Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

# S3 method for binDesign
tidy(x, ...)

## Arguments

x A binGroup::binDesign() object. Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

## See also

tidy(), binGroup::binDesign()

Other bingroup tidiers: glance.binDesign(), tidy.binWidth()

## Value

A tibble::tibble() with columns:

n

Number of trials in given iteration.

power

Power achieved for given value of n.

## Examples


library(binGroup)
des <- binDesign(nmax = 300, delta = 0.06,
p.hyp = 0.1, power = .8)

glance(des)#> # A tibble: 1 x 4
#>   power     n power.reached maxit
#>   <dbl> <int> <lgl>         <int>
#> 1 0.805   240 TRUE            238tidy(des)#> # A tibble: 238 x 2
#>        n     power
#>    <int>     <dbl>
#>  1     3 0.000064
#>  2     4 0.000248
#>  3     5 0.000602
#>  4     6 0.00117
#>  5     7 0.0000813
#>  6     8 0.000157
#>  7     9 0.000274
#>  8    10 0.000443
#>  9    11 0.000673
#> 10    12 0.0000640
#> # … with 228 more rows
# the ggplot2 equivalent of plot(des)
library(ggplot2)
ggplot(tidy(des), aes(n, power)) +
geom_line()