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 across 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, ...)
x | A |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
Other htest tidiers:
augment.htest()
,
tidy.htest()
,
tidy.pairwise.htest()
A tibble::tibble()
with columns:
True difference in means.
Number of observations by component.
Power achieved for given value of n.
Standard deviation.
Significance level (Type I error probability).
ptt <- power.t.test(n = 2:30, delta = 1) tidy(ptt) #> # A tibble: 29 × 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()