| facCombine.alldiffs {asremlPlus} | R Documentation |
Combines several factors into one in the components of an alldiffs.object
Description
Combines several factors, in the prediction component
of object, into one whose levels are the combinations of the
used levels of the individual factors. The matching
changes are made to the other components and the attributes of the
alldiffs.object. If any of the factors to be combined are in
LSDby, they are removed from the LSDby, unless the factors to
be combined are exactly those in the LSDby.
The levels of the factors are combined using fac.combine
from the dae package.
Usage
## S3 method for class 'alldiffs'
facCombine(object, factors, order="standard",
combine.levels=TRUE, sep="_", level.length = NA, ...)
Arguments
object |
An |
factors |
A |
order |
Either |
combine.levels |
A |
sep |
A |
level.length |
The maximum number of characters from the levels of factors to use in the row and column labels of the tables of pairwise differences and their p-values and standard errors. |
... |
Further arguments passed to |
Value
A modified alldiffs.object.
Author(s)
Chris Brien
See Also
as.alldiffs, allDifferences.data.frame,
print.alldiffs, sort.alldiffs,
renewClassify.alldiffs; fac.combine in package dae.
Examples
data("Ladybird.dat")
## Use asreml to get predictions and associated statistics
## Not run:
m1.asr <- asreml(logitP ~ Host*Cadavers*Ladybird,
random = ~ Run,
data = Ladybird.dat)
current.asrt <- as.asrtests(m1.asr)
HCL.pred <- asreml::predict.asreml(m1.asr, classify="Host:Cadavers:Ladybird",
sed=TRUE)
HCL.preds <- HCL.pred$pvals
HCL.sed <- HCL.pred$sed
HCL.vcov <- NULL
wald.tab <- current.asrt$wald.tab
den.df <- wald.tab[match("Host:Cadavers:Ladybird", rownames(wald.tab)), "denDF"]
## End(Not run)
## Use lmeTest and emmmeans to get predictions and associated statistics
if (requireNamespace("lmerTest", quietly = TRUE) &
requireNamespace("emmeans", quietly = TRUE))
{
m1.lmer <- lmerTest::lmer(logitP ~ Host*Cadavers*Ladybird + (1|Run),
data=Ladybird.dat)
HCL.emm <- emmeans::emmeans(m1.lmer, specs = ~ Host:Cadavers:Ladybird)
HCL.preds <- summary(HCL.emm)
den.df <- min(HCL.preds$df)
## Modify HCL.preds to be compatible with a predictions.frame
HCL.preds <- as.predictions.frame(HCL.preds, predictions = "emmean",
se = "SE", interval.type = "CI",
interval.names = c("lower.CL", "upper.CL"))
HCL.vcov <- vcov(HCL.emm)
HCL.sed <- NULL
}
## Use the predictions obtained with either asreml or lmerTest
if (exists("HCL.preds"))
{
## Form an all.diffs object
HCL.diffs <- as.alldiffs(predictions = HCL.preds, classify = "Host:Cadavers:Ladybird",
sed = HCL.sed, vcov = HCL.vcov, tdf = den.df)
## Check the class and validity of the alldiffs object
is.alldiffs(HCL.diffs)
validAlldiffs(HCL.diffs)
## Combine Cadavers and Ladybird
HCL.diffs <- facCombine(HCL.diffs, factors = c("Cadavers","Ladybird"))
## Check the validity of HCL.diffs
validAlldiffs(HCL.diffs)
}