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Computes the standard error for a Pearson or partial correlation

Source: R/meta_se.R
se.cor.Rd

Computes the standard error of a Pearson or partial correlation using the estimated correlation, sample size, and number of control variables. The correlation, along with the standard error output from this function, can be used as input in the meta.ave.cor.gen function in applications where a combination of different types of compatible correlations are used in the meta-analysis.

For more details, see Chapter 1 of Bonett (2021, Volume 5)

Usage

se.cor(cor, s, n)

Arguments

cor

estimated Pearson or partial correlation

s

number of control variables (set to 0 for Pearson)

n

sample size

Value

Returns a one-row matrix:

  • Estimate - Pearson or partial correlation (from input)

  • SE - standard error

References

Bonett DG (2008). “Meta-analytic interval estimation for bivariate correlations.” Psychological Methods, 13(3), 173–181. ISSN 1939-1463, doi:10.1037/a0012868 .

Bonett DG (2021). Statistical Methods for Psychologists, Vol 1-5, https://dgbonett.sites.ucsc.edu/.

Examples

se.cor(.427, 0, 55)
#>               Estimate      SE
#> Correlation:     0.427 0.11339

# Should return: 
#               Estimate      SE
# Correlation:     0.427 0.11339

se.cor(.283, 4, 80)
#>               Estimate      SE
#> Correlation:     0.283 0.10767
# Should return: 
#               Estimate      SE
# Correlation:     0.283 0.10767