pystatpower.proportion.single.equivalence ¶

FUNCTION	DESCRIPTION
`solve_power`	Calculate the statistical power.
`solve_size`	Estimate the required sample size.

solve_power ¶

solve_power(
    *,
    proportion: float,
    null_proportion: float,
    margin_lower: float,
    margin_upper: float,
    size: int,
    alpha: float = 0.025,
    method: Literal["z-p0", "z-phat"] = "z-phat",
    continuity_correction: bool = False,
) -> float

Calculate the statistical power.

PARAMETER	DESCRIPTION
`proportion`	Proportion under the alternative hypothesis. TYPE: `float`
`null_proportion`	Proportion under the null hypothesis. TYPE: `float`
`margin_lower`	The lower equivalence margin, must be a negative value. TYPE: `float`
`margin_upper`	The upper equivalence margin, must be a positive value. TYPE: `float`
`size`	Sample size. TYPE: `int`
`alpha`	Significance level. The equivalence test is a two one-sided test, with a significance level of 0.025 being commonly used. TYPE: `float` DEFAULT: `0.025`
`method`	The method used to construct the test statistic. `'z-p0'`: Standard normal distribution (large sample approximation), using p0 to calculate the variance. `'z-phat'`: Standard normal distribution (large sample approximation), using phat to calculate the variance. TYPE: `Literal['z-p0', 'z-phat']` DEFAULT: `'z-phat'`
`continuity_correction`	Whether to apply the continuity correction. TYPE: `bool` DEFAULT: `False`

RETURNS	DESCRIPTION
`float`	The statistical power of the test.

solve_size ¶

solve_size(
    *,
    proportion: float,
    null_proportion: float,
    margin_lower: float,
    margin_upper: float,
    alpha: float = 0.025,
    power: float = 0.8,
    method: Literal["z-p0", "z-phat"] = "z-phat",
    continuity_correction: bool = False,
) -> int

Estimate the required sample size.

PARAMETER	DESCRIPTION
`proportion`	Proportion under the alternative hypothesis. TYPE: `float`
`null_proportion`	Proportion under the null hypothesis. TYPE: `float`
`margin_lower`	The lower equivalence margin, must be a negative value. TYPE: `float`
`margin_upper`	The upper equivalence margin, must be a positive value. TYPE: `float`
`alpha`	Significance level. The equivalence test is a two one-sided test, with a significance level of 0.025 being commonly used. TYPE: `float` DEFAULT: `0.025`
`power`	Expected statistical power. 0.8 is a commonly used value for statistical power. TYPE: `float` DEFAULT: `0.8`
`method`	The method used to construct the test statistic. `'z-p0'`: Standard normal distribution (large sample approximation), using p0 to calculate the variance. `'z-phat'`: Standard normal distribution (large sample approximation), using phat to calculate the variance. TYPE: `Literal['z-p0', 'z-phat']` DEFAULT: `'z-phat'`
`continuity_correction`	Whether to apply the continuity correction. TYPE: `bool` DEFAULT: `False`

RETURNS	DESCRIPTION
`int`	The required sample size.