Summarise a randomised clinical trial design that assumes a Bernoulli distributed primary outcome variable

summary.ph2rand_des prints a summary of a design returned by des_one_stage or des_two_stage.

# S3 method for ph2rand_des
summary(object, ...)

Arguments

object	An object of class ph2rand_des, as returned by des_one_stage or des_two_stage.
...	Not currently used.

Value

Currently not used.

See also

des_one_stage, des_two_stage, plot.ph2rand_des.

Examples

# The default two-stage design
des <- des_two_stage()
# Print a summary
summary(des)
#>   -------------------------------------------------
#>   A two-stage trial based on an exact binomial test
#>   -------------------------------------------------
#> 
#>   ---------------
#>   Hypothesis test
#>   ---------------
#>   You have chosen to test the following hypothesis
#>     H0 : piE <= piC
#>   with the following type-I error constraint
#>     P(0.1,0.1) <= alpha = 0.1
#>   and the following type-II error constraint
#>     P(0.1,0.3) >= 1 - beta = 0.8
#> 
#>   -----------------
#>   Design parameters
#>   -----------------
#>   The design has:
#>     - n1C = 17
#>     - n2C = 17
#>     - n1E = 17
#>     - n2E = 17
#>     - e1 = Inf
#>     - f1 = 0
#>     - e2 = 4
#> 
#>   -------------------------
#>   Operating Characteristics
#>   -------------------------
#>   Key operating characteristics include
#> # A tibble: 2 x 10
#>     piC   piE `P(pi)` `ESS(pi)` `SDSS(pi)` `MSS(pi)` `E1(pi)` `E2(pi)` `F1(pi)`
#>   <dbl> <dbl>   <dbl>     <dbl>      <dbl>     <dbl>    <dbl>    <dbl>    <dbl>
#> 1   0.1   0.1  0.0702      47.0       16.5        34        0   0.0702   0.617 
#> 2   0.1   0.3  0.813       64.7       10.1        68        0   0.813    0.0972
#> # … with 1 more variable: `F2(pi)` <dbl>