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    <title>topic Re: Question about Response Surface and Blocking in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Question-about-Response-Surface-and-Blocking/m-p/887346#M104946</link>
    <description>&lt;P&gt;First, welcome to the community!&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I don't understand what you mean by "&lt;SPAN&gt;won't be able to &lt;STRONG&gt;test&lt;/STRONG&gt; all the samples in one day"? &amp;nbsp;I assume the samples are experimental units. &amp;nbsp;Are you concerned about the measurement process or measurement error? &amp;nbsp;Do you think the experimental units will change (e.g., degrade) with time? &amp;nbsp;Are you experimenting with factors in the measurement process?&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I don't know the situation enough to provide specific advice, but here are my thoughts, in general. &amp;nbsp;Blocking is a strategy to handle noise factors in an experiment situation. &amp;nbsp;If you are doing response surface types of designs (e.g., optimization type designs), you are optimizing levels for factors already discovered to be of interest from previous study. &amp;nbsp;IMHO, you should already know the effects of noise BEFORE conducting RSM. &amp;nbsp;If you don't your inference space will be insufficient to use a more complex model provided via RSM. &amp;nbsp;Your process should be consistent and stable before optimization.&lt;/P&gt;</description>
    <pubDate>Tue, 15 Jul 2025 21:48:35 GMT</pubDate>
    <dc:creator>statman</dc:creator>
    <dc:date>2025-07-15T21:48:35Z</dc:date>
    <item>
      <title>Question about Response Surface and Blocking</title>
      <link>https://community.jmp.com/t5/Discussions/Question-about-Response-Surface-and-Blocking/m-p/887326#M104944</link>
      <description>&lt;P&gt;Hi JMP Community,&lt;BR /&gt;I am interested in conducting RSM studies for two factors using CCD Orthogonal setup including 3 replicates. After finishing the setup, I get 52 as my total sample size. However, I won't be able to test all the samples in one day. I wanted to ask if it is possible to combine blocking with RSM. I also tried using CCD Orthogonal blocking, but it's only giving me two blocks since I am testing the factors at two levels - low and high.&amp;nbsp;&lt;BR /&gt;I have played with custom DOE designing. However, with custom DOE, I don't get similar levels that are bested tested in my RSM setup.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Any help would be greatly appreciated.&lt;/P&gt;
&lt;P&gt;Thank you.&lt;/P&gt;</description>
      <pubDate>Tue, 15 Jul 2025 21:35:53 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Question-about-Response-Surface-and-Blocking/m-p/887326#M104944</guid>
      <dc:creator>BetaAdjustment6</dc:creator>
      <dc:date>2025-07-15T21:35:53Z</dc:date>
    </item>
    <item>
      <title>Re: Question about Response Surface and Blocking</title>
      <link>https://community.jmp.com/t5/Discussions/Question-about-Response-Surface-and-Blocking/m-p/887346#M104946</link>
      <description>&lt;P&gt;First, welcome to the community!&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I don't understand what you mean by "&lt;SPAN&gt;won't be able to &lt;STRONG&gt;test&lt;/STRONG&gt; all the samples in one day"? &amp;nbsp;I assume the samples are experimental units. &amp;nbsp;Are you concerned about the measurement process or measurement error? &amp;nbsp;Do you think the experimental units will change (e.g., degrade) with time? &amp;nbsp;Are you experimenting with factors in the measurement process?&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I don't know the situation enough to provide specific advice, but here are my thoughts, in general. &amp;nbsp;Blocking is a strategy to handle noise factors in an experiment situation. &amp;nbsp;If you are doing response surface types of designs (e.g., optimization type designs), you are optimizing levels for factors already discovered to be of interest from previous study. &amp;nbsp;IMHO, you should already know the effects of noise BEFORE conducting RSM. &amp;nbsp;If you don't your inference space will be insufficient to use a more complex model provided via RSM. &amp;nbsp;Your process should be consistent and stable before optimization.&lt;/P&gt;</description>
      <pubDate>Tue, 15 Jul 2025 21:48:35 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Question-about-Response-Surface-and-Blocking/m-p/887346#M104946</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2025-07-15T21:48:35Z</dc:date>
