plotCCC: Calculates Concordance Correlation Coefficient (CCC) to...

In lshen1/drexplorer2: Dose-response Explorer2

Description

This function calculates and plots concordance for paired data. Infinite values in x and y are masked as NA so as to compute CCC and corr (otherwise, nan).

Usage

plotCCC(
  x,
  y,
  xlab = NA,
  ylab = NA,
  tag = "",
  col_legend = "red",
  pch = 1,
  main = NA,
  cex = 2,
  plot = TRUE,
  ylim = NA,
  xlim = NA,
  maskBeyondLim = FALSE,
  plotOutlier = FALSE,
  sampleName = NA,
  alpha_outlier = 0.01
)

Arguments

x	x vector.
y	y vector.
xlab	xlab.
ylab	ylab.
tag	add a tag.
col_legend	color for legend text.
pch	pch of the points.
main	main title.
cex	for the dots.
plot	whether draw a figure.
ylim	y axis limit.
xlim	x axis limit.
maskBeyondLim	whether mask values beyond xlim (for x) or ylim (for y) when xlim and ylim is specified. Default is FALSE so that even xlim ylim specified, CCC will not be affected.
plotOutlier	logical whether add an outlier plot comparing Diff vs Mean plot and related statistics.
sampleName	symbols of the text to be shown in outlier plot.
alpha_outlier	alpha to call outliers based on the observed differences assuming from Normal(mean_diff, sd_diff).

Value

a vector of c('ccc', 's_shift', 'l_shift', 'ccc_lo', 'ccc_hi', 'Cb', 'corr'). s_shift is scale shift; l_shift is location shift; ccc_lo and ccc_hi represent 95 interval for CCC. Cb for the bias correction term satisfying CCC=corr*Cb where corr is the Pearson correlation.

Examples

set.seed(100)
r1 <- runif(28)
r2 <- r1+rnorm(28, 0, 0.1)
ccc <- plotCCC(r1, r2, xlab = 'Simulated response, replicate 1',
               ylab = 'Simulated response, replicate 2')

lshen1/drexplorer2 documentation built on June 2, 2020, 9:27 p.m.