The function (in the form of an `mlm`

method for the generic
`pairs`

function) constructs a ``matrix'' of pairwise
HE plots (see heplot) for a multivariate linear model.

```
# S3 method for mlm
pairs(x, variables, var.labels, var.cex=2,
type = c("II", "III", "2", "3"),
idata=NULL, idesign=NULL, icontrasts=NULL, imatrix=NULL, iterm=NULL, manova,
offset.axes = 0.05, digits = getOption("digits") - 1, fill=FALSE, fill.alpha=0.3, ...)
```

x

an object of class `mlm`

.

variables

indices or names of the three of more response variables to be plotted; defaults to all of the responses.

var.labels

labels for the variables plotted in the diagonal panels; defaults to names of the response variables.

var.cex

character expansion for the variable labels.

type

``type'' of sum-of-squares-and-products matrices to compute; one of
`"II"`

, `"III"`

, `"2"`

, or `"3"`

, where `"II"`

is
the default (and `"2"`

is a synonym).

idata

an optional data frame giving a factor or factors defining the
intra-subject model for multivariate repeated-measures data.
See Details of `Anova`

for an explanation of the intra-subject design and for further explanation
of the other arguments relating to intra-subject factors.

idesign

a one-sided model formula using the ``data'' in idata and specifying the intra-subject design for repeated measure models.

icontrasts

names of contrast-generating functions to be applied by default to factors and ordered factors, respectively, in the within-subject ``data''; the contrasts must produce an intra-subject model matrix in which different terms are orthogonal. The default is c("contr.sum", "contr.poly").

imatrix

In lieu of `idata`

and `idesign`

, you can specify the
intra-subject design matrix directly via `imatrix`

, in the form of list of named elements.
Each element gives
the columns of the within-subject model matrix for an intra-subject term to be tested, and must
have as many rows as there are responses; the columns of the within-subject model
matrix for *different* terms must be mutually orthogonal.
*This functionality
requires car version 2.0 or later.*

iterm

For repeated measures designs, you must specify one intra-subject term
(a character string) to select the SSPE (E) matrix used in the HE plot.
Hypothesis terms plotted include the `iterm`

effect as well as all interactions
of `iterm`

with `terms`

.

manova

optional `Anova.mlm`

object for the model; if absent a
MANOVA is computed. Specifying the argument can therefore save
computation in repeated calls.

offset.axes

proportion to extend the axes in each direction; defaults to 0.05.

digits

number of significant digits in axis end-labels; taken from
the `"digits"`

option.

fill

A logical vector indicating whether each ellipse should be filled or not.
The first value is used for the error ellipse, the rest --- possibly recycled --- for
the hypothesis ellipses; a single fill value can be given.
Defaults to FALSE for backward compatibility. See Details of `heplot`

fill.alpha

Alpha transparency for filled ellipses, a numeric scalar or vector of values
within `[0,1]`

, where 0 means fully transparent and 1 means fully opaque. Defaults to 0.3.

…

arguments to pass down to `heplot`

, which is used to draw
each panel of the display.

Friendly, M. (2006).
Data Ellipses, HE Plots and Reduced-Rank Displays for Multivariate Linear
Models: SAS Software and Examples
*Journal of Statistical Software*, 17(6), 1-42.
https://www.jstatsoft.org/v17/i06/

Friendly, M. (2007).
HE plots for Multivariate General Linear Models.
*Journal of Computational and Graphical Statistics*, 16(2) 421-444.
http://datavis.ca/papers/jcgs-heplots.pdf

# NOT RUN { # ANCOVA, assuming equal slopes rohwer.mod <- lm(cbind(SAT, PPVT, Raven) ~ SES + n + s + ns + na + ss, data=Rohwer) # View all pairs, with ellipse for all 5 regressors pairs(rohwer.mod, hypotheses=list("Regr" = c("n", "s", "ns", "na", "ss"))) # }