R2MLwiN (version 0.1-7)

caterpillar: Draws a caterpillar plot (in MLwiN style).

Description

This function uses the means (or medians), upper-quantiles and lower-quantiles for all the groups to draw a caterpillar plot.

Usage

caterpillar(y, x, qtlow, qtup, xlab = "", ylab = "",
xlim = NULL, ylim = NULL, main = "")

Arguments

y

A numerical vector of means (or medians) used as the y coordinates for the plot.

x

A numerical vector specifying the group labels as x coordinates that correspond to the y coordinates.

qtlow

A numerical vector of lower-quantiles to be used to plot error bars.

qtup

A numerical vector of upper-quantiles to be used to plot error bars.

xlab

A label for the x axis. This is empty by default.

ylab

A label for the y axis. This is empty by default.

xlim

The x limits (x1, x2) of the plot. Note that x1 > x2 is allowed and leads to a `reversed axis'. The default value, NULL, indicates that the range of the finite values to be plotted should be used.

ylim

The y limits of the plot.

main

A main title for the plot, see also title.

See Also

caterpillarR

Examples

library(R2MLwiN)
## Modify the following paths as appropriate.
## MLwiN folder
mlwin = "C:/Program Files (x86)/MLwiN v2.27/"
## MLwiN sample worksheet folder
wspath=paste(mlwin,"/samples/",sep="")

## Example: tutorial
formula="normexam~(0|cons+standlrt)+(2|cons)+(1|cons)"
levID=c('school','student')
wsfile=paste(wspath,"tutorial.ws",sep="")
inputfile=paste(tempdir(),"/tutorial.dta",sep="")
ws2foreign(wsfile, foreignfile=inputfile, MLwiNPath=mlwin)
library(foreign);indata =read.dta(inputfile)
estoptions= list(EstM=1,resi.store=TRUE,resi.store.levs=2,mcmcMeth=list(iterations=5001))
(mymodel=runMLwiN(formula, levID, D="Normal", indata, estoptions,MLwiNPath=mlwin))

lencateg = length(unique(indata[["school"]]))
resi.chain2 = mymodel["resi.chains"][,1]
resi.chain2 = matrix(resi.chain2, nrow =lencateg)

## For each iteration, rank the schools
u0rank = apply(resi.chain2,2,rank)
## For each school, calculate the mean rank...
u0rankmn = apply(u0rank, 1,mean)
u0ranklo = apply(u0rank, 1, function(x) quantile(x,.025))
u0rankmd = apply(u0rank, 1,median)
u0rankhi = apply(u0rank, 1, function(x) quantile(x,.975))
rankno = order(u0rankmn)

caterpillar(y=u0rankmn[rankno], x=1:65, qtlow=u0ranklo[rankno], qtup=u0rankhi[rankno],
xlab="School", ylab="Rank")