mcalinfct

0th

Percentile

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.

Keywords
htest
Usage
mcalinfct(model, focus,
          mmm.data=model$model,
          formula.in=terms(model),
          linfct.Means=
          multcomp:::meanslinfct(model, focus, mmm.data, formula.in),
          type="Tukey"
          )
Arguments
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.
Value

  • Matrix to be used as a value for the linfct argument to glht.

Note

This function provides results similar to the mcp(focusname="Tukey") argument to glht. I think it provides better values for covariate and interaction terms.

See Also

MMC

Aliases
  • mcalinfct
Examples
## See the examples in HH/scripts/MMC.cc176.R
Documentation reproduced from package HH, version 2.1-5, License: GPL version 2 or newer

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