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    <title>topic Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886398#M43860</link>
    <description>&lt;P&gt;Thanks,&amp;nbsp;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13684"&gt;@Rick_SAS&lt;/a&gt;&amp;nbsp;. That property was what I was thinking about when I said that if a smeared estimate is used for the expected value (= eta in your post), then it should also be applied to the confidence bounds. The Swiss Tech paper implies that a direct exponentiation should be adequate.&amp;nbsp; Thoughts?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Wed, 26 Jul 2023 12:03:51 GMT</pubDate>
    <dc:creator>SteveDenham</dc:creator>
    <dc:date>2023-07-26T12:03:51Z</dc:date>
    <item>
      <title>Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886127#M43852</link>
      <description>&lt;P&gt;I have performed OLS regression on ln transformed x and y variables, and re-transformed the results (ln_pred) to the original units using Duan's Smearing Estimate (my own code). The latter is done to minimize re-transformation bias.&amp;nbsp; &amp;nbsp;I am not sure how to re-transform the ln confidence limits (Ln_Upper and Ln_Lower 95%) back to the original units--do I apply the smearing estimate or simply exponentiate the ln confidence limit values ?&lt;/P&gt;</description>
      <pubDate>Mon, 24 Jul 2023 17:44:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886127#M43852</guid>
      <dc:creator>Fluvio1</dc:creator>
      <dc:date>2023-07-24T17:44:34Z</dc:date>
    </item>
    <item>
      <title>Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886131#M43853</link>
      <description>&lt;P&gt;I haven't done this, but if I had, I probably would have used PROC NLIN, NLMIXED, GENMOD or GLIMMIX. For manually transformed values in PROC REG or GLM, it is nice to know that there is a relatively simple unbiased back-transformation that doesn't appear to be as volatile as the expected value estimator for a log-normal distribution.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;See this site:&amp;nbsp;&lt;A href="https://stat.ethz.ch/education/semesters/as2015/asr/Script_v151119.pdf" target="_self"&gt;https://stat.ethz.ch/education/semesters/as2015/asr/Script_v151119.pdf&lt;/A&gt;&amp;nbsp;The authors argue that since the confidence bounds are estimated percentiles of the distribution, the naive back-transformation (simple exponentiation) is certainly adequate and appropriate.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;At least until the smeared estimate is outside of the confidence interval...&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&lt;/P&gt;</description>
      <pubDate>Mon, 24 Jul 2023 18:08:42 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886131#M43853</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2023-07-24T18:08:42Z</dc:date>
    </item>
    <item>
      <title>Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886272#M43855</link>
      <description>&lt;P&gt;If (L, U) is a (1-alpha) CI for a parameter, p, then (eta(L), eta(U)) is a&amp;nbsp;(1-alpha) CI for the parameter, eta(p), for any strictly monotone increasing continuous transformation, eta. That's because&amp;nbsp;&lt;/P&gt;
&lt;P&gt;P(L &amp;lt;= X &amp;lt;= U) = P(eta(L) &amp;lt;= eta(X) &amp;lt;= eta(U))&lt;/P&gt;
&lt;P&gt;for a continuous r.v X. So, yes, you can apply the inverse transformation to back-transform the estimates, including CIs.&lt;/P&gt;</description>
      <pubDate>Tue, 25 Jul 2023 17:17:25 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886272#M43855</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2023-07-25T17:17:25Z</dc:date>
    </item>
    <item>
      <title>Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886398#M43860</link>
      <description>&lt;P&gt;Thanks,&amp;nbsp;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/13684"&gt;@Rick_SAS&lt;/a&gt;&amp;nbsp;. That property was what I was thinking about when I said that if a smeared estimate is used for the expected value (= eta in your post), then it should also be applied to the confidence bounds. The Swiss Tech paper implies that a direct exponentiation should be adequate.&amp;nbsp; Thoughts?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;SteveDenham&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 26 Jul 2023 12:03:51 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886398#M43860</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2023-07-26T12:03:51Z</dc:date>
