Generic print function for class MAMS.

Usage

# S3 method for class 'MAMS'
print(x, digits = max(3, getOption("digits") - 4), ...)

Arguments

x: An output object of class MAMS
digits: Number of significant digits to be printed.
...: Further arguments passed to or from other methods.

Value

Text output.

Details

print produces a brief summary of an object from class MAMS including boundaries and requires sample size if initially requested.

References

Magirr D, Jaki T, Whitehead J (2012) A generalized Dunnett test for multi-arm multi-stage clinical studies with treatment selection. Biometrika, 99(2), 494-501. Stallard N, Todd S (2003) Sequential designs for phase III clinical trials incorporating treatment selection. Statistics in Medicine, 22(5), 689-703. Magirr D, Stallard N, Jaki T (2014) Flexible sequential designs for multi-arm clinical trials. Statistics in Medicine, 33(19), 3269-3279.

Author

Thomas Jaki, Dominic Magirr, Philip Pallmann

Examples

# \donttest{
# 2-stage design with triangular boundaries
res <- mams(K=4, J=2, alpha=0.05, power=0.9, r=1:2, r0=1:2, 
             p=0.65,p0=0.55,
             ushape="triangular", lshape="triangular", nstart=30)
#> 
#>    i) find lower and upper boundaries
#>       
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> 
#>   ii) define alpha star
#>  iii) perform sample size calculation
#>       (maximum iteration number = 259)
#>       
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> .
#> 50
#>       
#> 
#>   iv) run simulation 

print(res)
#> 
#> Design parameters for a 2 stage trial with 4 treatments:
#> 
#>                                             Stage 1 Stage 2
#> Cumulative sample size per stage (control):      50     100
#> Cumulative sample size per stage (active):       50     100
#> 
#> Maximum total sample size:  500 
#> 
#>              Stage 1 Stage 2
#> Upper bound:   2.432   2.293
#> Lower bound:   0.811   2.293
#> 
#> 
#> Simulated error rates based on 50000 simulations:
#>                                                           
#> Prop. rejecting at least 1 hypothesis:               0.934
#> Prop. rejecting first hypothesis (Z_1>Z_2,...,Z_K)   0.901
#> Prop. rejecting hypothesis 1:                        0.920
#> Expected sample size:                              301.581
#> 
# }