r2: Explained Variance

In MAc: Meta-Analysis with Correlations

Description

Compares tau-squared from empty model (omnibus or overall weighted mean) to model with moderators and provides percentage of explained variance.

Usage

r2(x)

Arguments

x	Will take either a mareg (meta-regression), or macat (single predictor categorical moderator analysis) object and evaluate.

Author(s)

AC Del Re & William T. Hoyt

Maintainer: AC Del Re [e-mail]

Examples

# Sample data
id<-c(1:20)
n.1<-c(10,20,13,22,28,12,12,36,19,12,36,75,33,121,37,14,40,16,14,20)
n.2 <- c(11,22,10,20,25,12,12,36,19,11,34,75,33,120,37,14,40,16,10,21)
g <- c(.68,.56,.23,.64,.49,-.04,1.49,1.33,.58,1.18,-.11,1.27,.26,.40,.49,
.51,.40,.34,.42,1.16)
var.g <- c(.08,.06,.03,.04,.09,.04,.009,.033,.0058,.018,.011,.027,.026,.0040,
.049,.0051,.040,.034,.0042,.016)
mod<-factor(c(rep(c(1,1,2,3),5)))
mods2<-c(rep(1:5,4))
df<-data.frame(id, n.1,n.2, g, var.g,mod, mods2)


# Examples

# mareg fuction
temp <- mareg(g~ mod + mods2, var = var.g, method = "REML", data = df)

r2(temp)

MAc documentation built on May 1, 2019, 10:55 p.m.