power_ztest: Power calculation for the two-sided z-Test
In goseberg/samplesizr: Sample-size calculation made simple
Description
Usage
Arguments
Details
Value
Examples
Description
n_ztest performs the power calculation for the z-Test
to the level α comparing two independent samples.
The method is based on the pages 13 - 16 in [1].
Usage
1
power_ztest(effect, sd, n_X, alpha, r = 1)
Arguments
effect
Effect Δ_A used as alternative hypothesis.
sd
Standard deviation σ.
n_X
Sample size of group X.
alpha
Significance level α.
r
Default = 1. Quotient of Group sizes r = n_Y / n_X.
Details
[1] M.Kieser: Fallzahlberechnung in der medizinischen Forschung [2018], 1th Edition
Value
n_ztest returns the power.
Examples
1
power_ztest(effect = 10, sd = 20, n_X = 70, alpha = .05)
goseberg/samplesizr documentation built on May 28, 2019, 8:43 a.m.
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Description Usage Arguments Details Value Examples
Description
n_ztest performs the power calculation for the z-Test
to the level α comparing two independent samples.
The method is based on the pages 13 - 16 in [1].
Usage
1 | power_ztest(effect, sd, n_X, alpha, r = 1)
|
Arguments
effect |
Effect Δ_A used as alternative hypothesis. |
sd |
Standard deviation σ. |
n_X |
Sample size of group X. |
alpha |
Significance level α. |
r |
Default = 1. Quotient of Group sizes r = n_Y / n_X. |
Details
[1] M.Kieser: Fallzahlberechnung in der medizinischen Forschung [2018], 1th Edition
Value
n_ztest returns the power.
Examples
1 | power_ztest(effect = 10, sd = 20, n_X = 70, alpha = .05)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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