Tidy a(n) cld 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 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 cld
tidy(x, ...)

Arguments

x

A cld object created by calling multcomp::cld() on a glht, confint.glht() or summary.glht() object.

...

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

tidy(), multcomp::cld(), multcomp::summary.glht(), multcomp::confint.glht(), multcomp::glht()

Other multcomp tidiers: tidy.confint.glht(), tidy.glht(), tidy.summary.glht()

Value

A tibble::tibble() with columns:

lhs

Left hand side.

Examples

library(multcomp)
#> Loading required package: mvtnorm
#> 
#> Attaching package: ‘mvtnorm’
#> The following object is masked from ‘package:mclust’:
#> 
#>     dmvnorm
#> Loading required package: TH.data
#> 
#> Attaching package: ‘TH.data’
#> The following object is masked from ‘package:MASS’:
#> 
#>     geyser
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.      -19.3    -0.651
#> 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 0.0336 
#> 2 H - L     0   -14.7       3.87     -3.80 0.00112
#> 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