| plotCorrPrecision {Hmisc} | R Documentation |
Plot Precision of Estimate of Pearson Correlation Coefficient
Description
This function plots the precision (margin of error) of the
product-moment linear
correlation coefficient r vs. sample size, for a given vector of
correlation coefficients rho. Precision is defined as the larger
of the upper confidence limit minus rho and rho minus the lower confidence
limit. labcurve is used to automatically label the curves.
Usage
plotCorrPrecision(rho = c(0, 0.5), n = seq(10, 400, length.out = 100),
conf.int = 0.95, offset=0.025, ...)
Arguments
rho |
single or vector of true correlations. A worst-case precision graph results from rho=0 |
n |
vector of sample sizes to use on the x-axis |
conf.int |
confidence coefficient; default uses 0.95 confidence limits |
offset |
see |
... |
other arguments to |
Author(s)
Xing Wang and Frank Harrell
See Also
Examples
plotCorrPrecision()
plotCorrPrecision(rho=0)
[Package Hmisc version 5.1-3 Index]