| meta.ave.cor.gen {vcmeta} | R Documentation |
Confidence interval for an average correlation of any type
Description
Computes the estimate, standard error, and confidence interval for an average correlation. Any type of correlation can be used (e.g., Pearson, Spearman, semipartial, factor correlation, Gamma coefficient, Somers d coefficient, tetrachoric, point-biserial, biserial, etc.).
Usage
meta.ave.cor.gen(alpha, cor, se, bystudy = TRUE)
Arguments
alpha |
alpha level for 1-alpha confidence |
cor |
vector of estimated correlations |
se |
vector of standard errors |
bystudy |
logical to also return each study estimate (TRUE) or not |
Value
Returns a matrix. The first row is the average estimate across all studies. If bystudy is TRUE, there is 1 additional row for each study. The matrix has the following columns:
Estimate - estimated effect size
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
References
Bonett DG (2008). “Meta-analytic interval estimation for bivariate correlations.” Psychological Methods, 13(3), 173–181. ISSN 1939-1463, doi:10.1037/a0012868.
Examples
cor <- c(.396, .454, .409, .502, .350)
se <- c(.104, .064, .058, .107, .086)
meta.ave.cor.gen(.05, cor, se, bystudy = TRUE)
# Should return:
# Estimate SE LL UL
# Average 0.4222 0.03853362 0.3438560 0.4947070
# Study 1 0.3960 0.10400000 0.1753200 0.5787904
# Study 2 0.4540 0.06400000 0.3200675 0.5701415
# Study 3 0.4090 0.05800000 0.2893856 0.5160375
# Study 4 0.5020 0.10700000 0.2651183 0.6817343
# Study 5 0.3500 0.08600000 0.1716402 0.5061435