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    <title>topic Re: Fit data to a logistic function with a known asymptote in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/753751#M93564</link>
    <description>&lt;P&gt;If I understand correctly, you need to fit Logistic-2P, because the asymptote is known.&lt;/P&gt;
&lt;P&gt;In that case, you need to normalize your data, such that Y is between 0 and 1. In your case, I guess that you should divided your Y by 100.&lt;/P&gt;
&lt;P&gt;After that, the Logistic-2P will be available:&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="peng_liu_1-1715568564067.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/64133i7A278C9A2059FC3A/image-size/medium?v=v2&amp;amp;px=400" role="button" title="peng_liu_1-1715568564067.png" alt="peng_liu_1-1715568564067.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;Scaling your data should not impact the other two parameter estimates, i.e. the remaining two estimates are same. Unless you want to do some kind of prediction of Y given "cp", then your need to scale back after prediction using the fitted model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Mon, 13 May 2024 02:51:59 GMT</pubDate>
    <dc:creator>peng_liu</dc:creator>
    <dc:date>2024-05-13T02:51:59Z</dc:date>
    <item>
      <title>Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/752892#M93459</link>
      <description>&lt;P&gt;&lt;SPAN&gt;My goal is to fit this data to a logistic function (Logistic 3P for example). T&lt;/SPAN&gt;&lt;SPAN&gt;he y variable represents a proportion, so the maximum possible value is 100%. So I need to specify the asymptote as 100% because the model gives me values up this limit, and this is empirically impossible (attached image).&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Thak you for the help.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Kaik_0-1715174886341.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/64008iDDB63E2595456E0A/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Kaik_0-1715174886341.png" alt="Kaik_0-1715174886341.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 08 May 2024 13:29:19 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/752892#M93459</guid>
      <dc:creator>Kaik</dc:creator>
      <dc:date>2024-05-08T13:29:19Z</dc:date>
    </item>
    <item>
      <title>Re: Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/752935#M93467</link>
      <description>&lt;P&gt;It's hard to tell from just the screenshot: are you using Fit Curve, Nonlinear, or FDE platforms? Also, is it possible to share an anonymized set of the data to work with?&lt;/P&gt;</description>
      <pubDate>Wed, 08 May 2024 14:27:48 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/752935#M93467</guid>
      <dc:creator>Jed_Campbell</dc:creator>
      <dc:date>2024-05-08T14:27:48Z</dc:date>
    </item>
    <item>
      <title>Re: Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/753751#M93564</link>
      <description>&lt;P&gt;If I understand correctly, you need to fit Logistic-2P, because the asymptote is known.&lt;/P&gt;
&lt;P&gt;In that case, you need to normalize your data, such that Y is between 0 and 1. In your case, I guess that you should divided your Y by 100.&lt;/P&gt;
&lt;P&gt;After that, the Logistic-2P will be available:&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="peng_liu_1-1715568564067.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/64133i7A278C9A2059FC3A/image-size/medium?v=v2&amp;amp;px=400" role="button" title="peng_liu_1-1715568564067.png" alt="peng_liu_1-1715568564067.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;Scaling your data should not impact the other two parameter estimates, i.e. the remaining two estimates are same. Unless you want to do some kind of prediction of Y given "cp", then your need to scale back after prediction using the fitted model.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 13 May 2024 02:51:59 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/753751#M93564</guid>
      <dc:creator>peng_liu</dc:creator>
      <dc:date>2024-05-13T02:51:59Z</dc:date>
    </item>
    <item>
      <title>Re: Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754181#M93636</link>
      <description>&lt;P&gt;Thank you so much! I have another doubt related to this kind of analysis.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;When I try to compare parameter estimates, I obtain this error:&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Kaik_3-1715685535285.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/64197iC4431B9B4C7EA0FA/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Kaik_3-1715685535285.png" alt="Kaik_3-1715685535285.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;And when I try to make a custom inverse prediction, the std error in two variables is massive (the others are so good):&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Kaik_4-1715685599842.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/64198i4C8C11AA295B393B/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Kaik_4-1715685599842.png" alt="Kaik_4-1715685599842.png" /&gt;&lt;/span&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Kaik_5-1715685620881.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/64199i145168AB217F60A9/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Kaik_5-1715685620881.png" alt="Kaik_5-1715685620881.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;Is it possible that these two treatments cannot be modelled? Is there a possible solution? They are the two curves marked with an arrow (yellow and purple).&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Kaik_6-1715685759678.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/64200iEB19D8501EACA917/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Kaik_6-1715685759678.png" alt="Kaik_6-1715685759678.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thak you for the help to all users!&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 14 May 2024 11:24:17 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754181#M93636</guid>
      <dc:creator>Kaik</dc:creator>
      <dc:date>2024-05-14T11:24:17Z</dc:date>
    </item>
    <item>
      <title>Re: Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754185#M93639</link>
      <description>&lt;P&gt;There is not enough information here so that I can tell what is going on. From the fitted curve, I suspect the Growth Rate estimates of those two are relatively large. From the inverse prediction, seems the models have large uncertainties. I cannot tell where the uncertainties are from based on what I see here.&lt;/P&gt;</description>
      <pubDate>Tue, 14 May 2024 13:10:32 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754185#M93639</guid>
      <dc:creator>peng_liu</dc:creator>
      <dc:date>2024-05-14T13:10:32Z</dc:date>
    </item>
    <item>
      <title>Re: Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754188#M93640</link>
      <description>&lt;P&gt;Should you be concerned at the lack of parallelism among these curves?&lt;/P&gt;</description>
      <pubDate>Tue, 14 May 2024 13:25:32 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754188#M93640</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2024-05-14T13:25:32Z</dc:date>
    </item>
    <item>
      <title>Re: Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754932#M93733</link>
      <description>&lt;P&gt;Thank you for you help Peng.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;If you want, I can pass to you an anonymous data set to "play" with it, to discover what is happening here :).&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 16 May 2024 11:12:07 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754932#M93733</guid>
      <dc:creator>Kaik</dc:creator>
      <dc:date>2024-05-16T11:12:07Z</dc:date>
    </item>
    <item>
      <title>Re: Fit data to a logistic function with a known asymptote</title>
      <link>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754933#M93734</link>
      <description>&lt;P&gt;Hello Mark,&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Not so much, because they are different treatments, and each one reacts different. If you want, I can send you an anonymous dataset to investigate it :).&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you so mucho for your help!&lt;/P&gt;</description>
      <pubDate>Thu, 16 May 2024 11:13:50 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Fit-data-to-a-logistic-function-with-a-known-asymptote/m-p/754933#M93734</guid>
      <dc:creator>Kaik</dc:creator>
      <dc:date>2024-05-16T11:13:50Z</dc:date>
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