On 05/14/2011 07:20 AM, whitney.mel...@colorado.edu wrote:
I cannot seem to get a L'abbe plot to work on R. I do not understand what
the X coordinates, or alternatively an object of class metabin, is
supposed to mean. What is a class of metabin?
Hi Whitney,
The L'Abbe plot is a relatively simple illustration that shows the
results of intervention trials as two proportions on a Cartesian plane.
The outcomes must be dichotomous (dead/alive, cured/not cured,
improved/not improved, etc.) and the comparisons are between two
interventions. Say that I was asked to evaluate an intervention for
excessive drinkers that randomly assigned the subjects to either a
session with a behavioral therapist or a session of equal duration with
an ex-drinker. The outcome might be whether the subject drank more or
less over the succeeding month. Thus:
didf<-data.frame(subject=1:50,interv=rep(c("therapist","ex-drinker"),each=25),outcome=sample(c("more","less"),50,TRUE))
didf.tab<-table(didf$interv,didf$outcome)
didf.tab
less more
ex-drinker 14 11
therapist 12 13
chisq.test(didf.tab)
Pearson's Chi-squared test with Yates' continuity correction
data: didf.tab
X-squared = 0.0801, df = 1, p-value = 0.7771
Apparently ex-drinkers are no better or worse than therapists. So we
want to illustrate this with a L'Abbe plot.
library(plotrix)
labbePlot<-function(x,main="L'Abbe plot",
xlab="Positive response with placebo (%)",
ylab="Positive response with treatment (%)",...) {
plot(0,xlim=c(0,100),ylim=c(0,100),main=main,xlab=xlab,
ylab=ylab,type="n",...)
for(trial in 1:length(x)) {
sum_treat<-sum(x[[trial]][1,])
sum_interv<-sum(x[[trial]][2,])
xpos<-100*x[[trial]][1,1]/sum_treat
ypos<-100*x[[trial]][2,1]/sum_interv
rad<-sqrt(sum_treat+sum_interv)/2
draw.circle(xpos,ypos,rad)
}
segments(0,0,100,100)
}
x<-list(didf.tab)
labbePlot(x)
This shows that the therapists, whom we expected to do better, were
slightly, but not significantly, worse than the ex-drinkers. This can't
be right, so let's follow it up with a bigger trial.
didf2<-data.frame(subject=1:200,
interv=rep(c("therapist","ex-drinker"),each=100),
outcome=c(sample(c("more","less"),100,TRUE,prob=c(0.3,0.7)),
sample(c("more","less"),100,TRUE,prob=c(0.7,0.3))))
didf2.tab<-table(didf2$interv,didf2$outcome)
x<-list(didf.tab,didf2.tab)
labbePlot(x)
That's better, isn't it? This basic plot can be tarted up with colors
for the different circles, and other decorations so beloved of those who
use presentation packages. Now that I've written it, I might as well add
it to the plotrix package.
Jim
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