| mcalinfct {HH} | R Documentation |
MCA multiple comparisons analysis (pairwise). We calculate the contrast matrix for all pairwise comparisons, taking account of covariates and interactions.
mcalinfct(model, focus,
mmm.data=model$model,
formula.in=terms(model),
linfct.Means=
multcomp:::meanslinfct(model, focus, mmm.data, formula.in),
type="Tukey"
)
model |
aov object |
focus |
name of one of the factors in the model, as a character object. |
mmm.data |
data.frame from which the model was estimated.
Normally, the default is the correct value. |
formula.in |
formula of the model which was estimated.
Normally, the default is the correct value. The use of the
terms
function honors the keep.order=TRUE if it was specified. |
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 contrMat. |
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 <rmh@temple.edu>
## See the examples in HH/scripts/MMC.cc176.R