq', 'wilson', 'farrington_manning', 'fm', 'miettinen_nurminen', 'mn']`
`continuity_correction`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'chisq'` or `'wilson'` TYPE: `bool` DEFAULT: `False`

RETURNS	DESCRIPTION
`float`	The confidence interval width or the distance from the proportion difference to the confidence limit. If `interval_type` is `'two-sided'`, the confidence interval width is returned. If `interval_type` is `'lower'` or `'upper'`, the distance from the proportion difference to the confidence limit is returned.

solve_size ¶

solve_size(
    *,
    treatment_proportion: float,
    reference_proportion: float,
    distance: float,
    ratio: float = 1,
    conf_level: float = 0.95,
    interval_type: Literal["two-sided", "lower", "upper"] = "two-sided",
    method: Literal["chisq", "wilson", "farrington_manning", "fm", "miettinen_nurminen", "mn"],
    continuity_correction: bool = False,
) -> tuple[int, int]

Estimate the required sample size.

PARAMETER	DESCRIPTION
`treatment_proportion`	Proportion in the treatment group. TYPE: `float`
`reference_proportion`	Proportion in the reference group. TYPE: `float`
`distance`	Confidence interval width or distance from the proportion to the confidence limit. If `interval_type` = `'two-sided'`, specify the confidence interval width. If `interval_type` = `'lower'` or `'upper'`, specify the distance from the proportion difference to the confidence limit. TYPE: `float`
`ratio`	Ratio of sample sizes in the treatment and reference groups. TYPE: `float` DEFAULT: `1`
`conf_level`	Confidence level. If `interval_type` is `'two-sided'`, specify the two-sided confidence level. If `interval_type` is `'lower'` or `'upper'`, specify the one-sided confidence level. TYPE: `float` DEFAULT: `0.95`
`interval_type`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval. TYPE: `Literal['two-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`method`	The method used to construct the confidence interval. `'chisq'`: Pearson's chi-square method. `'wilson'`: Newcombe-Wilson method. `'farrington_manning'`, `'fm'`: Farrington and Manning's score method. `'miettinen_nurminen'`, `'mn'`: Miettinen and Nurminen's score method. TYPE: `Literal['chisq', 'wilson', 'farrington_manning', 'fm', 'miettinen_nurminen', 'mn']`
`continuity_correction`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'chisq'` or `'wilson'` TYPE: `bool` DEFAULT: `False`

RETURNS	DESCRIPTION
`tuple[int, int]`	The required sample sizes in treatment and reference groups, respectively.

solve_treatment_proportion ¶

solve_treatment_proportion(
    *,
    reference_proportion: float,
    treatment_size: int,
    reference_size: int,
    distance: float,
    conf_level: float = 0.95,
    interval_type: Literal["two-sided", "lower", "upper"] = "two-sided",
    method: Literal["chisq", "wilson", "farrington_manning", "fm", "miettinen_nurminen", "mn"],
    continuity_correction: bool = False,
    direction: Literal["greater", "less"],
) -> float

Estimate the required proportion in the treatment group.

PARAMETER	DESCRIPTION
`reference_proportion`	Proportion in the reference group. TYPE: `float`
`treatment_size`	Sample size in the treatment group. TYPE: `int`
`reference_size`	Sample size in the reference group. TYPE: `int`
`distance`	Confidence interval width or distance from the proportion to the confidence limit. If `interval_type` = `'two-sided'`, specify the confidence interval width. If `interval_type` = `'lower'` or `'upper'`, specify the distance from the proportion difference to the confidence limit. TYPE: `float`
`conf_level`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level is required. If `interval_type` is `'lower'` or `'upper'`, a one-sided confidence level is required. TYPE: `float` DEFAULT: `0.95`
`interval_type`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval. TYPE: `Literal['two-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`method`	The method used to construct the confidence interval. `'chisq'`: Pearson's chi-square method. `'wilson'`: Newcombe-Wilson method. `'farrington_manning'`, `'fm'`: Farrington and Manning's score method. `'miettinen_nurminen'`, `'mn'`: Miettinen and Nurminen's score method. TYPE: `Literal['chisq', 'wilson', 'farrington_manning', 'fm', 'miettinen_nurminen', 'mn']`
`continuity_correction`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'chisq'` or `'wilson'` TYPE: `bool` DEFAULT: `False`
`direction`	Controls which of the two potential solutions for the treatment proportion is selected. Since the confidence interval distance constraint typically yields two valid roots, this parameter determines whether to return the higher or lower proportion. `'greater'`: Returns the larger (higher) of the two treatment proportion solutions. `'less'`: Returns the smaller (lower) of the two treatment proportion solutions. TYPE: `Literal['greater', 'less']`

RETURNS	DESCRIPTION
`float`	The required proportion in the treatment group.

RAISES	DESCRIPTION
`SolutionNotFoundError`	If the solution cannot be found.

solve_reference_proportion ¶

solve_reference_proportion(
    *,
    treatment_proportion: float,
    treatment_size: int,
    reference_size: int,
    distance: float,
    conf_level: float = 0.95,
    interval_type: Literal["two-sided", "lower", "upper"] = "two-sided",
    method: Literal["chisq", "wilson", "farrington_manning", "fm", "miettinen_nurminen", "mn"],
    continuity_correction: bool = False,
    direction: Literal["greater", "less"],
) -> float

Estimate the required proportion in the reference group.

PARAMETER	DESCRIPTION
`treatment_proportion`	Proportion in the treatment group. TYPE: `float`
`treatment_size`	Sample size in the treatment group. TYPE: `int`
`reference_size`	Sample size in the reference group. TYPE: `int`
`distance`	Confidence interval width or distance from the proportion to the confidence limit. If `interval_type` = `'two-sided'`, specify the confidence interval width. If `interval_type` = `'lower'` or `'upper'`, specify the distance from the proportion difference to the confidence limit. TYPE: `float`
`conf_level`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level is required. If `interval_type` is `'lower'` or `'upper'`, a one-sided confidence level is required. TYPE: `float` DEFAULT: `0.95`
`interval_type`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval. TYPE: `Literal['two-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`method`	The method used to construct the confidence interval. `'chisq'`: Pearson's chi-square method. `'wilson'`: Newcombe-Wilson method. `'farrington_manning'`, `'fm'`: Farrington and Manning's score method. `'miettinen_nurminen'`, `'mn'`: Miettinen and Nurminen's score method. TYPE: `Literal['chisq', 'wilson', 'farrington_manning', 'fm', 'miettinen_nurminen', 'mn']`
`continuity_correction`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'chisq'` or `'wilson'` TYPE: `bool` DEFAULT: `False`
`direction`	Controls which of the two potential solutions for the reference proportion is selected. Since the confidence interval distance constraint typically yields two valid roots, this parameter determines whether to return the higher or lower proportion. `'greater'`: Returns the larger (higher) of the two reference proportion solutions. `'less'`: Returns the smaller (lower) of the two reference proportion solutions. TYPE: `Literal['greater', 'less']`

RETURNS	DESCRIPTION
`float`	The required proportion in the reference group.

RAISES	DESCRIPTION
`SolutionNotFoundError`	If the solution cannot be found.