| ci.pbcor {statpsych} | R Documentation |
Confidence interval for a point-biserial correlation
Description
Computes confidence intervals for two types of population point-biserial correlations. One type uses a weighted average of the group variances and is appropriate for nonexperimental designs with simple random sampling (but not stratified random sampling). The other type uses an unweighted average of the group variances and is appropriate for experimental designs. Equality of variances is not assumed for either type.
Usage
ci.pbcor(alpha, m1, m2, sd1, sd2, n1, n2)
Arguments
alpha |
alpha level for 1-alpha confidence |
m1 |
estimated mean for group 1 |
m2 |
estimated mean for group 2 |
sd1 |
estimated standard deviation for group 1 |
sd2 |
estimated standard deviation for group 2 |
n1 |
sample size for group 1 |
n2 |
sample size for group 2 |
Value
Returns a 2-row matrix. The columns are:
Estimate - estimated point-biserial correlation
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
References
Bonett DG (2020). “Point-biserial correlation: Interval estimation, hypothesis testing, meta-analysis, and sample size determination.” British Journal of Mathematical and Statistical Psychology, 73(S1), 113–144. ISSN 0007-1102, doi:10.1111/bmsp.12189.
Examples
ci.pbcor(.05, 28.32, 21.48, 3.81, 3.09, 40, 40)
# Should return:
# Estimate SE LL UL
# Weighted: 0.7065799 0.04890959 0.5885458 0.7854471
# Unweighted: 0.7020871 0.05018596 0.5808366 0.7828948