MAd (version 0.8-3)

macatC: Direct Categorical Moderator Comparison

Description

Function for a planned comparison between two levels of a moderator under a fixed or random effects model.

Usage

macatC(x1, x2, g, var, mod, data, method= "random", type= "post.hoc")

Value

diff

Mean difference between the two levels.

var.diff

Variance of diff.

p

Significance level.

Arguments

x1

One level of categorical moderator.

x2

Comparison level of same categorical moderator.

g

Hedges g (unbiased estimate of d) effect size.

var

Vaiance of g.

mod

Categorical moderator variable used for moderator analysis.

method

Default is random. For fixed effects, use fixed.

type

post.hoc assumes the comparison was not planned prior to conducting the meta analysis. The a priori option, planned, assumes the researcher planned to conduct the analysis a priori. Default is post.hoc using the Scheffe post hoc statistical method.

data

data.frame with values above.

Author

AC Del Re & William T. Hoyt

Maintainer: AC Del Re

Details

See Konstantopoulos & Hedges (2009; pp. 280-288) for the computations used in this function.

References

Konstantopoulos & Hedges (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. 279-293). New York: Russell Sage Foundation.

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.

See Also

macat,

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
macatC(1, 2, g=g, var=var.g, mod=mod, data=df,  method= "random", 
  type= "post.hoc")