MBESS (version 4.6.0)

smd.c: Standardized mean difference using the control group as the basis of standardization

Description

Function to calculate the standardized mean difference (regular or unbiased) using the control group standard deviation as the basis of standardization (for either raw data or summary measures).

Usage

smd.c(Group.T = NULL, Group.C = NULL, Mean.T = NULL, Mean.C = NULL, 
s.C = NULL, n.C = NULL, Unbiased=FALSE)

Arguments

Group.T

Raw data for the treatment group.

Group.C

Raw data for the control group.

Mean.T

The mean of the treatment group.

Mean.C

The mean of the control group.

s.C

The standard deviation of the control group (i.e., the square root of the unbiased estimator of the population variance).

n.C

The sample size of the control group.

Unbiased

Returns the unbiased estimate of the standardized mean difference using the standard deviation of the control group.

Value

Returns the estimated standardized mean difference using the control group standard deviation as the basis of standardization.

Details

When Unbiased=TRUE, the unbiased estimate of the standardized mean difference (using the control group as the basis of standardization) is returned (Hedges, 1981). Although the unbiased estimate of the standardized mean difference is not often reported, at least at the present time, it is nevertheless made available to those who are interested in calculating this quantity.

References

Hedges, L. V. (1981). Distribution theory for Glass's Estimator of effect size and related estimators. Journal of Educational Statistics, 2, 107--128.

Glass, G. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5, 3--8.

See Also

smd, conf.limits.nct

Examples

# NOT RUN {
# Generate sample data.
set.seed(113)
g.T <- rnorm(n=25, mean=.5, sd=1)
g.C <- rnorm(n=25, mean=0, sd=1)
smd.c(Group.T=g.T, Group.C=g.C)

M.T <- .66745
M.C <- .24878
sd.c <- 1.1311
n.c <- 25
smd.c(Mean.T=M.T, Mean.C=M.C, s=sd.c)
smd.c(Mean.T=M.T, Mean.C=M.C, s=sd.c, n.C=n.c, Unbiased=TRUE)
# }