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 summary.glht tidy(x, ...)
x | A |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
tidy()
, multcomp::summary.glht()
, multcomp::glht()
Other multcomp tidiers:
tidy.cld()
,
tidy.confint.glht()
,
tidy.glht()
A tibble::tibble()
with columns:
Levels being compared.
The estimated value of the regression term.
Value to which the estimate is compared.
The two-sided p-value associated with the observed statistic.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
The standard error of the regression term.
if (requireNamespace("multcomp", quietly = TRUE)) { library(multcomp) library(ggplot2) amod <- aov(breaks ~ wool + tension, data = warpbreaks) wht <- glht(amod, linfct = mcp(tension = "Tukey")) tidy(wht) ggplot(wht, aes(lhs, estimate)) + geom_point() CI <- confint(wht) tidy(CI) ggplot(CI, aes(lhs, estimate, ymin = lwr, ymax = upr)) + geom_pointrange() tidy(summary(wht)) 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 × 2 #> tension letters #> <chr> <chr> #> 1 L b #> 2 M a #> 3 H a