Translate group sequential design to integer events (survival designs) or sample size (other designs)

Usage

toInteger(x, ratio = 0, roundUpFinal = TRUE)

Arguments

x: An object of class gsDesign or gsSurv.
ratio: A non-negative integer, usually corresponding to experimental:control sample size ratio. Rounding is done to a multiple of ratio + 1. If input x has class gsSurv (design for time-to-event outcome), and x$ratio is a whole number, ratio is replaced by x$ratio. See details.
roundUpFinal: Final value in returned n.I is rounded up if TRUE; otherwise, just rounded. For gsSurv input, final total sample size is also controlled by this. See details.

Value

Output is an object of the same class as input x; i.e., gsDesign with integer vector for n.I

or gsSurv with integer vector n.I and integer total sample size. See details.

Details

If ratio = 3, rounding for final sample size is done to a multiple of 3 + 1 = 4. For a gsSurv object input in x, event counts output in n.I are rounded to nearest integer and final total sample size is rounded to a multiple of ratio + 1. For other input values of x (gsDesign class), n.I is interpreted as sample size; final value is rounded to a multiple of ratio + 1, with roundUpFinal controlling rounding of last value.

Examples

# The following code derives the group sequential design using the method
# of Lachin and Foulkes

x <- gsSurv(
  k = 3,                 # 3 analyses
  test.type = 4,         # Non-binding futility bound 1 (no futility bound) and 4 are allowable
  alpha = .025,          # 1-sided Type I error
  beta = .1,             # Type II error (1 - power)
  timing = c(0.45, 0.7), # Proportion of final planned events at interims
  sfu = sfHSD,           # Efficacy spending function
  sfupar = -4,           # Parameter for efficacy spending function
  sfl = sfLDOF,          # Futility spending function; not needed for test.type = 1
  sflpar = 0,            # Parameter for futility spending function
  lambdaC = .001,        # Exponential failure rate
  hr = 0.3,              # Assumed proportional hazard ratio (1 - vaccine efficacy = 1 - VE)
  hr0 = 0.7,             # Null hypothesis VE
  eta = 5e-04,           # Exponential dropout rate
  gamma = 10,            # Piecewise exponential enrollment rates
  R = 16,                # Time period durations for enrollment rates in gamma
  T = 24,                # Planned trial duration
  minfup = 8,            # Planned minimum follow-up
  ratio = 3              # Randomization ratio (experimental:control)
)
# Convert bounds to exact binomial bounds
toInteger(x, ratio = 3)
#> Time to event group sequential design with HR= 0.3 
#> Non-inferiority design with null HR= 0.7 
#> Randomization (Exp/Control):  ratio= 3 
#> Asymmetric two-sided group sequential design with
#> 90 % power and 2.5 % Type I Error.
#> Upper bound spending computations assume
#> trial continues if lower bound is crossed.
#> 
#>                ----Lower bounds----  ----Upper bounds-----
#>   Analysis N   Z   Nominal p Spend+  Z   Nominal p Spend++
#>          1 31 0.07    0.5277 0.0141 2.83    0.0023  0.0023
#>          2 48 1.11    0.8673 0.0345 2.52    0.0059  0.0047
#>          3 69 2.00    0.9774 0.0514 2.00    0.0226  0.0179
#>      Total                   0.1000                 0.0250 
#> + lower bound beta spending (under H1):
#>  Lan-DeMets O'Brien-Fleming approximation spending function with none = 1.
#> ++ alpha spending:
#>  Hwang-Shih-DeCani spending function with gamma = -4.
#> 
#> Boundary crossing probabilities and expected sample size
#> assume any cross stops the trial
#> 
#> Upper boundary (power or Type I Error)
#>           Analysis
#>    Theta      1      2      3  Total E{N}
#>   0.0000 0.0023 0.0047 0.0159 0.0230 41.5
#>   0.4065 0.2863 0.3402 0.2762 0.9027 49.7
#> 
#> Lower boundary (futility or Type II Error)
#>           Analysis
#>    Theta      1      2      3  Total
#>   0.0000 0.5277 0.3439 0.1054 0.9770
#>   0.4065 0.0141 0.0345 0.0487 0.0973
#>              T        n Events HR futility HR efficacy
#> IA 1  15.22419 8624.502     31       0.680       0.217
#> IA 2  19.23447 9064.000     48       0.483       0.302
#> Final 24.19069 9064.000     69       0.401       0.401
#> Accrual rates:
#>      Stratum 1
#> 0-16     566.5
#> Control event rates (H1):
#>       Stratum 1
#> 0-Inf         0
#> Censoring rates:
#>       Stratum 1
#> 0-Inf         0