omni: Omnibus Effect Size (Fixed and Random Effects)

View source: R/MAd.R

omniR Documentation

Omnibus Effect Size (Fixed and Random Effects)

Description

Computes fixed and random effects omnibus effect size for correlations.

Usage

omni(g, var, data, type="weighted", method = "random")

Arguments

g

Hedges g (unbiased estimate of d) effect size.

var

Vaiance of g.

type

weighted or unweighted. Default is weighted. Use the unweighted variance method only if Q is rejected and is very large relative to the number of studies in the meta-analysis.

method

Default is random. For fixed effects, use fixed.

data

data.frame with above values.

Details

Depricated function. Use mareg(es~1, var, data) instead.

Value

Fixed and random effects:

k

Number of studies in the meta-analysis.

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.

p

Significance level.

Q

Q-statistic (measure of homogeneity).

df.Q

Degrees of freedom for Q-statistic.

Qp

Q-statistic p-value (assesses overall homogeneity between studies).

I2

Proportion of total variation in effect size that is due to heterogeneity rather than chance (see Shadish & Haddock, 2009; pp. 263).

Author(s)

AC Del Re & William T. Hoyt

Maintainer: AC Del Re acdelre@gmail.com

References

Shadish & Haddock (2009). Analyzing effect sizes: Fixed-effects models. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta analysis (pp. 257-278). New York: Russell Sage Foundation.

Examples

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)))
df<-data.frame(id, n.1,n.2, g, var.g,mod)

# Example

omni(g = g, var = var.g, data = df, type="weighted", method = "random")

MAd documentation built on Aug. 7, 2022, 1:05 a.m.