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    <title>topic Proc NLIN Goodness of fit and model selection in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-Goodness-of-fit-and-model-selection/m-p/718362#M34722</link>
    <description>&lt;P&gt;Greetings all.&lt;/P&gt;&lt;P&gt;I have a fertilizer rate dataset in which yield (response) plateaus at a given fertilizer threshold (explanatory variable), which is common in rate trials.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have fit the data with both a linear-plateau and a quadratic-plateau model but am not sure which is the best fit.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I know that there is no single agreed upon metric that measures goodness of fit for nonlinear models. I've seen prior posts discuss pseudo-R^2 for nonlinear models. Would it be best to calculate pseudo-R^2 for each model and compare? These models are nested, so I believe I can also conduct a chi-square test to determine which is a better fit. If so, is this simply something to be done by hand or do macros exist for these types of comparisons, similar to the %GOF macro used for nonlinear mixed models?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;</description>
    <pubDate>Wed, 10 Feb 2021 19:17:12 GMT</pubDate>
    <dc:creator>dsuchoff1</dc:creator>
    <dc:date>2021-02-10T19:17:12Z</dc:date>
    <item>
      <title>Proc NLIN Goodness of fit and model selection</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-Goodness-of-fit-and-model-selection/m-p/718362#M34722</link>
      <description>&lt;P&gt;Greetings all.&lt;/P&gt;&lt;P&gt;I have a fertilizer rate dataset in which yield (response) plateaus at a given fertilizer threshold (explanatory variable), which is common in rate trials.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have fit the data with both a linear-plateau and a quadratic-plateau model but am not sure which is the best fit.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I know that there is no single agreed upon metric that measures goodness of fit for nonlinear models. I've seen prior posts discuss pseudo-R^2 for nonlinear models. Would it be best to calculate pseudo-R^2 for each model and compare? These models are nested, so I believe I can also conduct a chi-square test to determine which is a better fit. If so, is this simply something to be done by hand or do macros exist for these types of comparisons, similar to the %GOF macro used for nonlinear mixed models?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;</description>
      <pubDate>Wed, 10 Feb 2021 19:17:12 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-NLIN-Goodness-of-fit-and-model-selection/m-p/718362#M34722</guid>
      <dc:creator>dsuchoff1</dc:creator>
      <dc:date>2021-02-10T19:17:12Z</dc:date>
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