test.cor: Hypothesis test for a Pearson or partial correlation

In statpsych: Statistical Methods for Psychologists

Hypothesis test for a Pearson or partial correlation

Description

Computes a t test for a test of the null hypothesis that a population Pearson or partial correlations is equal to 0, or a z test using a Fisher transformation for a test of the null hypothesis that a Pearson or partial correlation is equal to some specified nonzero value. Set s = 0 for a Pearson correlation. The hypothesis testing results should be accompanied with a confidence interval for the population Pearson or partial correlation value (see ci.cor).

For more details, see Section 1.19 of Bonett (2021, Volume 2)

Usage

test.cor(cor, n, s, h)

Arguments

cor	estimated correlation
n	sample size
s	number of control variables
h	null hypothesis value of correlation

Value

Returns a 1-row matrix. The columns are:

• Estimate - estimate of correlation

• t or z - t test statistic (for h = 0) or z test statistic (for nonzero h)

• p - two-sided p-value

References

\insertRef

Bonett2021statpsych

Examples

test.cor(.484, 100, 0, .2)

# Should return:
# Estimate      z       p
#    0.484 3.2054 0.00135


test.cor(.372, 100, 0, 0)

# Should return:
#  Estimate      t df       p
#     0.372 3.9673 98 0.00014

statpsych documentation built on Jan. 13, 2026, 1:07 a.m.