power_binomial: Power Calculation for the Chi-Square Test

In goseberg/samplesizr: Sample-size calculation made simple

Description

power_chisq performs the power calculation for two independent samples with binary data using the absolute rate difference quantifying the effect of an intervention. The method used here is based on the pages 21 - 26 in [1].

Usage

power_binomial(p_Y, p_X, n_Y, n_X, alpha, power.exact)

Arguments

p_Y	Event rate of group Y on the alternative.
p_X	Event rate of group X on the alternative.
n_Y	Sample size of group Y.
n_X	Sample size of group X.
alpha	Significance level α.
power.exact	If set to FALSE an approximative distributive is used for calculating the power, given the alternative distribution at the bottom of p. 22 in [1]. On TRUE the iterative approach is used.

Details

[1] M.Kieser: Fallzahlberechnung in der medizinischen Forschung [2018], 1th Edition

Value

power_binomial returns the power.

Examples

power_binomial(p_Y = .5, p_X = .3, n_Y = 100, n_X = 50, alpha = .05, power.exact = TRUE)

goseberg/samplesizr documentation built on May 28, 2019, 8:43 a.m.