par.cor: Partial and semipartial correlation

In miscor: Miscellaneous Functions for the Correlation Coefficient

Description

This function computes the partial or semipartial correlation coefficient between two vaiables. In addition, this function can test the partial or semipartial correlation coefficient for H0: ρ .p = ρ0, so that any value for ρ0 can be specified.

Usage

par.cor(x = NULL, y = NULL, p.xy = NULL, p.x = NULL, p.y = NULL,
        sig = FALSE, rho0 = 0, alternative = c("two.sided", "less", "greater"),
        reduced = FALSE, conf.level = 0.95, digits = 3, output = TRUE)

Arguments

x	a numeric vector.
y	a numeric vector.
p.xy	a numeric vector or data.frame, varialbe(s) residualized from x and y.
p.x	a numeric vector or data.frame, varialbe(s) residualized only from x.
p.y	a numeric vector or data.frame, varialbe(s) residualized only from y.
sig	logical: if TRUE, statistical significance test is conducted.
rho0	a number indicating ρ0, the value under the null hypothesis.
alternative	a character string describing the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".
reduced	logical: if TRUE, compuatation is based on the reduced formula.
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.

Details

Partial correlation is the correlation of x and y while statistically controlling for third variables specified in the argument p.xy. These variables are residualized from x and y using (multiple) regression models. Semipartial correlation is the correlation of x and y while statistically controlling for third variables only for x (specified in the argument p.x) or y (specified in the argument p.y). These variables are residualized from x or y using a (multiple) regression model.

Value

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

call	function call
dat	list with data for x.resid (x residualized), y.resid (y residualized), x, y, p.xy, p.y, and p.x
spec	specification of function argument method
res	list with results, i.e., t or z (test statistic), df (degree of freedom) pval (significance value), r.p (partial or semipartial correlation coefficient), n (sample size), 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.

See Also

test.cor, conf.cor, comptest.cor, seqtest.cor

Examples

dat <- data.frame(x = c(4, 6, 8, 8, 9, 4),
                  y = c(3, 7, 9, 8, 9, 3),
                  z = c(1, 3, 4, 4, 5, 2))

#--------------------------------------
# Partial correlation

par.cor(dat$x, dat$y, p.xy = dat$z)

#--------------------------------------
# Semipartial correlation
# remove z from x

par.cor(dat$x, dat$y, p.x = dat$z)

#--------------------------------------
# Semipartial correlation
# remove z from y

par.cor(dat$x, dat$y, p.y = dat$y)

#--------------------------------------
# Partial correlation: Two-sided test
# H0: rho.p == 0, H1: rho.p != 0

par.cor(dat$x, dat$y, p.xy = dat$z, sig = TRUE)

#--------------------------------------
# Partial correlation: One-sided test
# H0: rho.p <= 0.2, H1: rho.p > 0.2

par.cor(dat$x, dat$y, p.xy = dat$z, sig = TRUE,
        rho0 = 0.4, alternative = "less")

Example output

|---------------------------------------------------------|
| miscor 0.1-1 (2017-04-02)                               |
| Miscellaneous Functions for the Correlation Coefficient |
|---------------------------------------------------------|
[1] 0.6631337
[1] 0.2213242
[1] -0.1541175

Statistical test for the partial correlation coefficient

  H0: rho.p == 0  versus  H1: rho.p != 0 

  t = 1.772, df = 4, p-value = 0.1511

  Sample estimate r.p:      0.663 
     Two-sided 95% CI: [-0.321, 0.959]


Statistical test for the partial correlation coefficient

  H0: rho.p >= 0.4  versus  H1: rho.p < 0.4 

  z = 0.580, p-value = 1.0000

  Sample estimate r.p:      0.663 
     One-sided 95% CI: [-1.000, 0.941]

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