    </item>
    <item>
      <title>Re: Question about Response Surface and Blocking</title>
      <link>https://community.jmp.com/t5/Discussions/Question-about-Response-Surface-and-Blocking/m-p/887398#M104951</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/72160"&gt;@BetaAdjustment6&lt;/a&gt;,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Welcome in the Community !&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Just some questions and clarifications from my side to continue the discussion :&lt;/P&gt;
&lt;P&gt;You mentioned your DoE setup includes 3 replicates, for a total of 52runs. That means you have 13 runs per "whole design structure".&lt;/P&gt;
&lt;P&gt;Can you run 13 runs in one day ? Or 26 ?&lt;/P&gt;
&lt;P&gt;If yes, you could maybe split the runs by respecting the design structure and the replicates, and add a blocking factor for the replicate number (depending on the number of design structures you're able to run in one day, either a 2-level blocking factor if you're able to run 26runs in one day, or a 4-levels blocking factor if you're able to run 13 runs in one day).&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;There are also other options :&lt;/P&gt;
&lt;UL&gt;
&lt;LI&gt;Use&amp;nbsp;&lt;A href="https://www.jmp.com/support/help/en/18.1/#page/jmp/custom-designs.shtml?_gl=1*1gu50l2*_up*MQ..*_ga*MjA0MzEyMDY2OC4xNzUyNjU2Mzgy*_ga_BRNVBEC1RS*czE3NTI2NTYzODEkbzEkZzAkdDE3NTI2NTYzODEkajYwJGwwJGgw#" target="_blank" rel="noopener"&gt;Custom Designs&lt;/A&gt; and specify a RSM model with a blocking factor (and the number of runs per block/day you're able to run). But Custom design may only provide axial points with values -1 and 1 (so a Face-Centered Central Composite Design :&amp;nbsp;&lt;A href="https://www.itl.nist.gov/div898/handbook/pri/section3/pri3361.htm" target="_blank" rel="noopener"&gt;https://www.itl.nist.gov/div898/handbook/pri/section3/pri3361.htm&lt;/A&gt;)&lt;/LI&gt;
&lt;LI&gt;You can also create your CCD Orthogonal design, and use the platform &lt;A href="https://www.jmp.com/support/help/en/18.1/#page/jmp/custom-designs.shtml?_gl=1*1gu50l2*_up*MQ..*_ga*MjA0MzEyMDY2OC4xNzUyNjU2Mzgy*_ga_BRNVBEC1RS*czE3NTI2NTYzODEkbzEkZzAkdDE3NTI2NTYzODEkajYwJGwwJGgw#" target="_blank" rel="noopener"&gt;Custom Designs&lt;/A&gt;&amp;nbsp;to introduce a blocking factor.
&lt;OL&gt;
&lt;LI&gt;First, create the CCD design with replicates.&lt;/LI&gt;
&lt;LI&gt;Then, use the &lt;A href="https://www.jmp.com/support/help/en/18.1/#page/jmp/custom-designs.shtml?_gl=1*1gu50l2*_up*MQ..*_ga*MjA0MzEyMDY2OC4xNzUyNjU2Mzgy*_ga_BRNVBEC1RS*czE3NTI2NTYzODEkbzEkZzAkdDE3NTI2NTYzODEkajYwJGwwJGgw#" target="_blank" rel="noopener"&gt;Custom Designs&lt;/A&gt; platform and select your covariates&amp;nbsp;&lt;A href="https://www.jmp.com/support/help/en/18.1/index.shtml#page/jmp/factors.shtml#" target="_blank" rel="noopener noreferrer"&gt;Factors&lt;/A&gt;&amp;nbsp;to import your design table :&lt;BR /&gt;&lt;SPAN class="lia-inline-image-display-wrapper lia-image-align-inline"&gt;&lt;SPAN class="lia-message-image-wrapper lia-message-image-actions-narrow lia-message-image-actions-below"&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Victor_G_0-1752656375628.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/78338iAFB251A6CF53034F/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Victor_G_0-1752656375628.png" alt="Victor_G_0-1752656375628.png" /&gt;&lt;/span&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI&gt;&lt;SPAN class="lia-inline-image-display-wrapper lia-image-align-inline"&gt;&lt;SPAN class="lia-message-image-wrapper lia-message-image-actions-narrow lia-message-image-actions-below"&gt;You can then add a blocking factor in the "Factors" panel for the labs, check the option "Include all selected covariate rows in the design", and "Make design".&lt;/SPAN&gt;&lt;/SPAN&gt;&amp;nbsp;&lt;/LI&gt;
&lt;/OL&gt;
&lt;/LI&gt;
&lt;/UL&gt;
&lt;P&gt;This way, your CCD Orthogonal design with replicates could include a blocking factor to take into account possible day-to-day variation.&lt;/P&gt;
&lt;P&gt;Hope these suggestions may help you,&lt;/P&gt;</description>
      <pubDate>Wed, 16 Jul 2025 09:04:29 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Question-about-Response-Surface-and-Blocking/m-p/887398#M104951</guid>
      <dc:creator>Victor_G</dc:creator>
      <dc:date>2025-07-16T09:04:29Z</dc:date>
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