MOTE (version 1.0.2)

d.dep.t.avg: d for Dependent t with Average SD Denominator

Description

This function displays d and the non-central confidence interval for repeated measures data, using the average standard deviation of each level as the denominator.

Usage

d.dep.t.avg(m1, m2, sd1, sd2, n, a = 0.05)

Arguments

m1

mean from first level

m2

mean from second level

sd1

standard deviation from first level

sd2

standard deviation from second level

n

sample size

a

significance level

Value

The effect size (Cohen's d) with associated confidence intervals, the confidence intervals associated with the means of each group, standard deviations of the means for each group.

d

effect size

dlow

lower level confidence interval d value

dhigh

upper level confidence interval d value

M1/M2

mean one and two

M1low/M2low

lower level confidence interval of mean one or two

M1high/M2high

upper level confidence interval of mean one or two

sd1/sd2

standard deviation of mean one and two

se1/se2

standard error of mean one and two

n

sample size

df

degrees of freedom (sample size - 1)

estimate

the d statistic and confidence interval in APA style for markdown printing

Details

To calculate d, mean two is subtracted from mean one, which is then divided by the average standard deviation.

d_av = (m1 - m2) / ((sd1 + sd2) / 2)

Learn more on our example page.

Examples

# NOT RUN {
#The following example is derived from the "dept_data" dataset included
#in the MOTE library.

#In a study to test the effects of science fiction movies on people's
#belief in the supernatural, seven people completed a measure of belief
#in the supernatural before and after watching a popular science fiction
#movie. Higher scores indicated higher levels of belief.

    t.test(dept_data$before, dept_data$after, paired = TRUE)

#You can type in the numbers directly, or refer to the dataset,
#as shown below.

    d.dep.t.avg(m1 = 5.57, m2 = 4.43, sd1 = 1.99,
                sd2 = 2.88, n = 7, a = .05)

    d.dep.t.avg(5.57, 4.43, 1.99, 2.88, 7, .05)

    d.dep.t.avg(mean(dept_data$before), mean(dept_data$after),
                sd(dept_data$before), sd(dept_data$after),
                length(dept_data$before), .05)

#The mean measure of belief on the pretest was 5.57, with a standard
#deviation of 1.99. The posttest scores appeared lower (M = 4.43, SD = 2.88)
#but the dependent t-test was not significant using alpha = .05,
#t(7) = 1.43, p = .203, d_av = 0.47. The effect size was a medium effect suggesting
#that the movie may have influenced belief in the supernatural.
# }