ancova {HH} | 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) panel.ancova(x, y, subscripts, groups, transpose = FALSE, ..., coef, contrasts, classes, ignore.groups, blocks, blocks.pch, blocks.cex) ## 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, ...) ## S3 method for class 'ancova': coefficients(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 aov , such as subset
or na.action . |
x |
Covariate in ancova , needed for plotting when the
formula does not include x .
"aov" object in print.ancova , to match the argument of
the print generic function.
Variable to plotted in "panel.ancova" .
|
groups |
Factor. Needed for plotting when the formula does not
include groups after the conditioning bar "|" . |
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 TRUE prints on the console the
command that draws the graph. This is strictly for debugging the
ancova command. |
superpose.level.name |
Name used in strip label for superposed panel. |
ignore.groups |
When TRUE , an additional panel showing all
groups together with a common regression line is displayed. |
ignore.groups.name |
Name used in strip label for
ignore.groups panel. |
blocks |
Additional factor used to label points in the panels. |
blocks.pch |
Alternate set of labels used when a blocks
factor is specified. |
blocks.cex |
Alternate set of cex used when a blocks
factor is specified. |
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 "panel.ancova" , see
panel.xyplot in R and both
xyplot and trellis.args in S-Plus. |
object |
An "aov" |
coef, contrasts, classes |
Internal variables used to communicate between
ancova and panel.ancova . They keep track
of the constant or different slopes and intercepts in each
panel of the plot. |
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 (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.
hotdog <- read.table(hh("datasets/hotdog.dat"), header=TRUE) ## 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 apple <- read.table(hh("datasets/apple.dat"), header=TRUE) apple$treat <- factor(apple$treat) contrasts(apple$treat) <- contr.treatment(6) apple$block <- factor(apple$block) ancova(yield ~ treat + pre, data=apple, blocks=block)