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,
...
)an object of class mlm.
indices or names of the three of more response variables to be plotted; defaults to all of the responses.
labels for the variables plotted in the diagonal panels; defaults to names of the response variables.
character expansion for the variable labels.
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).
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.
a one-sided model formula using the ``data'' in idata and specifying the intra-subject design for repeated measure models.
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").
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.
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.
optional Anova.mlm object for the model; if absent a
MANOVA is computed. Specifying the argument can therefore save computation
in repeated calls.
proportion to extend the axes in each direction; defaults to 0.05.
number of significant digits in axis end-labels; taken from
the "digits" option.
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
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.
Michael Friendly
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
heplot, heplot3d
# 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")))
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