MCA multiple comparisons analysis (pairwise)
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$model, formula.in=terms(model), linfct.Means= meanslinfct.hh(model, focus, mmm.data, formula.in, contrasts.arg=model$contrasts), type="Tukey" ) meanslinfct.hh(model, focus, mmm.data = model$model, formula.in = terms(model), contrasts.arg = NULL)
- name of one of the factors in the model, as a character object.
data.framefrom which the model was estimated. Normally, the default is the correct value.
formulaof the model which was estimated. Normally, the default is the correct value. The use of the
termsfunction honors the
keep.order=TRUEif it was specified.
- Contrast matrix for the adjusted means of each level of the focus factor. Normally, the default is the correct value.
- Name of the multiple comparison procedure to be used.
- argument to
- Matrix to be used as a value for the
This function provides results similar to the
mcp(focusname="Tukey") argument to
I think it provides better values for covariate and interaction terms.
## See the examples in HH/scripts/MMC.cc176.R