# mcalinfct

##### 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$model,
formula.in=terms(model),
linfct.Means=
multcomp.meanslinfct(model, focus, mmm.data, formula.in,
contrasts.arg=model$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.

##### See Also

##### Examples

```
# NOT RUN {
## See the examples in HH/scripts/MMC.cc176.R
# }
```

*Documentation reproduced from package HH, version 3.1-39, License: GPL (>= 2)*