HH: mcalinfct – R documentation

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mcalinfct

MCA multiple comparisons analysis (pairwise)

Description

MCA multiple comparisons analysis (pairwise). We calculate the contrast matrix for all pairwise comparisons, taking account of covariates and interactions.

Usage

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"
          )

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.

Author(s)

Richard M. Heiberger <rmh@temple.edu>

Examples

## See the examples in HH/scripts/MMC.cc176.R

HH

Statistical Analysis and Data Display: Heiberger and Holland

v3.1-43

GPL (>= 2)

Authors

Richard M. Heiberger

Initial release

2020-11-27