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

Source: `R/summary.ph2rand_des.R`
`summary.ph2rand_des.Rd`

`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>