data("Ladybird.dat")
## Use asreml to get predictions and associated statistics
if (FALSE) {
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$wald.tab
den.df <- wald.tab[match("Host:Cadavers:Ladybird", rownames(wald.tab)), "denDF"]
}
## Use lmeTest and emmmeans to get predictions and associated statistics
if (requireNamespace("lmerTest", quietly = TRUE) &
requireNamespace("emmeans", quietly = TRUE))
{
m1.lmer <- lmerTest::lmer(logitP ~ Host*Cadavers*Ladybird + (1|Run),
data=Ladybird.dat)
HCL.emm <- emmeans::emmeans(m1.lmer, specs = ~ Host:Cadavers:Ladybird)
HCL.preds <- summary(HCL.emm)
den.df <- min(HCL.preds$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 <- allDifferences(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)
## Rename Cadavers
HCL.diffs <- facRename(HCL.diffs, factor.names = "Cadavers", newnames = "Cadaver.nos")
## Check the validity of HCL.diffs
validAlldiffs(HCL.diffs)
}
Run the code above in your browser using DataLab