Tidy a(n) glht object

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 glht
tidy(x, conf.int = FALSE, conf.level = 0.95, ...)

Arguments

x	A `glht` object returned by `multcomp::glht()`.
conf.int	Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to `FALSE`.
conf.level	The confidence level to use for the confidence interval if `conf.int = TRUE`. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.
...	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.level = 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.

Value

A tibble::tibble() with columns:

contrast

Levels being compared.

estimate

The estimated value of the regression term.

null.value

Value to which the estimate is compared.

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 7
#>   term    contrast null.value estimate std.error statistic adj.p.value
#>   <chr>   <chr>         <dbl>    <dbl>     <dbl>     <dbl>       <dbl>
#> 1 tension M - L             0   -10.        3.87     -2.58     0.0336 
#> 2 tension H - L             0   -14.7       3.87     -3.80     0.00110
#> 3 tension H - M             0    -4.72      3.87     -1.22     0.447  
ggplot(wht, aes(lhs, estimate)) +
  geom_point()

CI <- confint(wht)
tidy(CI)
#> # A tibble: 3 x 5
#>   term    contrast estimate conf.low conf.high
#>   <chr>   <chr>       <dbl>    <dbl>     <dbl>
#> 1 tension M - L      -10.      -19.3    -0.651
#> 2 tension H - L      -14.7     -24.1    -5.37 
#> 3 tension H - M       -4.72    -14.1     4.63 
ggplot(CI, aes(lhs, estimate, ymin = lwr, ymax = upr)) +
  geom_pointrange()

tidy(summary(wht))
#> # A tibble: 3 x 7
#>   term    contrast null.value estimate std.error statistic adj.p.value
#>   <chr>   <chr>         <dbl>    <dbl>     <dbl>     <dbl>       <dbl>
#> 1 tension M - L             0   -10.        3.87     -2.58     0.0336 
#> 2 tension H - L             0   -14.7       3.87     -3.80     0.00110
#> 3 tension 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
#>   tension letters
#>   <chr>   <chr>  
#> 1 L       b      
#> 2 M       a      
#> 3 H       a

Arguments

See also

Value

Examples