ancovaplot
Analysis of Covariance Plots
Analysis of Covariance Plots. Any of the ancova models
y ~ x * t
y ~ t * x
y ~ x + t
y ~ t + x
y ~ x , groups=t
y ~ t, x=x
y ~ x * t, groups=b
y ~ t * x, groups=b
y ~ x + t, groups=b
y ~ t + x, groups=b
- Keywords
- models, hplot, regression, dplot
Usage
ancovaplot(object, ...)
# S3 method for formula
ancovaplot(object, data, groups=NULL, x=NULL, ...,
formula=object,
col=rep(tpg$col,
length=length(levels(as.factor(groups)))),
pch=rep(c(15,19,17,18,16,20, 0:14),
length=length(levels(as.factor(groups)))),
slope, intercept,
layout=c(length(levels(cc)), 1),
col.line=col, lty=1,
superpose.panel=TRUE,
between=if (superpose.panel)
list(x=c(rep(0, length(levels(cc))-1), 1))
else
list(x=0),
col.by.groups=FALSE ## ignored unless groups= is specified
)panel.ancova.superpose(x, y, subscripts, groups,
slope, intercept,
col, pch, ...,
col.line, lty,
superpose.panel,
col.by.groups,
condition.factor,
groups.cc.incompatible,
plot.resids=FALSE,
print.resids=FALSE,
mean.x.line=FALSE,
col.mean.x.line="gray80")
Arguments
- formula, object
formula
specifying theaov
model. The function modifies it for thexyplot
specification.- data
data.frame
- groups
If the treatment factor is included in the
formula
, thengroups
is not needed. By defaultgroups
will be set to the treatment factor, but the user may specify another factor forgroups
, usually a blocking factor. Thepch
will follow the value ofgroups
. If the treatment is not included in theformula
, thengroups
is required.- x
Covariate. Required by
ancovaplot.formula
if the covariate is not included in theformula
.For
panel.ancova.superpose
, seepanel.superpose
.- …
Other arguments to be passed to
xyplot
.- col, pch
Standard lattice arguments.
pch
follows the value ofgroups
. Whencol.by.groups
isTRUE
, thencol
follow the value ofgroups
. Whencol.by.groups
isFALSE
, thencol
follows the value of the treatment factor, and is constant in each panel.- slope, intercept
Vector, the length of the number of treatment levels, containing slope and intercept of the
abline
in each panel. This is by default calculated based on the formula. The user may override each independently.- layout, between
Standard lattice arguments.
- col.line, lty
Standard lattice arguments. By default, they follow the value of the treatment factor in the
formula
.col.line
is recycled to the number of panels in the plot.- y, subscripts
See
panel.xyplot
.- superpose.panel
logical. if
TRUE
(the default), there is an additional panel on the right containing the superposition of the points and lines for all treatment levels.- col.by.groups
logical. See the discussion in argument
col
.- condition.factor, groups.cc.incompatible
These are both internal variables.
condition.factor
contains a copy of the treatment factor.groups.cc.incompatible
is a logical which is set toTRUE
when thegroups
argument is explicitly set by the user.- plot.resids, print.resids, mean.x.line, col.mean.x.line
logical, logical, logical or numeric, color name. When
plot.resids==TRUE
then vertical line segments connecting the data points and the fitted line are drawn. The other two arguments are interpreted only whenplot.resids==TRUE
. Whenprint.resids==TRUE
then the values of the residuals are printed on the console. Whenis.numeric(mean.x.line)
then a vertical reference line is drawn at the specified value, which will normally be specified by the user as the mean of the full set of x values. The reference line will have color specified bycol.mean.x.line
.
Details
ancova=aov specification |
xyplot specification |
abline |
|
y ~ x * t |
y ~ x | t, groups=t |
lm(y[t] ~ x[t]) |
## separate lines |
y ~ t * x |
y ~ x | t, groups=t |
lm(y[t] ~ x[t]) |
## separate lines |
y ~ x + t |
y ~ x | t, groups=t |
lm(y ~ x + t) |
## parallel lines |
y ~ t + x |
y ~ x | t, groups=t |
lm(y ~ x + t) |
## parallel lines |
y ~ x , groups=t |
y ~ x | t, groups=t |
lm(y ~ x) |
## single regression line |
y ~ t, x=x |
y ~ x | t, groups=t |
mean(t) |
## separate horizontal lines |
y ~ x * t, groups=b |
y ~ x | t, groups=b |
lm(y[t] ~ x[t]) |
## sep lines, pch&col follow b |
y ~ t * x, groups=b |
y ~ x | t, groups=b |
lm(y[t] ~ x[t]) |
## sep lines, pch&col follow b |
y ~ x + t, groups=b |
y ~ x | t, groups=b |
lm(y ~ x + t) |
## par lines, pch&col follow b |
Value
ancovaplot
returns a c("ancova","trellis")
object.
panel.ancova.superpose
is an ordinary lattice panel
function.
References
Heiberger, Richard M. and Holland, Burt (2004). 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
See the older ancova
.
Examples
# NOT RUN {
data(hotdog, package="HH")
ancovaplot(Sodium ~ Calories + Type, data=hotdog)
ancovaplot(Sodium ~ Calories * Type, data=hotdog)
ancovaplot(Sodium ~ Calories, groups=Type, data=hotdog)
ancovaplot(Sodium ~ Type, x=Calories, data=hotdog)
## Please see demo("ancova", package="HH") to coordinate placement
## of all four of these plots on the same page.
ancovaplot(Sodium ~ Calories + Type, data=hotdog, plot.resids=TRUE)
# }