    </item>
    <item>
      <title>Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886403#M43861</link>
      <description>&lt;P&gt;I had never heard of Duan's smearing estimator until this post, and I have no experience with it. I quickly glanced at the paper you cited. It looks to me like they transformed X and Y variables by using LOG and then backtransformed the estimates by using inverse-LOG = EXP. Yes, that is valid and standard.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Maybe I am wrong, but even though the paper mentions Duan's work, I don't think they actually use it. Those paragraphs seem to be inserted (maybe at the suggestion of a referee) to let the reader know that there is an alternative, which they authors do not use.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I think it is important to point out that there is a difference between a generalized linear model with a log-link and a linear model on the log-transformed data. See&amp;nbsp;&lt;A href="https://blogs.sas.com/content/iml/2015/09/16/plot-distrib-exp.html" target="_blank"&gt;Error distributions and exponential regression models - The DO Loop (sas.com)&lt;/A&gt;&lt;BR /&gt;which compares&lt;BR /&gt;GENMOD&lt;/P&gt;
&lt;PRE class="sas"&gt;model y = &lt;SPAN&gt;x&lt;/SPAN&gt; / dist=&lt;SPAN&gt;normal&lt;/SPAN&gt; &lt;SPAN&gt;link&lt;/SPAN&gt;=&lt;SPAN&gt;log&lt;/SPAN&gt;;&lt;/PRE&gt;
&lt;P&gt;to GLM&amp;nbsp;&lt;/P&gt;
&lt;PRE class="sas"&gt;model logY = &lt;SPAN&gt;x;&lt;/SPAN&gt;&lt;/PRE&gt;
&lt;P&gt;The OP seems to be using the latter. Which model is correct depends on the error distribution, which is perhaps why the OP mentions the smearing estimate. I do not know the correct model for the OP's data. Graphing the distribution of the residuals might be prudent. Domain knowledge might also help.&lt;/P&gt;</description>
      <pubDate>Wed, 26 Jul 2023 13:01:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886403#M43861</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2023-07-26T13:01:47Z</dc:date>
    </item>
    <item>
      <title>Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886478#M43864</link>
      <description>&lt;P&gt;Thank you Steve. However it does look&amp;nbsp; like some of the Duan's&amp;nbsp; smeared estimates are outside the confidence limits. If I compute the quantiles for the exponentiated confidence limits, they&amp;nbsp; are highly skewed:&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="Fluvio1_0-1690389621589.png" style="width: 400px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/86136iA42798032013DCD5/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Fluvio1_0-1690389621589.png" alt="Fluvio1_0-1690389621589.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;Not sure how to handle this ?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 26 Jul 2023 16:40:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886478#M43864</guid>
      <dc:creator>Fluvio1</dc:creator>
      <dc:date>2023-07-26T16:40:45Z</dc:date>
    </item>
    <item>
      <title>Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886479#M43865</link>
      <description>&lt;P&gt;Thank you Rick for the insightful explanation.&lt;/P&gt;</description>
      <pubDate>Wed, 26 Jul 2023 16:41:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886479#M43865</guid>
      <dc:creator>Fluvio1</dc:creator>
      <dc:date>2023-07-26T16:41:43Z</dc:date>
    </item>
    <item>
      <title>Re: Proc REG.   How do I transform ln confidence limits back to original arithmetic units ?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886489#M43866</link>
      <description>&lt;P&gt;Thanks again Rick.&amp;nbsp; I attached the original paper by Duan that defines the smearing estimator. Also see below:&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Fluvio1_0-1690390001666.png" style="width: 400px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/86137i6ED328106F0D37B3/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Fluvio1_0-1690390001666.png" alt="Fluvio1_0-1690390001666.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 26 Jul 2023 17:01:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-REG-How-do-I-transform-ln-confidence-limits-back-to/m-p/886489#M43866</guid>
      <dc:creator>Fluvio1</dc:creator>
      <dc:date>2023-07-26T17:01:34Z</dc:date>
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