statpsych (version 2.0.0)

test.cor: 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)

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

Arguments

cor

estimated correlation

n

sample size

s

number of control variables

h

null hypothesis value of correlation

References

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