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 TukeyHSD
tidy(x, ...)

Arguments

x

A TukeyHSD object return from stats::TukeyHSD().

...

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:

adj.p.value

P-value adjusted for multiple comparisons.

comparison

Levels being compared.

conf.high

Upper bound on the confidence interval for the estimate.

conf.low

Lower bound on the confidence interval for the estimate.

estimate

The estimated value of the regression term.

Examples

fm1 <- aov(breaks ~ wool + tension, data = warpbreaks) thsd <- TukeyHSD(fm1, "tension", ordered = TRUE) tidy(thsd)
#> # A tibble: 3 x 6 #> term comparison estimate conf.low conf.high adj.p.value #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 tension M-H 4.72 -4.63 14.1 0.447 #> 2 tension L-H 14.7 5.37 24.1 0.00112 #> 3 tension L-M 10. 0.647 19.4 0.0336
# may include comparisons on multiple terms fm2 <- aov(mpg ~ as.factor(gear) * as.factor(cyl), data = mtcars) tidy(TukeyHSD(fm2))
#> # A tibble: 42 x 6 #> term comparison estimate conf.low conf.high adj.p.value #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 as.factor(gear) 4-3 8.43 5.19 11.7 0.00000297 #> 2 as.factor(gear) 5-3 5.27 0.955 9.59 0.0147 #> 3 as.factor(gear) 5-4 -3.15 -7.60 1.30 0.201 #> 4 as.factor(cyl) 6-4 -5.40 -9.45 -1.36 0.00748 #> 5 as.factor(cyl) 8-4 -5.23 -8.60 -1.86 0.00201 #> 6 as.factor(cyl) 8-6 0.172 -3.70 4.04 0.993 #> 7 as.factor(gear):as.factor… 4:4-3:4 5.42 -6.65 17.5 0.832 #> 8 as.factor(gear):as.factor… 5:4-3:4 6.70 -7.24 20.6 0.778 #> 9 as.factor(gear):as.factor… 3:6-3:4 -1.75 -15.7 12.2 1.000 #> 10 as.factor(gear):as.factor… 4:6-3:4 -1.75 -14.5 11.0 1.000 #> # … with 32 more rows