# d.dep.t.avg: d for Dependent t with Average SD Denominator In MOTE: Effect Size and Confidence Interval Calculator

## 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

 `1` ```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

## 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)

## 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

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27``` ```#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. ```

MOTE documentation built on May 2, 2019, 5:51 a.m.