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    <title>topic Re: Incorporating measurement error into Dunnetts analysis in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/368655#M61854</link>
    <description>&lt;P&gt;Here are some of my thoughts regarding your situation, realizing you haven't provided enough detail to be a sure. &amp;nbsp;I don't know what a "test" is? &amp;nbsp;Your study is crossed, nested. &amp;nbsp;Meaning test and Variable are crossed and measurements are nested within those. Since you have multiple measures for each test, your measurement precision repeatability is confounded with within test variation. &amp;nbsp;First you would want to determine if your measurement repeatability is consistent. &amp;nbsp; This can be accomplished using range charts. &amp;nbsp;Also , using the range chart can give you an idea about measurement system discrimination (also known as effective resolution). &amp;nbsp;The guidance is to have at least 5 measurement units inside the upper control limit of the range chart. &amp;nbsp;Your example is near the limit of acceptability. &amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Community Stdev Question - XBar of Value.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/31326i93FD8B909FC99228/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Community Stdev Question - XBar of Value.png" alt="Community Stdev Question - XBar of Value.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;If the precision repeatability is consistent and has sufficient discrimination, you can them average those values to reduce the error.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;If you prefer a quantitative approach, you can get variance components for your study (Analyze&amp;gt;Quality and Process&amp;gt;Variability/Attribute Gauge Chart). &amp;nbsp;Put the Y in the Y, Response box and the layers of your sampling tree starting with Variable/Test/Measurement. &amp;nbsp;Select crossed then nested in the Model Type.&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2021-03-17 at 8.07.21 AM.jpg" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/31328i555A36CFC748FC33/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Screen Shot 2021-03-17 at 8.07.21 AM.jpg" alt="Screen Shot 2021-03-17 at 8.07.21 AM.jpg" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;Using the red triangle nest to Variability Gauge, select Variance Components.&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2021-03-17 at 8.08.49 AM.jpg" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/31329iB8B66E5686359D36/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Screen Shot 2021-03-17 at 8.08.49 AM.jpg" alt="Screen Shot 2021-03-17 at 8.08.49 AM.jpg" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;MSA and MSE are acronyms for Measurement System Analysis or Evaluation (See also EMP). &amp;nbsp;These acronyms are typically associated with the work of Wheeler and are a recommended alternative to the traditional gauge R&amp;amp;R study. &amp;nbsp;See here:&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.jmp.com/en_us/whitepapers/jmp/emp-management-systems-analysis.html" target="_blank"&gt;https://www.jmp.com/en_us/whitepapers/jmp/emp-management-systems-analysis.html&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://community.jmp.com/t5/Tutorials/Evaluating-amp-Monitoring-Your-Process-Using-MSA-and-SPC/ta-p/277447" target="_blank"&gt;https://community.jmp.com/t5/Tutorials/Evaluating-amp-Monitoring-Your-Process-Using-MSA-and-SPC/ta-p/277447&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt; &lt;/P&gt;
&lt;P&gt; &lt;/P&gt;</description>
    <pubDate>Wed, 17 Mar 2021 14:14:28 GMT</pubDate>
    <dc:creator>statman</dc:creator>
    <dc:date>2021-03-17T14:14:28Z</dc:date>
    <item>
      <title>Incorporating measurement error into Dunnetts analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/367570#M61746</link>
      <description>&lt;P&gt;I want to start incorporating my measurement error into my dunnetts analysis.&amp;nbsp; I have attached a file below which has two variables which I am trying to determine if they are different.&amp;nbsp; Both variables were tested 3 times and each test was measured 3 times.&amp;nbsp; Since I am trying to determine if the variables are different in the past I've always just averaged all 3 measurements and used as the value for each test in my dunnetts analysis.&amp;nbsp; However I was interested in finding out if there was a way to incorporate the error in my measurements into my analysis.&amp;nbsp; Also, I was hoping for instructions on how to do this for myself since I will be doing this kind of analysis frequently in the future.&amp;nbsp; Thank you.&lt;/P&gt;</description>
      <pubDate>Fri, 09 Jun 2023 22:08:17 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/367570#M61746</guid>
      <dc:creator>wyler0</dc:creator>
      <dc:date>2023-06-09T22:08:17Z</dc:date>
    </item>
    <item>
      <title>Re: Incorporating measurement error into Dunnetts analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/367697#M61761</link>
      <description>&lt;P&gt;Not sure whether I understand you right,&lt;/P&gt;&lt;P&gt;but if you take the raw data for your analysis, you will see the error right in the result of the analysis. So I would take the raw data.&lt;/P&gt;&lt;P&gt;The analysis tells you, if the error is large in comparison to the difference between variables you want to detect.&lt;/P&gt;&lt;P&gt;But of course you need to care about the measurement, it needs to be precise enough to detect the difference you need to detect.&lt;BR /&gt;That's the reason, why you might need to do a MSA before starting real measurements.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sun, 14 Mar 2021 12:28:51 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/367697#M61761</guid>
      <dc:creator>Georg</dc:creator>
