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One-stage designs

Source: R/OneStageDesign.R
OneStageDesign-class.Rd

OneStageDesign implements a one-stage design as special case of a two-stage design, i.e. as sub-class of TwoStageDesign. This is possible by defining n2 = 0, c = c1f = c1e, c2(x1) = ifelse(x1NaN).

Usage

OneStageDesign(n, ...)

# S4 method for class 'numeric'
OneStageDesign(n, c, event_rate)

# S4 method for class 'OneStageDesign'
TwoStageDesign(n1, event_rate, order = 5L, eps = 0.01, ...)

# S4 method for class 'OneStageDesignSurvival'
TwoStageDesign(n1, order = 5L, eps = 0.01, ...)

# S4 method for class 'OneStageDesign'
plot(x, y, ...)

Arguments

n

sample size (stage-one sample size)

...

further optional arguments

c

rejection boundary (c = c1f = c1e)

event_rate

probability that a subject in either group will eventually have an event, only needs to be specified for time-to-event endpoints.

n1

OneStageDesign object to convert, overloaded from TwoStageDesign

order

integer >= 2, default is 5; order of Gaussian quadrature integration rule to use for new TwoStageDesign.

eps

numeric > 0, default = .01; the single critical value c must be split in a continuation interval [c1f, c1e]; this is given by c +/- eps.

x

design to plot

y

not used

Details

Note that the default plot,TwoStageDesign-method method is not supported for OneStageDesign objects.

See also

TwoStageDesign, GroupSequentialDesign-class

Examples

design <- OneStageDesign(30, 1.96)
summary(design)
#> OneStageDesign: n1 =  30 
#> 
          futility | continue | efficacy
#> 
      x1:     1.96 |   NaN |  1.96
#> 
  c2(x1):     +Inf |    NA |  -Inf
#> 
  n2(x1):        0 |     0 |     0
#> 

design_twostage <- TwoStageDesign(design)
summary(design_twostage)
#> TwoStageDesign: n1 =  30 
#> 
          futility |            continue           | efficacy
#> 
      x1:     1.95 |  1.95  1.95  1.96  1.97  1.97 |  1.97
#> 
  c2(x1):     +Inf | +3.00 +3.00 +0.00 -3.00 -3.00 |  -Inf
#> 
  n2(x1):        0 |     0     0     0     0     0 |     0
#> 

design_survival <- OneStageDesign(30, 1.96, 0.7)

TwoStageDesign(design_survival)
#> TwoStageDesignSurvival<n_events1=30;1.9<=x1<=2.0;n_events2=0>