int.plot.lm: Linear Model-driven Interaction Plots of Response with...

In byandell/pda: Practial Data Analysis for Designed Experiments

Description

A plot is created showing the requested function of responses for each level of the x.factor at each level of the trace.factor.

Usage

## S3 method for class 'lm'
ci.plot(object, ..., bar.plot="ci")
## S3 method for class 'lme'
ci.plot(object, data, ..., bar.plot="ci")
## S3 method for class 'lmer'
ci.plot(object, data, ..., bar.plot="ci")
## S3 method for class 'lm'
int.plot(object, data, factors, lsm, ci, offset,
   bar.plot="lsd", ylim, type, width, sort.mean=FALSE, edge,
   xlab, ylab, level, rdf, fine, xpos, ypos, cex, white, panelf = NULL,...)
## S3 method for class 'lme'
int.plot(object, data, ...)
## S3 method for class 'lmer'
int.plot(object, data, ...)

Arguments

object	fitted model object (optional unless response is omitted).
data	data frame in which to interpret the variables named in the fit object (taken from object if omitted).
factors	Character string of length 2 with names of x.factor and trace.factor as found in object and data (default is first 2 factors in object).
lsm	Least squares means for plotting (default is object from model).
sort.mean	should x.factor levels be sorted by mean value (default=FALSE).
ylim,type,xlab,ylab	plot parameters
ci,offset,width,edge,xpos,ypos,level,rdf,fine,cex	optional parameters for bar-drawing routines lsd.bar and se.bar. There are some parameters, such as width and edge which can change to plotting area.
bar.plot	"lsd" (default for int.plot), "ci" (default for ci.plot), "test", "ellipse" or "none". The "test" is a sqrt(2) contraction of confidence interval for approximate graphical comparisons of means.
white	white plot background if TRUE (default)
panelf	optional extra panel function for lattice plot
...	optional parameters for plotting routines

Value

list containing sd, rdf, level and sample size, and either lsd (lsd.plot) or width (ci.plot).

See Also

int.plot, xyplot, margin.plot.lm, lsd.bar, ci.width, pvalue.ellipse.

Examples

data(ToothGrowth)
ToothGrowth$dose = ordered(ToothGrowth$dose)
tooth.fit = aov(len~dose*supp, ToothGrowth)
lsd.plot( tooth.fit, ToothGrowth, factors = c("supp","dose"))

cat.lsm = lsmean(tooth.fit)
lsd.plot(tooth.fit, ToothGrowth, factors = c("supp","dose"),
         lsm = cat.lsm)

byandell/pda documentation built on May 13, 2019, 9:27 a.m.