      <dc:date>2021-03-14T12:28:51Z</dc:date>
    </item>
    <item>
      <title>Re: Incorporating measurement error into Dunnetts analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/368412#M61831</link>
      <description>&lt;P&gt;Hi Georg,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Sorry for the delayed reply.&amp;nbsp; You mentioned doing an MSA.&amp;nbsp; What is that?&amp;nbsp; I haven't heard that term before.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;What you have suggested is one of the ways I've tried to do this analysis.&amp;nbsp; But the issue I have is that it gives my experiment more power than it actually has.&amp;nbsp; My experiment is looking at whether or not the variables are different.&amp;nbsp; To do determine if this is true I have done 3 tests.&amp;nbsp; So my n=3 for each variable.&amp;nbsp; But if I take all of the measurement values JMP is analyzing the data like my n=9 which it does not.&amp;nbsp; I unfortunately cannot fix the inherent error in my measurements.&amp;nbsp; Looking at it from this perspective is it possible to use all of my measurement points and then manually change the n variable?&lt;/P&gt;</description>
      <pubDate>Tue, 16 Mar 2021 22:26:07 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/368412#M61831</guid>
      <dc:creator>wyler0</dc:creator>
      <dc:date>2021-03-16T22:26:07Z</dc:date>
    </item>
    <item>
      <title>Re: Incorporating measurement error into Dunnetts analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/368655#M61854</link>
      <description>&lt;P&gt;Here are some of my thoughts regarding your situation, realizing you haven't provided enough detail to be a sure. &amp;nbsp;I don't know what a "test" is? &amp;nbsp;Your study is crossed, nested. &amp;nbsp;Meaning test and Variable are crossed and measurements are nested within those. Since you have multiple measures for each test, your measurement precision repeatability is confounded with within test variation. &amp;nbsp;First you would want to determine if your measurement repeatability is consistent. &amp;nbsp; This can be accomplished using range charts. &amp;nbsp;Also , using the range chart can give you an idea about measurement system discrimination (also known as effective resolution). &amp;nbsp;The guidance is to have at least 5 measurement units inside the upper control limit of the range chart. &amp;nbsp;Your example is near the limit of acceptability. &amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Community Stdev Question - XBar of Value.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/31326i93FD8B909FC99228/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Community Stdev Question - XBar of Value.png" alt="Community Stdev Question - XBar of Value.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;If the precision repeatability is consistent and has sufficient discrimination, you can them average those values to reduce the error.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;If you prefer a quantitative approach, you can get variance components for your study (Analyze&amp;gt;Quality and Process&amp;gt;Variability/Attribute Gauge Chart). &amp;nbsp;Put the Y in the Y, Response box and the layers of your sampling tree starting with Variable/Test/Measurement. &amp;nbsp;Select crossed then nested in the Model Type.&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2021-03-17 at 8.07.21 AM.jpg" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/31328i555A36CFC748FC33/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Screen Shot 2021-03-17 at 8.07.21 AM.jpg" alt="Screen Shot 2021-03-17 at 8.07.21 AM.jpg" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;Using the red triangle nest to Variability Gauge, select Variance Components.&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2021-03-17 at 8.08.49 AM.jpg" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/31329iB8B66E5686359D36/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Screen Shot 2021-03-17 at 8.08.49 AM.jpg" alt="Screen Shot 2021-03-17 at 8.08.49 AM.jpg" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;MSA and MSE are acronyms for Measurement System Analysis or Evaluation (See also EMP). &amp;nbsp;These acronyms are typically associated with the work of Wheeler and are a recommended alternative to the traditional gauge R&amp;amp;R study. &amp;nbsp;See here:&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.jmp.com/en_us/whitepapers/jmp/emp-management-systems-analysis.html" target="_blank"&gt;https://www.jmp.com/en_us/whitepapers/jmp/emp-management-systems-analysis.html&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://community.jmp.com/t5/Tutorials/Evaluating-amp-Monitoring-Your-Process-Using-MSA-and-SPC/ta-p/277447" target="_blank"&gt;https://community.jmp.com/t5/Tutorials/Evaluating-amp-Monitoring-Your-Process-Using-MSA-and-SPC/ta-p/277447&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt; &lt;/P&gt;
&lt;P&gt; &lt;/P&gt;</description>
      <pubDate>Wed, 17 Mar 2021 14:14:28 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/368655#M61854</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2021-03-17T14:14:28Z</dc:date>
    </item>
    <item>
      <title>Re: Incorporating measurement error into Dunnetts analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/368810#M61869</link>
      <description>&lt;P&gt;Thanks for the reply Statman.&amp;nbsp; I will start trying to do some statistical analysis of my values.&amp;nbsp; But it looks like I might want to look into cleaning up the variability in my values.&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 17 Mar 2021 22:23:54 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Incorporating-measurement-error-into-Dunnetts-analysis/m-p/368810#M61869</guid>
      <dc:creator>wyler0</dc:creator>
      <dc:date>2021-03-17T22:23:54Z</dc:date>
    </item>
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