mcr (version 1.3.3.1)

MCResult.plot: 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),
  ...
)

Value

No return value, instead a plot is generated

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

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)