Description Usage Arguments Value Author(s) See Also Examples
Produces a data frame which resembles to what SAS software gives in proc mixed statement. The approximation for degrees of freedom is Satterthwaite's.
1 | difflsmeans(model, test.effs=NULL, ddf="Satterthwaite",...)
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model |
linear mixed effects model (lmer object). |
test.effs |
charachter vector specifying names of terms to be tested. If NULL all the terms are tested. |
ddf |
By default the Satterthwaite's approximation to degrees of freedom is calculated. If ddf="Kenward-Roger", then the Kenward-Roger's approximation is calculated using |
... |
other potential arguments. |
Produces Differences of Least Squares Means (population means) table with p-values and Confidence intervals.
Alexandra Kuznetsova, Per Bruun Brockhoff, Rune Haubo Bojesen Christensen
1 2 3 4 5 6 7 8 9 10 11 12 | ## import lme4 package and lmerTest package
library(lmerTest)
## specify lmer model
m1 <- lmer(Informed.liking ~ Gender*Information +(1|Consumer), data=ham)
## calculate least squares means for interaction Gender:Information
difflsmeans(m1, test.effs="Gender:Information")
m <- lmer(Coloursaturation ~ TVset*Picture + (1|Assessor), data=TVbo)
plot(difflsmeans(m, test.effs="TVset"))
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