metacor.DSL: DerSimonian-Laird (DSL) meta-analytical approach with correlation coefficients as effect sizes

Description

Implements the DerSimonian-Laird (DSL) random-effect meta-analytical approach with correlation coefficients as effect sizes, as described by Schulze (2004).

Usage

metacor.DSL(r, n, labels, alpha = 0.05, plot = TRUE,
   xlim = c(-1, 1), transform = TRUE)

Arguments

vector of correlations

vector of sample sizes

labels

vector of the study names

alpha

alpha-level for the main test and for the confidence intervals

plot

logical; should a forest plot be returned?

xlim

range of the x-axis of the forest plot

transform

logical; should the z-values be back-transformed to r-space?

Value

vector of the z-values

z.var

vector of the variances of each z

z.lower

the lower limits of the confidence intervals for each z

z.upper

the upper limits of the confidence intervals for each z

z.mean

the mean effect size z

r.mean

the mean effect size r, back-transformed from z-space

z.se

the standard error of z.mean

z.mean.lower

the lower limit of the confidence interval for z.mean

r.mean.lower

the lower limit of the confidence interval for r.mean, back-transformed from z-space

z.mean.upper

the upper limit of the confidence interval for z.mean

r.mean.upper

the upper limit of the confidence interval for r.mean, back-transformed from z-space

the p-value for the null hypothesis H0 -> z.mean = 0

References

Schulze, R. (2004) Meta-analysis: a comparison of approaches. Hogrefe & Huber, Gottingen, Germany.

Examples

Run this code

# NOT RUN {
data(lui)
lui <- lui[order(lui$r.FDis),]
test <- metacor.DSL(lui$r.FDis, lui$n, lui$label)
test
# }