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 power.htest
tidy(x, ...)

Arguments

x

A power.htest object such as those returned from stats::power.t.test().

...

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

Needs custom info.

power

Power achieved for given value of n.

Examples

ptt <- power.t.test(n = 2:30, delta = 1) tidy(ptt)
#> # A tibble: 29 x 5 #> n delta sd sig.level power #> <int> <dbl> <dbl> <dbl> <dbl> #> 1 2 1 1 0.05 0.0913 #> 2 3 1 1 0.05 0.157 #> 3 4 1 1 0.05 0.222 #> 4 5 1 1 0.05 0.286 #> 5 6 1 1 0.05 0.347 #> 6 7 1 1 0.05 0.406 #> 7 8 1 1 0.05 0.461 #> 8 9 1 1 0.05 0.513 #> 9 10 1 1 0.05 0.562 #> 10 11 1 1 0.05 0.607 #> # ... with 19 more rows
library(ggplot2) ggplot(tidy(ptt), aes(n, power)) + geom_line()