R: Set up a compact letter display of all pair-wise comparisons
cld
R Documentation
Set up a compact letter display of all pair-wise comparisons
Description
Extract information from glht, summary.glht or
confint.glht objects which is required to create
and plot compact letter displays of all pair-wise comparisons.
Usage
## S3 method for class 'summary.glht'
cld(object, level = 0.05, decreasing = FALSE, ...)
## S3 method for class 'glht'
cld(object, level = 0.05, decreasing = FALSE, ...)
## S3 method for class 'confint.glht'
cld(object, decreasing = FALSE, ...)
Arguments
object
An object of class glht, summary.glht or confint.glht.
level
Significance-level to be used to term a specific pair-wise
comparison significant.
decreasing
logical. Should the order of the letters be increasing or decreasing?
...
additional arguments.
Details
This function extracts all the information from glht,
summary.glht or confint.glht objects that is required
to create a compact letter display of all pair-wise comparisons.
In case the contrast matrix is not of type "Tukey", an error
is issued. In case of confint.glht objects, a pair-wise comparison
is termed significant whenever a particular confidence interval contains 0.
Otherwise, p-values are compared to the value of "level".
Once, this information is extracted, plotting of all pair-wise
comparisons can be carried out.
Value
An object of class cld, a list with items:
y
Values of the response variable of the original model.
yname
Name of the response variable.
x
Values of the variable used to compute Tukey contrasts.
weights
Weights used in the fitting process.
lp
Predictions from the fitted model.
covar
A logical indicating whether the fitted model contained covariates.
signif
Vector of logicals indicating significant differences with
hyphenated names that identify pair-wise comparisons.
References
Hans-Peter Piepho (2004), An Algorithm for a Letter-Based
Representation of All-Pairwise Comparisons, Journal of
Computational and Graphical Statistics, 13(2), 456–466.
See Also
glhtplot.cld
Examples
### multiple comparison procedures
### set up a one-way ANOVA
data(warpbreaks)
amod <- aov(breaks ~ tension, data = warpbreaks)
### specify all pair-wise comparisons among levels of variable "tension"
tuk <- glht(amod, linfct = mcp(tension = "Tukey"))
### extract information
tuk.cld <- cld(tuk)
### use sufficiently large upper margin
old.par <- par(mai=c(1,1,1.25,1), no.readonly = TRUE)
### plot
plot(tuk.cld)
par(old.par)
### now using covariates
data(warpbreaks)
amod2 <- aov(breaks ~ tension + wool, data = warpbreaks)
### specify all pair-wise comparisons among levels of variable "tension"
tuk2 <- glht(amod2, linfct = mcp(tension = "Tukey"))
### extract information
tuk.cld2 <- cld(tuk2)
### use sufficiently large upper margin
old.par <- par(mai=c(1,1,1.25,1), no.readonly = TRUE)
### plot using different colors
plot(tuk.cld2, col=c("black", "red", "blue"))
par(old.par)
### set up all pair-wise comparisons for count data
data(Titanic)
mod <- glm(Survived ~ Class, data = as.data.frame(Titanic), weights = Freq, family = binomial())
### specify all pair-wise comparisons among levels of variable "Class"
glht.mod <- glht(mod, mcp(Class = "Tukey"))
### extract information
mod.cld <- cld(glht.mod)
### use sufficiently large upper margin
old.par <- par(mai=c(1,1,1.5,1), no.readonly = TRUE)
### plot
plot(mod.cld)
par(old.par)