Confidence interval for a semipartial correlation

Source: R/statpsych2.R

Computes a Fisher confidence interval for a population semipartial correlation. This function requires an (unadjusted) estimate of the squared multiple correlation in the full model that contains the predictor variable of interest plus all control variables. This function computes a modified Aloe-Becker confidence interval that uses n - 3 rather than n in the standard error and also uses a Fisher transformation of the semipartial correlation.

ci.spcor(alpha, cor, r2, n)

Arguments

alpha

alpha level for 1-alpha confidence

cor

estimated semipartial correlation

r2

estimated squared multiple correlation in full model

n

sample size

Value

Returns a 1-row matrix. The columns are:

  • Estimate - estimated semipartial correlation (from input)

  • SE - standard error

  • LL - lower limit of the confidence interval

  • UL - upper limit of the confidence interval

References

Aloe AM, Becker BJ (2012). “An effect size for regression predictors in meta-analysis.” Journal of Educational and Behavioral Statistics, 37(2), 278--297. ISSN 1076-9986, doi:10.3102/1076998610396901 .

Examples

ci.spcor(.05, .582, .699, 20)
#>  Estimate        SE        LL        UL
#>     0.582 0.1374298 0.2525662 0.7905182

# Should return:
# Estimate        SE        LL        UL
#    0.582 0.1374298 0.2525662 0.7905182