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

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 238
tidy(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()