| ci.spcor {statpsych} | R Documentation |
Confidence interval for a semipartial correlation
Description
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.
Usage
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)
# Should return:
# Estimate SE LL UL
# 0.582 0.1374298 0.2525662 0.7905182