pystatpower.proportion.single.ci ¶

Functions:

Name	Description
`solve_distance`	Calculate the width of the confidence interval for a single-group proportion (two-sided confidence interval),
`solve_size`	Estimate the required sample size for a single-group proportion confidence interval.
`solve_proportion`	Estimate the required proportion for a single-group proportion confidence interval.

solve_distance ¶

solve_distance(
    *,
    proportion: float,
    size: int,
    conf_level: float = 0.95,
    interval_type: Literal[
        "two-sided", "lower", "upper"
    ] = "two-sided",
    method: Literal[
        "wald", "wilson", "clopper-pearson", "cp"
    ] = "cp",
    continuity_correction: bool = False,
) -> float

Calculate the width of the confidence interval for a single-group proportion (two-sided confidence interval), or the distance from the proportion to the confidence limit (lower or upper one-sided confidence interval).

Parameters:

Name	Type	Description	Default
`proportion`	`float`	Proportion.	required
`size`	`int`	Sample size.	required
`conf_level`	`float`	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.	`0.95`
`interval_type`	`Literal['two-sided', 'lower', 'upper']`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval.	`'two-sided'`
`method`	`Literal['wald', 'wilson', 'clopper-pearson', 'cp']`	The method used to construct the confidence interval. `'wald'`: Wald method. `'wilson'`: Wilson method. `'clopper-pearson'`, `'cp'`: Clopper-Pearson method.	`'cp'`
`continuity_correction`	`bool`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'wald'` or `'wilson'`	`False`

Returns:

Name	Type	Description
`float`	`float`	The confidence interval width (two-sided confidence interval), or the distance from the proportion to the confidence limit (lower or upper one-sided confidence interval).

solve_size ¶

solve_size(
    *,
    proportion: float,
    distance: float,
    conf_level: float = 0.95,
    interval_type: Literal[
        "two-sided", "lower", "upper"
    ] = "two-sided",
    method: Literal[
        "wald", "wilson", "clopper-pearson", "cp"
    ] = "cp",
    continuity_correction: bool = False,
) -> int

Estimate the required sample size for a single-group proportion confidence interval.

For two-sided confidence interval, the confidence interval width needs to be given.

For one-sided confidence interval, the distance from the proportion to the confidence limit needs to be given.

Parameters:

Name	Type	Description	Default
`proportion`	`float`	Proportion.	required
`distance`	`float`	If `interval_type` is `'two-sided'`, a confidence interval width is required. If `interval_type` is `'lower'` or `'upper'`, a distance from the proportion to the confidence limit is required.	required
`conf_level`	`float`	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.	`0.95`
`interval_type`	`Literal['two-sided', 'lower', 'upper']`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval.	`'two-sided'`
`method`	`Literal['wald', 'wilson', 'clopper-pearson', 'cp']`	The method used to construct the confidence interval. `'wald'`: Wald method. `'wilson'`: Wilson method. `'clopper-pearson'`, `'cp'`: Clopper-Pearson method.	`'cp'`
`continuity_correction`	`bool`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'wald'` or `'wilson'`	`False`

Returns:

Name	Type	Description
`int`	`int`	The required sample size.

solve_proportion ¶

solve_proportion(
    *,
    size: int,
    distance: float,
    conf_level: float = 0.95,
    interval_type: Literal[
        "two-sided", "lower", "upper"
    ] = "two-sided",
    method: Literal[
        "wald", "wilson", "clopper-pearson", "cp"
    ] = "cp",
    continuity_correction: bool = False,
    direction: Literal["greater", "less"] = "greater",
) -> float

Estimate the required proportion for a single-group proportion confidence interval.

For two-sided confidence interval, the confidence interval width needs to be given.

For one-sided confidence interval, the distance from the proportion to the confidence limit needs to be given.

Parameters:

Name	Type	Description	Default
`size`	`int`	Sample size.	required
`distance`	`float`	If `interval_type` is `'two-sided'`, a confidence interval width is required. If `interval_type` is `'lower'` or `'upper'`, a distance from the proportion to the confidence limit is required.	required
`conf_level`	`float`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level should is required. If `interval_type` is `'lower'` or `'upper'`, a one-sided confidence level is required.	`0.95`
`interval_type`	`Literal['two-sided', 'lower', 'upper']`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval.	`'two-sided'`
`method`	`Literal['wald', 'wilson', 'clopper-pearson', 'cp']`	The method used to construct the confidence interval. `'wald'`: Wald method. `'wilson'`: Wilson method. `'clopper-pearson'`, `'cp'`: Clopper-Pearson method.	`'cp'`
`continuity_correction`	`bool`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'wald'` or `'wilson'`	`False`
`direction`	`Literal['greater', 'less']`	The search direction for the proportion relative to the 0.5. `'greater'`: Search for the proportion greater than 0.5. `'less'`: Search for the proportion less than 0.5.	`'greater'`

Returns:

Name	Type	Description
`float`	`float`	The required proportion.