getDesignGroupSequential: Get Design Group Sequential

Description

Provides adjusted boundaries and defines a group sequential design.

Usage

getDesignGroupSequential(
  ...,
  kMax = NA_integer_,
  alpha = NA_real_,
  beta = NA_real_,
  sided = 1,
  informationRates = NA_real_,
  futilityBounds = NA_real_,
  typeOfDesign = C_DEFAULT_TYPE_OF_DESIGN,
  deltaWT = 0,
  optimizationCriterion = C_OPTIMIZATION_CRITERION_DEFAULT,
  gammaA = 1,
  typeBetaSpending = C_TYPE_OF_DESIGN_BS_NONE,
  userAlphaSpending = NA_real_,
  userBetaSpending = NA_real_,
  gammaB = 1,
  bindingFutility = NA,
  constantBoundsHP = C_CONST_BOUND_HP_DEFAULT,
  twoSidedPower = NA,
  tolerance = C_DESIGN_TOLERANCE_DEFAULT
)

Arguments

...

Ensures that all arguments are be named and that a warning will be displayed if unknown arguments are passed.

kMax

The maximum number of stages K. K = 1, 2, 3,..., 10, default is 3.

alpha

The significance level alpha, default is 0.025.

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.

sided

One-sided or two-sided, default is 1.

informationRates

The information rates, default is (1 : kMax)/kMax.

futilityBounds

The futility bounds, defined on the test statistic z scale (vector of length K - 1).

typeOfDesign

The type of design. Type of design is one of the following: O'Brien & Fleming ("OF"), Pocock ("P"), Wang & Tsiatis Delta class ("WT"), Haybittle & Peto ("HP"), Optimum design within Wang & Tsiatis class ("WToptimum"), O'Brien & Fleming type alpha spending ("asOF"), Pocock type alpha spending ("asP"), Kim & DeMets alpha spending ("asKD"), Hwang, Shi & DeCani alpha spending ("asHSD"), user defined alpha spending ("asUser"), default is "OF".

deltaWT

Delta for Wang & Tsiatis Delta class.

optimizationCriterion

Optimization criterion for optimum design within Wang & Tsiatis class ("ASNH1", "ASNIFH1", "ASNsum"), default is "ASNH1".

gammaA

Parameter for alpha spending function, default is 1.

typeBetaSpending

Type of beta spending. Type of of beta spending is one of the following: O'Brien & Fleming type beta spending, Pocock type beta spending, Kim & DeMets beta spending, Hwang, Shi & DeCani beta spending, user defined beta spending ("bsOF", "bsP",...).

userAlphaSpending

The user defined alpha spending. Vector of length kMax containing the cumulative alpha-spending up to each interim stage.

userBetaSpending

The user defined beta spending. Vector of length kMax containing the cumulative beta-spending up to each interim stage.

gammaB

Parameter for beta spending function, default is 1.

bindingFutility

If bindingFutility = TRUE is specified the calculation of the critical values is affected by the futility bounds (default is FALSE).

constantBoundsHP

The constant bounds up to stage K - 1 for the Haybittle & Peto design (default is 3).

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.

tolerance

The tolerance, default is 1e-08.

Value

Returns a TrialDesignGroupSequential object.

Details

Depending on typeOfDesign some parameters are specified, others not. For example, only if typeOfDesign "asHSD" is selected, gammaA needs to be specified.

If an alpha spending approach was specified ("asOF", "asP", "asKD", "asHSD", or "asUser") additionally a beta spending function can be specified to produce futility bounds.

Examples

Run this code

# NOT RUN {
# Run with default values
getDesignGroupSequential() 

# Calculate the Pocock type alpha spending critical values if the second 
# interim analysis was performed after 70% of information was observed
getDesignGroupSequential(informationRates = c(0.4, 0.7), typeOfDesign = "asP") 

# }