intxplot {HH} | R Documentation |
Interaction plot, with an option to print standard error bars. There is an option to offset group lines to prevent the bars from overprinting.
intxplot(x, data=sys.parent[1], groups.in, scales, key.length=1, key.lines, key=TRUE, trace.factor.name=deparse(substitute(groups.in)), x.factor.name=x.factor, xlab=x.factor.name, main=list(main.title, cex=main.cex), condition.name="condition", panel="panel.intxplot", summary.function="sufficient", se, ..., data.is.summary=FALSE, main.title=paste( "Interactions of", trace.factor.name, "and", x.factor.name, if (length(x[[3]]) > 1) paste("|", condition.name.to.use)), main.cex=1.5) panel.intxplot(x, y, subscripts, groups, type = "l", ..., se, cv=1.96, offset.use=(!missing(groups) && !missing(se)), offset.scale=2*max(as.numeric(groups)), offset= as.numeric(groups[match(levels(groups), groups)]) / offset.scale, rug.use=offset.use)
x |
For intxplot , a formula with a factor as the
predictor variable.
For panel.intxplot , standard argument for panel functions. |
data |
data.frame, as used in xyplot . |
groups.in |
groups.in , as used in xyplot . |
scales |
Optional, additional arguments for the standard scales
in xyplot . |
key.length |
Number of columns in the key. |
key.lines |
default value for the lines argument of key . |
key |
logical. If TRUE , draw the key. |
trace.factor.name |
Name of the grouping variable. |
x.factor.name |
name of the dependent variable. |
xlab |
as in xyplot , defaults to the name of the predictor variable
from the formula. |
main |
as in xyplot . Defaults to the main.title argument. |
panel |
as in xyplot . Defaults to the "panel.intxplot" . |
condition.name |
name of the conditioning variable. |
summary.function |
The default sufficient finds the mean,
standard deviation, and sample size of the response variable for each
level of the conditioning factor. See sufficient . |
se |
standard errors to be passed to panel.intxplot .
se Missing, logical, or a numeric vector.
If missing or FALSE , standard errors are not plotted.
If se=TRUE in intxplot ,
the standard errors are calculated from the
sufficient statistics for each group as the group's standard deviation
divided by the square root of the group's observation
count. If se is numeric vector, it is evaluated in the environment of
the sufficient statistics.
the se argument to panel.intxplot must be numeric.
|
... |
In intxplot , arguments for panel.intxplot .
In panel.intxplot , arguments for panel.superpose . |
data.is.summary |
logical, defaults to FALSE under the
assumption that the input data.frame is the original data and the
intxplot function will generate the summary information
(primarily standard deviation sd and number of
observations nobs for each group). When TRUE , the
standard error calculation assumes variables sd and
nobs are in the dataset. |
main.title |
Default main title for plot. |
main.cex |
Default character expansion for main title. |
y, subscripts, groups, type |
Standard arguments for panel functions. |
cv |
critical value for confidence intervals. Defaults to 1.96. |
offset.use |
logical. If TRUE , offset the endpoints
of each group. |
offset.scale |
Scale number indicating how far apart the ends of the groups will be placed. Larger numbers make them closer together. |
offset |
Actual numbers by which the end of the groups are offset
from their nominal location which is the as.numeric of the
group levels. |
rug.use |
logical. If TRUE , display a rug for the endpoints
of each group. |
"trellis"
object.
Richard M. Heiberger <rmh@temple.edu>
## This uses the same data as the HH Section 12.13 rhizobium example. rhiz.clover <- read.table(hh("datasets/rhiz3-clover.dat"), header=TRUE) rhiz.clover$comb <- factor(rhiz.clover$comb, labels=c("clover","clover+alfalfa")) position(rhiz.clover$comb) <- c(2,5) rhiz.clover$strain <- factor(rhiz.clover$strain, labels=c('3DOk1','3DOk5','3DOk4','3DOk7','3DOk13','k.comp')) rhiz.clover$Npg <- rhiz.clover$nitro / rhiz.clover$weight ## interaction plot, no se intxplot(Npg ~ strain, groups=comb, data=rhiz.clover) ## interaction plot, individual se for each treatment combination intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE) ## Rescaled to allow the CI bars to stay within the plot region intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE, ylim=range(rhiz.clover$Npg)) ## interaction plot, common se based on ANOVA table intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5)) ## Rescaled to allow the CI bars to stay within the plot region intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5), ylim=range(rhiz.clover$Npg)) ## change distance between endpoints intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE, offset.scale=20) ## When data includes the nobs and sd variables, data.is.summary=TRUE is needed. intxplot(Npg ~ strain, groups=comb, se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5), data=sufficient(rhiz.clover, y="Npg", c("strain","comb")), data.is.summary=TRUE, ylim=range(rhiz.clover$Npg))