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

In metacor: Meta-Analysis of Correlation Coefficients

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)

Etienne Laliberté [e-mail] http://www.elaliberte.info/

References

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

See Also

metacor.OP

Examples

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

Example output

Loading required package: rmeta
Loading required package: grid
Loading required package: gsl
$z
 [1] -0.45988001 -0.45283992 -0.39829489 -0.38791384 -0.34188964 -0.13743549
 [7] -0.11668598 -0.10863026 -0.04579188  0.00000000  0.01540579  0.02461536
[13]  0.04063365  0.11097042  0.13568233  0.14035783  0.17247257  0.20369449

$z.var
 [1] 0.014492754 0.005780347 0.030303030 0.025641026 0.003205128 0.025641026
 [7] 0.008771930 0.003039514 0.008547009 0.012987013 0.003401361 0.004219409
[13] 0.003484321 0.043478261 0.010752688 0.030303030 0.022222222 0.003484321

$z.lower
 [1] -0.2239280739 -0.3038266193 -0.0571089538 -0.0740684257 -0.2309285257
 [6]  0.1764099248  0.0668814674 -0.0005739485  0.1354068579  0.2233586255
[11]  0.1297132120  0.1519287006  0.1563266618  0.5196511645  0.3389211294
[16]  0.4815437664  0.4646467547  0.3193875071

$r.lower
 [1] -0.2202587863 -0.2948105768 -0.0570469490 -0.0739332726 -0.2269092556
 [6]  0.1746024353  0.0667819223 -0.0005739484  0.1345853201  0.2197168962
[11]  0.1289905778  0.1507704375  0.1550655497  0.4774307351  0.3265138838
[16]  0.4474791091  0.4338638637  0.3089529969

$z.upper
 [1] -0.69583195 -0.60185322 -0.73948083 -0.70175925 -0.45285075 -0.45128090
 [7] -0.30025342 -0.21668657 -0.22699061 -0.22335863 -0.09890163 -0.10269798
[13] -0.07505937 -0.29771032 -0.06755647 -0.20082811 -0.11970161  0.08800148

$r.upper
 [1] -0.60171548 -0.53836697 -0.62883139 -0.60548326 -0.42423950 -0.42295134
 [7] -0.29154451 -0.21335771 -0.22317077 -0.21971690 -0.09858042 -0.10233845
[13] -0.07491873 -0.28921585 -0.06745388 -0.19817104 -0.11913315  0.08777501

$z.mean
[1] -0.0882517

$r.mean
[1] -0.0880233

$z.mean.se
[1] 0.05245145

$z.mean.lower
[1] 0.01455125

$r.mean.lower
[1] 0.01455022

$z.mean.upper
[1] -0.1910547

$r.mean.upper
[1] -0.1887635

$p
[1] 0.04623201

metacor documentation built on Oct. 2, 2019, 5:03 p.m.