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 confint.glht
tidy(x, ...)

Arguments

x

A confint.glht object created by calling multcomp::confint.glht() on a glht object created with multcomp::glht().

...

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:

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.

lhs

Left hand side.

rhs

Right hand side.

Examples

library(multcomp) library(ggplot2) amod <- aov(breaks ~ wool + tension, data = warpbreaks) wht <- glht(amod, linfct = mcp(tension = "Tukey")) tidy(wht)
#> # A tibble: 3 x 3 #> lhs rhs estimate #> <chr> <dbl> <dbl> #> 1 M - L 0 -10. #> 2 H - L 0 -14.7 #> 3 H - M 0 -4.72
ggplot(wht, aes(lhs, estimate)) + geom_point()
CI <- confint(wht) tidy(CI)
#> # A tibble: 3 x 5 #> lhs rhs estimate conf.low conf.high #> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 M - L 0 -10. -19.4 -0.648 #> 2 H - L 0 -14.7 -24.1 -5.37 #> 3 H - M 0 -4.72 -14.1 4.63
ggplot(CI, aes(lhs, estimate, ymin = lwr, ymax = upr)) + geom_pointrange()
tidy(summary(wht))
#> # A tibble: 3 x 6 #> lhs rhs estimate std.error statistic p.value #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 M - L 0 -10. 3.87 -2.58 0.0335 #> 2 H - L 0 -14.7 3.87 -3.80 0.00115 #> 3 H - M 0 -4.72 3.87 -1.22 0.447
ggplot(mapping = aes(lhs, estimate)) + geom_linerange(aes(ymin = lwr, ymax = upr), data = CI) + geom_point(aes(size = p), data = summary(wht)) + scale_size(trans = "reverse")
cld <- cld(wht) tidy(cld)
#> # A tibble: 3 x 2 #> lhs letters #> <chr> <chr> #> 1 L b #> 2 M a #> 3 H a