designFreqZ | R Documentation |
Computes the number of samples necessary to reach a tolerable type I and type II error for the frequentist z-test.
designFreqZ( meanDiffMin, alternative = c("twoSided", "greater", "less"), alpha = 0.05, beta = 0.2, testType = c("oneSample", "paired", "twoSample"), ratio = 1, sigma = 1, h0 = 0, kappa = sigma, lowN = 3L, highN = 100L, ... )
meanDiffMin |
numeric that defines the minimal relevant mean difference, the smallest population mean that we would like to detect. |
alternative |
a character string specifying the alternative hypothesis must be one of "twoSided" (default), "greater" or "less". |
alpha |
numeric in (0, 1) that specifies the tolerable type I error control –independent on n– that the designed test has to adhere to. Note that it also defines the rejection rule e10 > 1/alpha. |
beta |
numeric in (0, 1) that specifies the tolerable type II error control necessary to calculate both "n" and "phiS". Note that 1-beta defines the power. |
testType |
either one of "oneSample", "paired", "twoSample". |
ratio |
numeric > 0 representing the randomisation ratio of condition 2 over condition 1. If testType is not equal to "twoSample", or if nPlan is of length(1) then ratio=1. |
sigma |
numeric > 0 representing the assumed population standard deviation used for the test. |
h0 |
numeric, represents the null hypothesis, default h0=0. |
kappa |
the true population standard deviation. Default kappa=sigma. |
lowN |
integer that defines the smallest n of our search space for n. |
highN |
integer that defines the largest n of our search space for n. This might be the largest n that we are able to fund. |
... |
further arguments to be passed to or from methods. |
returns a 'freqZDesign' object.
freqDesign <- designFreqZ(meanDiffMin = 0.5, highN = 100) freqDesign$nPlan freqDesign2 <- designFreqZ(meanDiffMin = 0.2, lowN = 32, highN = 200) freqDesign2$nPlan
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