compute_gs: Converts Vector of Standardized Mean Differences

In MAd: Meta-Analysis with Mean Differences

Converts Vector of Standardized Mean Differences

Description

Adds g (unbiassed standardized mean difference) to a data.frame. Required inputs are: n.1 (sample size of group one), sd.1 (standard deviation of group one), n.2 (sample size of group two).

Usage

compute_gs(d , var.d , n.1, n.2, data)

Arguments

d	Standardized mean difference (biased).
var.d	Variance of d.
n.1	sample size of group one.
n.2	sample size of group two.
data	data.frame with standardized mean difference, variance of d, sample size of group one, sample size of group two.

Value

g	Unbiased standardized mean difference.
var.g	Variance of g.
se.g	Standard error of g.

Author(s)

AC Del Re & William T. Hoyt

Maintainer: AC Del Re [e-mail]

References

Borenstein (2009). Effect sizes for continuous data. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta analysis (pp. 279-293). New York: Russell Sage Foundation.

See Also

compute_ds, compute_dgs

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)
m.1 <- c(.68,.56,.23,.64,.49,.4,1.49,.53,.58,1.18,.11,1.27,.26,.40,.49,
         .51,.40,.34,.42,.66)
m.2 <- c(.38,.36,.23,.34,.29,.4,1.9,.33,.28,1.1,.111,.27,.21,.140,.149,
         .51,.140,.134,.42,.16)
sd.1 <- c(.28,.26,.23,.44,.49,.34,.39,.33,.58,.38,.31,.27,.26,.40,
          .49,.51,.140,.134,.42,.46)
sd.2 <- c(.28,.26,.23,.44,.49,.44,.39,.33,.58,.38,.51,.27,.26,.40,
          .49,.51,.140,.134,.142,.36)
mod1 <- c(1,2,3,4,1,2,8,7,5,3,9,7,5,4,3,2,3,5,7,1)
mod2 <- factor(c(rep(c(1,2,3,4),5)))
dfs <- data.frame(id, n.1,m.1, sd.1, n.2, m.2, sd.2, mod1, mod2)

# Example

# first compute d
dfs2 <- compute_ds(n.1, m.1, sd.1, n.2, m.2, sd.2, data = dfs)

# now, compute g
compute_gs(d, var.d, n.1, n.2, dfs2)

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