Hmisc: plotCorrPrecision – R documentation

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plotCorrPrecision

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 = 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 `labcurve`
`...`	other arguments to `labcurve`

Author(s)

Xing Wang and Frank Harrell

Examples

plotCorrPrecision()
plotCorrPrecision(rho=0)

Hmisc

Harrell Miscellaneous

v4.5-0

GPL (>= 2)

Authors

Frank E Harrell Jr <fh@fharrell.com>, with contributions from Charles Dupont and many others.

Initial release

2021-02-27