# mmc

##### MMC (Mean--mean Multiple Comparisons) plots.

Constructs a `"mmc.multicomp"`

object from the formula and
other arguments. The constructed object must be explicitly plotted
with the `mmcplot`

function.

##### Usage

`mmc(model, ...) ## R`# S3 method for glht
mmc(model, ...)

# S3 method for default
mmc(model, ## lm object
linfct=NULL,
focus=
if (is.null(linfct))
{
if (length(model$contrasts)==1) names(model$contrasts)
else stop("focus or linfct must be specified.")
}
else
{
if (is.null(names(linfct)))
stop("focus must be specified.")
else names(linfct)
},
focus.lmat,
ylabel=deparse(terms(model)[[2]]),
lmat=if (missing(focus.lmat)) {
t(linfct)
} else {
lmatContrast(t(none.glht$linfct), focus.lmat)
},
lmat.rows=lmatRows(model, focus),
lmat.scale.abs2=TRUE,
estimate.sign=1,
order.contrasts=TRUE,
level=.95,
calpha=NULL,
alternative = c("two.sided", "less", "greater"),
...
)

multicomp.mmc(x, ## S-Plus
focus=dimnames(attr(x$terms,"factors"))[[2]][1],
comparisons="mca",
lmat,
lmat.rows=lmatRows(x, focus),
lmat.scale.abs2=TRUE,
ry,
plot=TRUE,
crit.point,
iso.name=TRUE,
estimate.sign=1,
x.offset=0,
order.contrasts=TRUE,
main,
main2,
focus.lmat,
...)

# S3 method for mmc.multicomp
[(x, ..., drop = TRUE)

##### Arguments

- model
`"aov"`

object in`"lm"`

method.- ylabel
name of the response variable.

- lmat
contrast matrix as in the S-Plus

`multicomp`

. The convention for`lmat`

in R is to use the transpose of the`linfct`

component produced by`glht`

. Required for user-specified contrasts.- lmat.rows
rows in

`lmat`

for the`focus`

factor.- focus
define the factor to compute contrasts of. In R this argument often can be used to simplify the call. The statement

`mmc(my.aov, focus="factorA")`

is interpreted as`mmc(my.aov, factorA="Tukey", `interaction_average`=TRUE, `covariate_average`=TRUE)`

With`TRUE, TRUE`

,`multcomp::glht`

always gives the same result as the S-Plus`multcomp`

function. Without the`TRUE, TRUE`

,`multcomp::glht`

gives a different answer when there are interactions or covariates in the model. See- focus.lmat
R only. Contrast matrix used in the user-specified comparisons of the

`focus`

factor. This is the matrix the user constructs. Row names must include all levels of the factor. Column names are the names the user assigns to the contrasts. Each column must sum to zero. See`catalystm.lmat`

in the Examples section for an example. The`focus.lmat`

matrix is multiplied by the`lmat`

from the`none`

component to create the`lmat`

for the user-specified contrasts. Display the`hibrido.lmat`

and`maiz2.lmat`

in the maiz example below to see what is happening.- linfct
In R, see

- …
other arguments.

`alternative`

and`base`

are frequently used with`glht`

.- comparisons
argument to

`multicomp`

- lmat.scale.abs2
logical, scale the contrasts in the columns of

`lmat`

to make the sum of the absolute values of each column equal 2.- estimate.sign
numeric. If

`0`

, leave contrasts in the default lexicographic direction. If positive, force all contrasts to positive, reversing their names if needed (if contrast A-B is negative, reverse it to B-A). If negative, the force all contrasts to positive.- order.contrasts
sort the contrasts in the (

`mca`

,`none`

,`lmat`

) components by height on the MMC plot. This will place the contrasts in the multicomp plots in the same order as in the MMC plot.- alternative
Direction of alternative hypothesis. See

- level
Confidence level. Defaults to 0.95.

- crit.point, calpha
critical value for the tests. The value from the specified

`multicomp`

method is used for the user-specified contrasts when`lmat`

is specified. This argument is called`crit.point`

with`multicomp`

in S-Plus and`calpha`

when used with`glht`

and`confint`

in R. In R, with a large number of levels for the focus factor,`calpha`

should be specified. See notes below for discussion of the timing issues and the examples for an illustration how to use`calpha`

.- plot
logical, display the plot if

`TRUE`

.- ry, iso.name, x.offset, main, main2
arguments to

`plot.mmc.multicomp`

.- x, drop
See

`"["`

.

##### Details

By default, if `lmat`

is not specified, we plot the isomeans grid
and the pairwise comparisons for the `focus`

factor. By default,
we plot the specified contrasts if the `lmat`

is specified.
Each contrast is plotted at a height which is the weighted average of
the means being compared. The weights are scaled to the sum of their
absolute values equals 2.

We get the right contrasts automatically if the aov is oneway. If we specify an lmat for oneway it must have a leading row of 0.

For any more complex design, we must study the `lmat`

from the `mca`

component of the result to see how to construct the `lmat`

(with the
extra rows as needed) and how to specify the `lmat.rows`

corresponding to the rows for the focus factor.

`mmc`

in R works from either an `"glht"`

object or an
`"aov"`

object. `multicomp.mmc`

in S-Plus works from an
`"aov"`

object.

##### Value

An `"mmc.multicomp"`

object contains either the first two or all
three of the `"multicomp"`

components `mca`

, `none`

,
`lmat`

described here. Each `"multicomp"`

component in
R also contains a `"glht"`

object.

Object containing the pairwise comparisons.

Object comparing each mean to 0.

Object for the contrasts specified in
the `lmat`

argument.

"[.mmc.multicomp" is a subscript method.

##### Note

The multiple comparisons calculations in R and S-Plus use
completely different functions.
MMC plots in R are constructed by `mmc`

based on

##### References

Heiberger, Richard M. and Holland, Burt (2004b).
*Statistical Analysis and Data Display: An Intermediate Course
with Examples in S-Plus, R, and SAS*.
Springer Texts in Statistics. Springer.
ISBN 0-387-40270-5.

Heiberger, Richard M. and Holland, Burt (2006).
"Mean--mean multiple comparison displays for families of linear contrasts."
*Journal of Computational and Graphical Statistics*, 15:937--955.

Hsu, J. and Peruggia, M. (1994).
"Graphical representations of Tukey's multiple comparison method."
*Journal of Computational and Graphical Statistics*, 3:143--161.

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