Description Usage Arguments Value Note Author(s) See Also Examples
MCA multiple comparisons analysis (pairwise). We calculate the contrast matrix for all pairwise comparisons, taking account of covariates and interactions.
1 2 3 4 5 6 7 8 9 10  mcalinfct(model, focus,
mmm.data=model$model,
formula.in=terms(model),
linfct.Means=
multcomp.meanslinfct(model, focus, mmm.data, formula.in,
contrasts.arg=model$contrasts),
type="Tukey"
)

model 

focus 
name of one of the factors in the model, as a character object. 
mmm.data 

formula.in 

linfct.Means 
Contrast matrix for the adjusted means of each level of the focus factor. Normally, the default is the correct value. 
type 
Name of the multiple comparison procedure to be used.
See 
Matrix to be used as a value for the linfct
argument to
glht
.
This function provides results similar to the
mcp(focusname="Tukey")
argument to glht
.
I think it provides better values for covariate and interaction terms.
Richard M. Heiberger <[email protected]>
1  ## See the examples in HH/scripts/MMC.cc176.R

Loading required package: lattice
Loading required package: grid
Loading required package: latticeExtra
Loading required package: RColorBrewer
Loading required package: multcomp
Loading required package: mvtnorm
Loading required package: survival
Loading required package: TH.data
Loading required package: MASS
Attaching package: 'TH.data'
The following object is masked from 'package:MASS':
geyser
Loading required package: gridExtra
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