mareg: Meta-Regression
In MAc: Meta-Analysis with Correlations

Description Usage Arguments Details Value References See Also Examples

Meta-regression function for a single or multiple predictor model. This function is a wrapper for the rma() function in the metafor package (Viechtbauer, W, 2010). Please see https://CRAN.R-project.org/package=metafor for details or for more advanced functionality with the rma() function.

1	mareg(formula, var, data, ztor = FALSE, method = "REML", subset, ...)

`formula`	This is a formula based function, similar to other functions in R (e.g., lm), where the criterion variable (e.g., r or z') is dependent on ('~') the predictor variables (e.g., moderators). The formula for two moderators would take this form: mareg(r ~ mod1 + mod2, var.r, data), where r is the criterion variable predicted by mod1 and mod2. The variance (var) of each r is var.r in this case.
`var`	Variance of r or z'.
`data`	Aggregated `data.frame` (see `agg` function for setting up the dataset for these analyses) with id, es (r or z'), var (variance of r or z') for each study.
`method`	Default is `REML` (Restricted-Maximal Likelihood), which is the standard random effects method. For fixed effects, use `FE`. Other options are specified in the `metafor` package manual ('rma' function).
`ztor`	Default is FALSE. If TRUE, this assumes z' (Fisher's z) was used in the `es` argument and the analyist would like z' to be converted to r (for interpretive purposes) after analyzing in z'.
`subset`	an optional vector specifying a subset of observations to be used in the fitting process.
`...`	Additional arguments to be passed to rma().

See Wolfgang Viechtbauer (2010). metafor: Meta-Analysis Package for R. R package version 1.1-0. for the details of the rma() function. https://CRAN.R-project.org/package=metafor

`estimate`	Unstandardized regression coefficient estimate.
`se`	Standard error of the estimate coefficient.
`z`	z-value.
`ci.l`	Lower 95% confidence interval.
`ci.u`	Upper 95% confidence interval.
`Pr(>\|z\|)`	p-value (significance level).
`QE`	Q-error. Measure of error in the model.
`QE.df`	Degrees of freedom for Q-error.
`QEp`	Q-error p-value (for homogeneity).
`QM`	Q-model. Measure of model fit.
`QM.df`	Degrees of freedom for Q-model.
`QMp`	Q-between p-value (for homogeneity). QM and QMp provide the test of whether the moderator variable(s) account for significant variance among effect sizes.

Wolfgang Viechtbauer (2010). metafor: Meta-Analysis Package for R. R package version 1.1-0. https://CRAN.R-project.org/package=metafor

wd, plotcon

# install metafor
# install.packages('metafor', dependencies = TRUE)

# Sample data
id<-c(1:20)
n<-c(10,20,13,22,28,12,12,36,19,12,36,75,33,121,37,14,40,16,14,20)
r<-c(.68,.56,.23,.64,.49,-.04,.49,.33,.58,.18,-.11,.27,.26,.40,.49,
.51,.40,.34,.42,.16)
mod1<-c(1,2,3,4,1,2,8,7,5,3,9,7,5,4,3,2,3,5,7,1)
dat<-data.frame(id,n,r,mod1)
dat$var.r <- var_r(dat$r, dat$n) # MAc function to derive variance
dat$z <- r_to_z(dat$r)  # MAc function to convert to Fisher's z (z')
dat$var.z <- var_z(dat$n)  # MAc function for variance of z'
dat$mods2 <- factor(rep(1:2, 10))
dat



# Examples

# Random Effects
mareg(r~ mod1 + mods2, var = var.r, method = "REML",  data = dat)

# Fixed Effects
mareg(r~ mod1 + mods2, var = var.r, method = "FE",  data = dat)

   id   n     r mod1      var.r           z       var.z mods2
1   1  10  0.68    1 0.03211264  0.82911404 0.142857143     1
2   2  20  0.56    2 0.02479710  0.63283319 0.058823529     2
3   3  13  0.23    3 0.07474987  0.23418947 0.100000000     1
4   4  22  0.64    4 0.01659867  0.75817374 0.052631579     2
5   5  28  0.49    1 0.02138696  0.53606034 0.040000000     1
6   6  12 -0.04    2 0.09061841 -0.04002135 0.111111111     2
7   7  12  0.49    8 0.05249527  0.53606034 0.111111111     1
8   8  36  0.33    7 0.02268741  0.34282825 0.030303030     2
9   9  19  0.58    5 0.02446472  0.66246271 0.062500000     1
10 10  12  0.18    3 0.08511361  0.18198269 0.111111111     2
11 11  36 -0.11    9 0.02788418 -0.11044692 0.030303030     1
12 12  75  0.27    7 0.01161506  0.27686382 0.013888889     2
13 13  33  0.26    5 0.02716780  0.26610841 0.033333333     1
14 14 121  0.40    4 0.00588000  0.42364893 0.008474576     2
15 15  37  0.49    3 0.01604022  0.53606034 0.029411765     1
16 16  14  0.51    2 0.04211169  0.56272977 0.090909091     2
17 17  40  0.40    3 0.01809231  0.42364893 0.027027027     1
18 18  16  0.34    5 0.05214422  0.35409253 0.076923077     2
19 19  14  0.42    7 0.05217823  0.44769202 0.090909091     1
20 20  20  0.16    1 0.04997133  0.16138670 0.058823529     2
Loading 'metafor' package (version 2.0-0). For an overview 
and introduction to the package please type: help(metafor).

Call:
mareg.default(formula = r ~ mod1 + mods2, var = var.r, data = dat,     method = "REML")

  intrcpt       mod1     mods22  
 0.570902  -0.040419  -0.002163  

Call:
mareg.default(formula = r ~ mod1 + mods2, var = var.r, data = dat,     method = "FE")

  intrcpt       mod1     mods22  
 0.570907  -0.040420  -0.002158