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anova_rm.html
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anova_rm.html
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<!DOCTYPE html>
<html>
<head>
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<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<title>EZ Statistics: Repeated Measures ANOVA</title>
<meta name="description" content="EZ Statistics Repeated Measures ANOVA">
<link rel="stylesheet" href="style/stats.css">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.4/jquery.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery-csv/0.71/jquery.csv-0.71.min.js"></script>
<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
<script src="jstat.js"></script>
<script src="ezstatistics-0.30.js"></script>
</head>
<body>
<center><img class="round" src="style/logo.png" height="105"/></center>
<div style="text-align: right"><a href="index.html">Back to main page</a></div>
<h3 class="f18b">Repeated Measures Analysis of Variance (ANOVA)</h3>
Requires that the samples are related (dependent) and normally distributed. You can read more about the test
at <a href="https://statistics.laerd.com/statistical-guides/repeated-measures-anova-statistical-guide.php" target="_blank">Laerd Statistics</a>
or <a href="http://www.real-statistics.com/anova-repeated-measures/repeated-measures-anova-tool/" target="_blank">Real Statistics</a>.
<br> <br>
Tests the hypotheses:
<table>
<tr>
<th class="dark" width="30">H<sub>0</sub></th>
<td class="border">The means of the samples are equal </td>
</tr>
<tr>
<th class="dark">H<sub>1</sub></th>
<td class="border">The means of the samples are different </td>
</tr>
</table>
<div class="smalltext">
<div class="label16">
<h3 class="f16"> Data Entry</h3>
</div>
<br/>
<table>
<tr>
<td width="110">No samples:</td>
<td><input class="value" name="no" id="no" value="4"> <button onclick="javascript:update_no_samples()">Update</button></td>
</tr>
</table>
<table id="samples">
<tr>
<td width="110">Sample A:</td>
<td><input class="sample" name="sampA" id="samp1" value="16,12,23,8,3,5,19,22,12,16,14,24,9,3,2"></td>
</tr>
<tr>
<td width="110">Sample B:</td>
<td><input class="sample" name="sampB" id="samp2" value="22,18,24,20,12,13,22,22,20,22,25,26,12,9,8"></td>
</tr>
<tr>
<td width="110">Sample C:</td>
<td><input class="sample" name="sampC" id="samp3" value="23,24,26,28,13,11,25,23,22,26,18,21,20,13,6"></td>
</tr>
<tr>
<td width="110">Sample D:</td>
<td><input class="sample" name="sampD" id="samp4" value="25,29,27,30,17,15,26,26,24,29,21,23,23,16,10"></td>
</tr>
</table>
<table>
<tr>
<td width="110">Significance level α</td>
<td><input class="value" name="alpha" id="alpha" value="0.05"></td>
</tr>
<tr>
<td width="110">Upload CSV file:</td>
<td>
<input type="file" name="File Upload" id="txtFileUpload" accept=".csv" />
</td>
</tr>
<tr>
<td width="110">Post-test:</td>
<td>
<select name="posttest" id="posttest">
<option value="tukeys">Tukey's HSD</option>
</select>
Correction:
<select name="correction" id="correction">
<option value="none">None</option>
<option value="bonferroni">Bonferroni</option>
</select>
</td>
</tr>
</table>
<br>
<button class="test" onclick="javascript:run_rm_anova()">Run Test</button>
<button class="clear" onclick="javascript:clear_fields(-1)">Clear</button>
<div id="error">
</div>
<div id="test_results" style="display: none;">
<div class="label16">
<h3 class="f16"> Test Result</h3>
</div>
<br/>
<table class="border">
<thead>
<tr>
<th colspan=4 class="dark">Data Summary</th>
</tr>
<tr>
<th class="dark" width="70">Sample</th>
<th class="dark" width="40">N</th>
<th class="dark" width="100">Mean</th>
<th class="dark" width="100">Stdev</th>
</tr>
</thead>
<tbody id ="summary">
<tr>
<th class="dark">A</th>
<td class="border" id="n1"> </td>
<td class="border" id="mean1"> </td>
<td class="border" id="stdev1"> </td>
</tr>
<tr>
<th class="dark">B</th>
<td class="border" id="n2"> </td>
<td class="border" id="mean2"> </td>
<td class="border" id="stdev2"> </td>
</tr>
<tr>
<th class="dark">C</th>
<td class="border" id="n3"> </td>
<td class="border" id="mean3"> </td>
<td class="border" id="stdev3"> </td>
</tr>
<tr>
<th class="dark">D</th>
<td class="border" id="n4"> </td>
<td class="border" id="mean4"> </td>
<td class="border" id="stdev4"> </td>
</tr>
</tbody>
</table>
<br>
<table class="border">
<thead>
<tr>
<th class="dark" width="550" colspan="2">Result</th>
</tr>
</thead>
<tbody>
<tr>
<td class="dark" width="130"><b>Significance level α:</b></td>
<td class="border" width="420" id="sign_level"> </td>
</tr>
<tr>
<td class="dark"><b>P-value:</b></td>
<td class="border" id="p"> </td>
</tr>
<tr>
<td class="dark"><b>F-score:</b></td>
<td class="border" id="f"> </td>
</tr>
<tr>
<td class="dark"><b>Result:</b></td>
<td class="border" id="res"> </td>
</tr>
</tbody>
</table>
<br>
<div id="postres">
<div class="label16">
<h3 class="f16"> Post-test</h3>
</div>
<br/>
The post-test shows which pairs of samples that have different means (if any).
<div id="post">
</div>
</div>
<div id="assumptions">
<div class="label16">
<h3 class="f16"> Check test assumptions <button class="help" onclick="javascript:toggle('ashelp')";>?</button></h3>
</div>
<div id="ashelp" style="display: none;">
<br>
The samples should be normally distributed. If not, consider using the <a href="friedman.html">Friedman test</a> instead.
Note that the normality test is not entirely accurate for sample sizes under 20.
</div>
<br>
<div id="normtest">
<table class="border">
<thead>
<tr>
<th class="dark" width="550" colspan="2">Shapiro-Wilk test for normally distributed samples</th>
</tr>
</thead>
<tbody id="normtest_cont">
</tbody>
</table>
</div>
</div>
<div id="viz">
<div class="label16">
<h3 class="f16"> Data Visualization</h3>
</div>
<div id="chart"></div>
</div>
</div>
</div>
</body>
</html>