facCombine.alldiffs | R Documentation |
alldiffs.object
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.
## S3 method for class 'alldiffs'
facCombine(object, factors, order="standard",
combine.levels=TRUE, sep="_", level.length = NA, ...)
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 |
A modified alldiffs.object
.
Chris Brien
as.alldiffs
, allDifferences.data.frame
,
print.alldiffs
, sort.alldiffs
,
renewClassify.alldiffs
; fac.combine
in package dae.
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)
}
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