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Last data update: 2014.03.03

R: DerSimonian-Laird (DSL) meta-analytical approach with...

metacor.DSL

R Documentation

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

`r`	vector of correlations
`n`	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

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

Author(s)

References

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

Examples

data(lui)
lui <- lui[order(lui$r.FDis),]
test <- metacor.DSL(lui$r.FDis, lui$n, lui$label)
test