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]