mcalinfct: MCA multiple comparisons analysis (pairwise)

Description Usage Arguments Value Note Author(s) See Also Examples

Description

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

Usage

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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 <[email protected]>

See Also

MMC

Examples

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

Example output

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

HH documentation built on May 29, 2017, 7:49 p.m.

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