pystatpower.models.correlation.inequality ¶

Functions:

Name	Description
`solve_power`	Calculate the power of the difference test between two correlation coefficients.
`solve_size`	Estimate the sample size required for the difference test between two correlation coefficients.
`solve_correlation`	Estimate the alternative correlation coefficient required for the difference test between two correlation coefficients.
`solve_null_correlation`	Estimeta the null correlation coefficient required for the difference test between two correlation coefficients.

solve_power ¶

solve_power(*, null_correlation: float, correlation: float, size: float, alpha: float = 0.05, bias_adj: bool = False) -> float

Calculate the power of the difference test between two correlation coefficients.

Parameters:

Name	Type	Description	Default
`null_correlation`	`float`	Correlation coefficient under the null hypothesis.	required
`correlation`	`float`	Correlation coefficient under the alternative hypothesis.	required
`size`	`float`	Sample size.	required
`alpha`	`float`	Significance level. Default is 0.05.	`0.05`
`bias_adj`	`bool`	Specify whether or not the bias adjustment is used. Default is False.	`False`

Returns:

Name	Type	Description
`power`	`float`	Power of the test.

solve_size ¶

solve_size(*, null_correlation: float, correlation: float, alpha: float = 0.05, power: float = 0.8, bias_adj: bool = False) -> float

Estimate the sample size required for the difference test between two correlation coefficients.

Parameters:

Name	Type	Description	Default
`null_correlation`	`float`	Correlation coefficient under the null hypothesis.	required
`correlation`	`float`	Correlation coefficient under the alternative hypothesis.	required
`alpha`	`float`	Significance level. Default is 0.05.	`0.05`
`power`	`float`	Power of the test. Default is 0.80.	`0.8`
`bias_adj`	`bool`	Specify whether or not the bias adjustment is used. Default is False.	`False`

Returns:

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

solve_correlation ¶

solve_correlation(*, null_correlation: float, size: float, alpha: float = 0.05, power: float = 0.8, bias_adj: bool = False, search_direction: str = 'upper') -> float

Estimate the alternative correlation coefficient required for the difference test between two correlation coefficients.

Parameters:

Name	Type	Description	Default
`null_correlation`	`float`	Correlation coefficient under the null hypothesis.	required
`size`	`float`	Sample size.	required
`alpha`	`float`	Significance level. Default is 0.05.	`0.05`
`power`	`float`	Power of the test. Default is 0.80.	`0.8`
`bias_adj`	`bool`	Specify whether or not the bias adjustment is used. Default is False.	`False`
`search_direction`	`str`	Specify the search direction relative to the null correlation. Default is 'upper'.	`'upper'`

Returns:

Name	Type	Description
`correlation`	`float`	The required alternative correlation.

solve_null_correlation ¶

solve_null_correlation(*, correlation: float, size: int, alpha: float = 0.05, power: float = 0.05, bias_adj: bool = False, search_direction: str = 'lower') -> float

Estimeta the null correlation coefficient required for the difference test between two correlation coefficients.

Parameters:

Name	Type	Description	Default
`correlation`	`float`	Correlation coefficient under the alternative hypothesis.	required
`size`	`int`	Sample size.	required
`alpha`	`float`	Significance level. Default is 0.05.	`0.05`
`power`	`float`	Power of the test. Default is 0.05.	`0.05`
`bias_adj`	`bool`	Specify whether or not the bias adjustment is used. Default is False.	`False`
`search_direction`	`str`	Specify the search direction relative to the alternative correlation. Default is 'lower'.	`'lower'`

Returns:

Name	Type	Description
`null_correlation`	`float`	The required null correlation.