Computes the standard error for a Spearman correlation

Computes the Bonett-Wright standard error of a Spearman correlation using the estimated Spearman correlation and sample size. The standard error 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.spear(cor, n)

Arguments

cor

estimated Spearman correlation

n

sample size

Value

Returns a one-row matrix:

• Estimate - Spearman correlation (from input)

• SE - standard error

References

Bonett DG, Wright TA (2000). “Sample size requirements for estimating Pearson, Kendall and Spearman correlations.” Psychometrika, 65(1), 23–28. ISSN 0033-3123, doi:10.1007/BF02294183 .

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

Examples

se.spear(.427, 55)
#>                        Estimate      SE
#> Spearman correlation:     0.427 0.11845

# Should return: 
#                       Estimate      SE
# Spearman correlation:    0.427 0.11845