Mean-Difference Plot
Creates a mean-difference plot of two columns of a matrix.
mdplot(x, columns=c(1,2), xlab="Mean", ylab="Difference", main=NULL, ...)
x |
numeric |
columns |
which columns of |
xlab |
label for the x-axis. |
ylab |
label for the y-axis. |
main |
title of the plot. Defaults to |
... |
any other arguments are passed to |
Plots differences vs means for a set of bivariate values.
This is a generally useful approach for comparing two correlated measures of the same underlying phenomenon.
Bland and Altman (1986) argue it is more information than a simple scatterplot of the two variables.
The bivariate values are stored as columns of x.
A plot is created on the current graphics device.
Gordon Smyth
Cleveland, W. S., (1993). Visualizing Data. Hobart Press.
Bland, J. M., and Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327, 307-310.
plotMD is an object-oriented implementation of mean-difference plots for expression data.
An overview of diagnostic functions available in LIMMA is given in 09.Diagnostics.
x1 <- runif(100) x2 <- (x1 + rnorm(100,sd=0.01))^1.2 oldpar <- par(mfrow=c(1,2)) plot(x1,x2) mdplot(cbind(x1,x2),bg.pch=1,bg.cex=1) par(oldpar)
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