conf.cor: Product-moment correlation coefficient with confidence...

In miscor: Miscellaneous Functions for the Correlation Coefficient

Description

This function computes the product-moment correlation coefficient with two-sided or one-sided confidence interval using Fisher's z tranformation.

Usage

conf.cor(x = NULL, y = NULL, r = NULL, n = NULL,
         alternative = c("two.sided", "less", "greater"),
         conf.level = 0.95, digits = 3, output = TRUE)

Arguments

x	a numeric vector.
y	a numeric vector.
r	alternative specification, product-moment correlation coefficient.
n	alternative specification, number of observations.
alternative	a character string describing the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".
conf.level	confidence level of the interval.
digits	integer indicating the number of decimal places to be displayed.
output	logical; if TRUE, output is shown.

Value

Returns an object of class conf.cor with following entries:

call	function call
dat	data.frame with x and y (if available)
spec	specification of function arguments
res	list with results, i.e., r (correlation coefficient), n, lower (lower limit of CI), upper (upper limit of CI)

Author(s)

Takuya Yanagida [e-mail],

References

Rasch, D., Kubinger, K. D., & Yanagida, T. (2011). Statistics in psychology - Using R and SPSS. New York: John Wiley & Sons.

Kubinger, K. D., Rasch, D., & Simeckova, M. (2007). Testing a correlation coefficient's significance: Using H0: 0 < ρ ≤ λ is preferable to H0: ρ = 0. Psychology Science, 49, 74-87.

See Also

test.cor, seqtest.cor, comptest.cor

Examples

#--------------------------------------
# Two-sided 95% Confidence Interval
# r = 0.55, n = 120

conf.cor(r = 0.55, n = 120)

#--------------------------------------
# One-sided 99% Confidence Interval

# Generate random data
dat <- sim.cor(100, rho = 0.4)

conf.cor(dat$x, dat$y, conf.level = 0.99, alternative = "less")

miscor documentation built on May 1, 2019, 10:14 p.m.