Hmisc (version 3.0-10)

errbar: Plot Error Bars

Description

errbar adds vertical error bars to an existing plot or makes a new plot with error bars. It can also make a horizontal error bar plot that shows error bars for group differences as well as bars for groups. For the latter type of plot, the lower x-axis scale corresponds to group estimates and the upper scale corresponds to differences. The spacings of the two scales are identical but the scale for differences has its origin shifted so that zero may be included. If at least one of the confidence intervals includes zero, a vertical dotted reference line at zero is drawn.

Usage

errbar(x, y, yplus, yminus, cap, xlab, ylab, add=FALSE, 
       lty=1, ylim, lwd=1, Type=rep(1,length(y)), ...)

Arguments

x
vector of numeric x values (for vertical error bars) or a factor or character variable (for horizontal error bars, x representing the group labels)
y
vector of y values.
yplus
vector of y values: the tops of the error bars.
yminus
vector of y values: the bottoms of the error bars.
cap
The width of the little lines at the tops and bottoms of the error bars in units of the width of the plot. Default is .015.
xlab
ylab
optional axis labels if add=FALSE. Defaults to blank for horizontal charts.
add
Set toTRUE to add bars to an existing plot (available only for vertical error bars)
lty
Line type for bars
ylim
Y-axis limits. Default is to use range of yminus and yplus. For horizonal charts, ylim is really the x-axis range, excluding differences.
lwd
Line width for line segments (not main line)
Type
used for horizontal bars only. Is an integer vector with values 1 if corresponding values represent simple estimates, 2 if they represent differences.
...
other parameters passed to plot function.

Examples

Run this code
set.seed(1)
x <- 1:10
y <- x + rnorm(10)
delta <- runif(10)
errbar( x, y, y + delta, y - delta )


# Show bootstrap nonparametric CLs for 3 group means and for
# pairwise differences on same graph
group <- sample(c('a','b','d'), 200, TRUE)
y     <- runif(200) + .25*(group=='b') + .5*(group=='d')
cla <- smean.cl.boot(y[group=='a'],B=100,reps=TRUE)  # usually B=1000
a   <- attr(cla,'reps')
clb <- smean.cl.boot(y[group=='b'],B=100,reps=TRUE)
b   <- attr(clb,'reps')
cld <- smean.cl.boot(y[group=='d'],B=100,reps=TRUE)
d   <- attr(cld,'reps')
a.b <- quantile(a-b,c(.025,.975))
a.d <- quantile(a-d,c(.025,.975))
b.d <- quantile(b-d,c(.025,.975))
errbar(c('a','b','d','a - b','a - d','b - d'),
       c(cla[1],clb[1],cld[1],cla[1]-clb[1],cla[1]-cld[1],clb[1]-cld[1]),
       c(cla[3],clb[3],cld[3],a.b[2],a.d[2],b.d[2]),
       c(cla[2],clb[2],cld[2],a.b[1],a.d[1],b.d[1]),
       Type=c(1,1,1,2,2,2))


       
rm(x,y,delta,group,a,b,d,a.b,a.d,b.d,cla,clb,cld)

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