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<table width="100%" summary="page for d.dep.t.avg"><tr><td>d.dep.t.avg</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>d for Dependent t with Average SD Denominator</h2>

<h3>Description</h3>

<p>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.
</p>


<h3>Usage</h3>

<pre>
d.dep.t.avg(m1, m2, sd1, sd2, n, a = 0.05)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>m1</code></td>
<td>
<p>mean from first level</p>
</td></tr>
<tr valign="top"><td><code>m2</code></td>
<td>
<p>mean from second level</p>
</td></tr>
<tr valign="top"><td><code>sd1</code></td>
<td>
<p>standard deviation from first level</p>
</td></tr>
<tr valign="top"><td><code>sd2</code></td>
<td>
<p>standard deviation from second level</p>
</td></tr>
<tr valign="top"><td><code>n</code></td>
<td>
<p>sample size</p>
</td></tr>
<tr valign="top"><td><code>a</code></td>
<td>
<p>significance level</p>
</td></tr>
</table>


<h3>Details</h3>

<p>To calculate d, mean two is subtracted from mean one, which is then
divided by the average standard deviation.
</p>
<p>d_av = (m1 - m2) / ((sd1 + sd2) / 2)
</p>
<p><a href="https://www.aggieerin.com/shiny-server/tests/deptavgm.html">Learn more on our example page.</a>
</p>


<h3>Value</h3>

<p>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.
</p>
<table summary="R valueblock">
<tr valign="top"><td><code>d</code></td>
<td>
<p>effect size</p>
</td></tr>
<tr valign="top"><td><code>dlow</code></td>
<td>
<p>lower level confidence interval d value</p>
</td></tr>
<tr valign="top"><td><code>dhigh</code></td>
<td>
<p>upper level confidence interval d value</p>
</td></tr>
<tr valign="top"><td><code>M1/M2</code></td>
<td>
<p>mean one and two</p>
</td></tr>
<tr valign="top"><td><code>M1low/M2low</code></td>
<td>
<p>lower level confidence interval of mean one or two</p>
</td></tr>
<tr valign="top"><td><code>M1high/M2high</code></td>
<td>
<p>upper level confidence interval of mean one or two</p>
</td></tr>
<tr valign="top"><td><code>sd1/sd2</code></td>
<td>
<p>standard deviation of mean one and two</p>
</td></tr>
<tr valign="top"><td><code>se1/se2</code></td>
<td>
<p>standard error of mean one and two</p>
</td></tr>
<tr valign="top"><td><code>n</code></td>
<td>
<p>sample size</p>
</td></tr>
<tr valign="top"><td><code>df</code></td>
<td>
<p>degrees of freedom (sample size - 1)</p>
</td></tr>
<tr valign="top"><td><code>estimate</code></td>
<td>
<p>the d statistic and confidence interval in APA style for markdown printing</p>
</td></tr>
</table>


<h3>Examples</h3>

<pre>

#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.
</pre>


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