Get Fixed Design

Create a fixed (single-stage) trial design. This convenience wrapper constructs an object of class TrialDesignFixed with kMax = 1.

Usage

getDesignFixed(
  alpha = 0.025,
  beta = 0.2,
  sided = 1L,
  directionUpper = NA,
  twoSidedPower = NA
)

Arguments

alpha

The significance level alpha, default is 0.025. Must be a positive numeric of length 1.

beta

Type II error rate, necessary for providing sample size calculations (e.g., getSampleSizeMeans()), beta spending function designs, or optimum designs, default is 0.20. Must be a positive numeric of length 1.

sided

Is the alternative one-sided (1) or two-sided (2), default is 1. Must be a positive integer of length 1.

directionUpper

Logical. Specifies the direction of the alternative, only applicable for one-sided testing; default is TRUE which means that larger values of the test statistics yield smaller p-values.

twoSidedPower

For two-sided testing, if twoSidedPower = TRUE is specified the sample size calculation is performed by considering both tails of the distribution. Default is FALSE, i.e., it is assumed that one tail probability is equal to 0 or the power should be directed to one part.#'

Value

Returns a TrialDesign object. The following generics (R generic functions) are available for this result object:

• names() to obtain the field names,

• print() to print the object,

• summary() to display a summary of the object,

• plot() to plot the object,

• as.data.frame() to coerce the object to a data.frame,

• as.matrix() to coerce the object to a matrix.

Details

The fixed design represents a single-stage hypothesis test. The returned object can be used with the standard analysis and plotting helpers in the package. Typical use is to specify the type I error alpha and the desired type II error beta (or equivalently power = 1 - beta).

See also

Other design functions: getDesignCharacteristics(), getDesignConditionalDunnett(), getDesignFisher(), getDesignGroupSequential(), getDesignInverseNormal(), getGroupSequentialProbabilities(), getPowerAndAverageSampleNumber()

Examples

# Basic fixed design with default alpha and beta
design <- getDesignFixed()
design
#> Design parameters and output of fixed sample size design:
#> 
#> User defined parameters: not available
#> 
#> Derived from user defined parameters: not available
#> 
#> Default parameters:
#>   Significance level              : 0.0250 
#>   Type II error rate              : 0.2000 
#>   Test                            : one-sided 
#> 
#> Output:
#>   Critical values                 : 1.960 
#>   Stage levels (one-sided)        : 0.0250 
#> 

# Custom significance and power
design2 <- getDesignFixed(alpha = 0.05, beta = 0.1)
design2
#> Design parameters and output of fixed sample size design:
#> 
#> User defined parameters:
#>   Significance level              : 0.0500 
#>   Type II error rate              : 0.1000 
#> 
#> Derived from user defined parameters: not available
#> 
#> Default parameters:
#>   Test                            : one-sided 
#> 
#> Output:
#>   Critical values                 : 1.645 
#>   Stage levels (one-sided)        : 0.0500 
#>