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.
This functionality
requires car version 2.0 or later.
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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