ancova | R Documentation |
Compute and plot oneway analysis of covariance.
The result object is an ancova
object which consists of
an ordinary aov
object with an additional trellis
attribute. The
trellis
attribute is a trellis
object consisting of
a series of plots of y ~ x
. The left set of panels is
conditioned on the levels of the factor groups
. The right
panel is a superpose of all the groups.
ancova(formula, data.in = NULL, ...,
x, groups, transpose = FALSE,
display.plot.command = FALSE,
superpose.level.name = "superpose",
ignore.groups = FALSE, ignore.groups.name = "ignore.groups",
blocks, blocks.pch = letters[seq(levels(blocks))],
layout, between, main,
pch=trellis.par.get()$superpose.symbol$pch)
panel.ancova(x, y, subscripts, groups,
transpose = FALSE, ...,
coef, contrasts, classes,
ignore.groups, blocks, blocks.pch, blocks.cex, pch)
## The following are ancova methods for generic functions.
## S3 method for class 'ancova'
anova(object, ...)
## S3 method for class 'ancova'
predict(object, ...)
## S3 method for class 'ancova'
print(x, ...) ## prints the anova(x) and the trellis attribute
## S3 method for class 'ancova'
model.frame(formula, ...)
## S3 method for class 'ancova'
summary(object, ...)
## S3 method for class 'ancova'
plot(x, y, ...) ## standard lm plot. y is always ignored.
## S3 method for class 'ancova'
coef(object, ...)
formula |
A formula specifying the model. |
data.in |
A data frame in which the variables specified in the formula will be found. If missing, the variables are searched for in the standard way. |
... |
Arguments to be passed to |
x |
Covariate in |
groups |
Factor. Needed for plotting when the formula does not
include |
transpose |
S-Plus: The axes in each panel of the plot are transposed. The analysis is identical, just the axes displaying it have been interchanged. R: no effect. |
display.plot.command |
The default setting is usually what the user
wants. The alternate value |
superpose.level.name |
Name used in strip label for superposed panel. |
ignore.groups |
When |
ignore.groups.name |
Name used in strip label for
|
pch |
Plotting character for groups. |
blocks |
Additional factor used to label points in the panels. |
blocks.pch |
Alternate set of labels used when a |
blocks.cex |
Alternate set of |
layout |
The layout of multiple panels. The default is a single row. See details. |
between |
Space between the panels for the individual group levels and the superpose panel including all groups. |
main |
Character with a main header title to be done on the top of each page. |
y , subscripts |
In |
object |
An |
object. The functions using this argument are methods for the similarly named generic functions.
coef , contrasts , classes |
Internal variables used to communicate between
|
The ancova
function does two things. It passes its
arguments directly to the aov
function and returns the entire
aov
object. It also rearranges the data and formula in its
argument and passes that to the xyplot
function. The
trellis
attribute is a trellis
object consisting of
a series of plots of y ~ x
. The left set of panels is
conditioned on the levels of the factor groups
. The right
panel is a superpose of all the groups.
The result object is an ancova
object which consists of
an ordinary aov
object with an additional trellis
attribute. The default print method is to print both the anova
of the object and the trellis
attribute.
Richard M. Heiberger <rmh@temple.edu>
Heiberger, Richard M. and Holland, Burt (2015). Statistical Analysis and Data Display: An Intermediate Course with Examples in R. Second Edition. Springer-Verlag, New York. https://link.springer.com/book/10.1007/978-1-4939-2122-5
ancova-class
aov
xyplot
.
See ancovaplot
for a newer set of functions that keep the
graph and the aov
object separate.
data(hotdog)
## y ~ x ## constant line across all groups
ancova(Sodium ~ Calories, data=hotdog, groups=Type)
## y ~ a ## different horizontal line in each group
ancova(Sodium ~ Type, data=hotdog, x=Calories)
## This is the usual usage
## y ~ x + a or y ~ a + x ## constant slope, different intercepts
ancova(Sodium ~ Calories + Type, data=hotdog)
ancova(Sodium ~ Type + Calories, data=hotdog)
## y ~ x * a or y ~ a * x ## different slopes, and different intercepts
ancova(Sodium ~ Calories * Type, data=hotdog)
ancova(Sodium ~ Type * Calories, data=hotdog)
## y ~ a * x ## save the object and print the trellis graph
hotdog.ancova <- ancova(Sodium ~ Type * Calories, data=hotdog)
attr(hotdog.ancova, "trellis")
## label points in the panels by the value of the block factor
data(apple)
ancova(yield ~ treat + pre, data=apple, blocks=block)
## Please see
## demo("ancova")
## for a composite graph illustrating the four models listed above.
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