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Hypothesis test for a Pearson or partial correlation

Source: R/statpsych2.R
test.cor.Rd

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

Bonett DG (2021). Statistical Methods for Psychologists https://dgbonett.sites.ucsc.edu/.

Examples

test.cor(.484, 100, 0, .2)
#>  Estimate      z p
#>     0.484 3.2054 0

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


test.cor(.372, 100, 0, 0)
#>  Estimate      t df       p
#>     0.372 3.9673 98 0.00014

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