designFreqT {safestats}

Design a Frequentist T-Test

Description

Computes the number of samples necessary to reach a tolerable type I and type II error for the frequentist t-test.

Usage

designFreqT(
  deltaMin,
  alpha = 0.05,
  beta = 0.2,
  alternative = c("twoSided", "greater", "less"),
  h0 = 0,
  testType = c("oneSample", "paired", "twoSample"),
  ...
)

Arguments

deltaMin

numeric that defines the minimal relevant standardised effect size, the smallest effect size that we would the experiment to be able to detect.

alpha

numeric in (0, 1) that specifies the tolerable type I error control –independent of 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 the sample sizes and deltaS, which defines the test. Note that 1-beta defines the power.

alternative

a character string specifying the alternative hypothesis must be one of "twoSided" (default), "greater" or "less".

h0

a number indicating the hypothesised true value of the mean under the null. For the moment h0=0.

testType

either one of "oneSample", "paired", "twoSample".

...

further arguments to be passed to or from methods, but mainly to perform do.calls.

Value

Returns an object of class 'freqTDesign'. An object of class 'freqTDesign' is a list containing at least the following components:

nPlan

the planned sample size(s).

esMin

the minimal clinically relevant standardised effect size provided by the user.

alpha

the tolerable type I error provided by the user.

beta

the tolerable type II error provided by the user.

lowN

the smallest n of the search space for n provided by the user.

highN

the largest n of the search space for n provided by the user.

testType

any of "oneSample", "paired", "twoSample" provided by the user.

alternative

any of "twoSided", "greater", "less" provided by the user.

Examples

designFreqT(0.5)