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Computes the standard error for a semipartial correlation

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

Computes the standard error of a semipartial correlation using the estimated semipartial correlation, sample size, and squared multiple correlation for the full model. The full model includes the independent variable of interest and all control variables. The effect size estimate and 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.semipart(cor, r2, n)

Arguments

cor

estimated semipartial correlation

r2

estimated squared multiple correlation for a model that includes the IV and all control variables

n

sample size

Value

Returns a one-row matrix:

  • Estimate - semipartial correlation (from input)

  • SE - standard error

References

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

Examples

se.semipart(.454, .25, 60)
#>                           Estimate      SE
#> Semipartial correlation:     0.454 0.10298

# Should return: 
#                           Estimate      SE
# Semipartial correlation:     0.454 0.10298