MCResult.plot: Scatter Plot Method X vs. Method Y

In mcr: Method Comparison Regression

Scatter Plot Method X vs. Method Y

Description

Plot method X (reference) vs. method Y (test) with (optional) line of identity, regression line and confidence bounds for response.

Usage

MCResult.plot(
  x,
  alpha = 0.05,
  xn = 20,
  equal.axis = FALSE,
  xlim = NULL,
  ylim = NULL,
  xaxp = NULL,
  yaxp = NULL,
  x.lab = x@mnames[1],
  y.lab = x@mnames[2],
  add = FALSE,
  draw.points = TRUE,
  points.col = "black",
  points.pch = 1,
  points.cex = 0.8,
  reg = TRUE,
  reg.col = NULL,
  reg.lty = 1,
  reg.lwd = 2,
  identity = TRUE,
  identity.col = NULL,
  identity.lty = 2,
  identity.lwd = 1,
  ci.area = TRUE,
  ci.area.col = NULL,
  ci.border = FALSE,
  ci.border.col = NULL,
  ci.border.lty = 2,
  ci.border.lwd = 1,
  add.legend = TRUE,
  legend.place = c("topleft", "topright", "bottomleft", "bottomright"),
  main = NULL,
  sub = NULL,
  add.cor = TRUE,
  cor.method = c("pearson", "kendall", "spearman"),
  add.grid = TRUE,
  digits = list(coef = 2, cor = 3),
  ...
)

Arguments

x	object of class "MCResult".
alpha	numeric value specifying the 100(1-alpha)% confidence bounds.
xn	number of points (default 20) for calculation of confidence bounds.
equal.axis	logical value. If equal.axis=TRUE x-axis will be equal to y-axis.
xlim	limits of the x-axis. If xlim=NULL the x-limits will be calculated automatically.
ylim	limits of the y-axis. If ylim=NULL the y-limits will be calculated automatically.
xaxp	ticks of the x-axis. If xaxp=NULL the x-ticks will be calculated automatically.
yaxp	ticks of the y-axis. If yaxp=NULL the y-ticks will be calculated automatically.
x.lab	label of x-axis. Default is the name of reference method.
y.lab	label of y-axis. Default is the name of test method.
add	logical value. If add=TRUE, the plot will be drawn in current graphical window.
draw.points	logical value. If draw.points=TRUE, the data points will be drawn.
points.col	Color of data points.
points.pch	Type of data points (see par()).
points.cex	Size of data points (see par()).
reg	Logical value. If reg=TRUE, the regression line will be drawn.
reg.col	Color of regression line.
reg.lty	Type of regression line.
reg.lwd	The width of regression line.
identity	logical value. If identity=TRUE the identity line will be drawn.
identity.col	The color of identity line.
identity.lty	The type of identity line.
identity.lwd	the width of identity line.
ci.area	logical value. If ci.area=TRUE (default) the confidence area will be drawn.
ci.area.col	the color of confidence area.
ci.border	logical value. If ci.border=TRUE the confidence limits will be drawn.
ci.border.col	The color of confidence limits.
ci.border.lty	The line type of confidence limits.
ci.border.lwd	The line width of confidence limits.
add.legend	logical value. If add.legend=FALSE the plot will not have any legend.
legend.place	The position of legend: "topleft","topright","bottomleft","bottomright".
main	String value. The main title of plot. If main=NULL it will include regression name.
sub	String value. The subtitle of plot. If sub=NULL and ci.border=TRUE or ci.area=TRUE it will include the art of confidence bounds calculation.
add.cor	Logical value. If add.cor=TRUE the correlation coefficient will be shown.
cor.method	a character string indicating which correlation coefficient is to be computed. One of "pearson" (default), "kendall", or "spearman", can be abbreviated.
add.grid	Logical value. If add.grid=TRUE (default) the gridlines will be drawn.
digits	list with the number of digits for the regression equation and the correlation coefficient.
...	further graphical parameters

Value

No return value, instead a plot is generated

See Also

plotBias, plotResiduals, plotDifference, compareFit,includeLegend

Examples

 library(mcr)
 data(creatinine,package="mcr")
 creatinine <- creatinine[complete.cases(creatinine),]
  x <- creatinine$serum.crea
  y <- creatinine$plasma.crea

  m1 <- mcreg(x,y,method.reg="Deming",  mref.name="serum.crea",
                                        mtest.name="plasma.crea", na.rm=TRUE)
  m2 <- mcreg(x,y,method.reg="WDeming", method.ci="jackknife",
                                        mref.name="serum.crea",
                                        mtest.name="plasma.crea", na.rm=TRUE)

  plot(m1,  xlim=c(0.5,3),ylim=c(0.5,3), add.legend=FALSE,
                           main="Deming vs. weighted Deming regression",
                           points.pch=19,ci.area=TRUE, ci.area.col=grey(0.9),
                           identity=FALSE, add.grid=FALSE, sub="")
  plot(m2, ci.area=FALSE, ci.border=TRUE, ci.border.col="red3",
                           reg.col="red3", add.legend=FALSE,
                           draw.points=FALSE,add=TRUE)

  includeLegend(place="topleft",models=list(m1,m2),
                           colors=c("darkblue","red"), design="1", digits=2)

mcr documentation built on Oct. 11, 2023, 5:14 p.m.