# ancova

##### Compute and plot oneway analysis of covariance

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.

- Keywords
- models, hplot, regression, dplot

##### Usage

```
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, ...)
```

##### Arguments

- 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 plo - 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. - 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`

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"`

,#ifndef S-Plus see`panel.xyplot`

. #endif #ifdef S-Plus see both`xyplot`

and - 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.

##### Details

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.

##### Value

- 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.

##### References

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.

##### See Also

`ancova-class`

`aov`

`xyplot`

.
See `ancovaplot`

for a newer set of functions that keep the
graph and the `aov`

object separate.

##### Examples

```
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.
```

*Documentation reproduced from package HH, version 3.1-25, License: GPL (>= 2)*