dPPC2 {MDMA}

Effect sizes from pretest-posttest-control group designs

Description

dPPC2 calculates an effect size for studies with pretest and posttest scores for two groups, usually a treatment and a control group. It is based on Morris (2008), who based it on Becker (1988).

Usage

dPPC2(preT, posT, preC, posC, correct = TRUE, CIlevel = 0.95)

Arguments

preT

pre-scores for treatment group.

posT

post-scores for treatment group.

preC

pre-scores for control group.

posC

post-scores for control group.

correct

indicates whether a correction factor should be calculated (i.e., Hedges' g instead of Cohen's d).

CIlevel

the confidence level required.

Value

dPPC2 returns a vector of length 6, containing:

d

the effect size estimate.

SE

the standard error of the effect sie estimate.

lower.bound

lower bound of the confidence interval.

upper.bound

upper bound of the confidence interval.

NT

sample size of treatment group.

NC

sample size of control group.

Author(s)

Mathijs Deen

References

• Becker, B.J. (1988). Synthesizing standardized mean-change measures. British Journal of Mathematical and Statistical Psychology, 41, 257-278.

• Morris, S.B. (2008). Estimating effect sizes from pretest-posttest-control group designs. Organizational Research Methods, 11, 364-386.

Examples

library(MASS)
set.seed(1)
treatment <- mvrnorm(n=50, mu=c(50,40), Sigma = matrix(c(100,70,70,100), ncol=2), empirical = TRUE)
control <- mvrnorm(n=50, mu=c(50,45), Sigma = matrix(c(100,70,70,100), ncol=2), empirical = TRUE)
dPPC2(treatment[,1], treatment[,2], control[,1], control[,2])