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    <title>topic Re: How to fit a logistic regression model using the same covariates included in the previous study in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128346#M294549</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Much clearer.&amp;nbsp; Let's see. You have estimates of the parameters, and you have your data.&amp;nbsp; You wish to run your data through the final model, with the known parameter estimates, and get an ROC. The Details section of the documentation has a section "Receiver Operating Characteristic Curves" and in the Comparing ROC Curves section says:&lt;/P&gt;&lt;P&gt;"ROC curves can be created from each model fit in a selection routine, from the specified model in the &lt;A _jive_internal="true" class="olink" href="/ms-its:C:\Program Files\SASHome\SASFoundation\9.3\core\help\en\statug.chm::/statug.hlp/statug_logistic_syntax22.htm"&gt;MODEL&lt;/A&gt; statement, from specified models in ROC statements, or from input variables which act as (pi hat) in the preceding discussion."&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;This sounds like what you want (it also sounds, to me, like scoring your data using the final model).&amp;nbsp; Unfortunately, I cannot find an example where input variables are used.&amp;nbsp; I do know that you would need to calculate the predicted probabilities in a dataset, but the devil is in the details, and that is where I am stuck as well.&amp;nbsp; Perhaps someone can step in and help.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Tue, 25 Sep 2012 11:17:41 GMT</pubDate>
    <dc:creator>SteveDenham</dc:creator>
    <dc:date>2012-09-25T11:17:41Z</dc:date>
    <item>
      <title>How to fit a logistic regression model using the same covariates included in the previous study</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128342#M294545</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi, I am trying to validate a prediction model using SAS. I need to use the model with the coefficients from the previous study and calculate Area under the ROC curve. I know how to run and get ROC and AUC using the covariates but I can't seem to figure out how to include the coefficients. Anyone know how to do it? Thanks&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sun, 23 Sep 2012 21:04:30 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128342#M294545</guid>
      <dc:creator>Rashu</dc:creator>
      <dc:date>2012-09-23T21:04:30Z</dc:date>
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    <item>
      <title>Re: How to fit a logistic regression model using the same covariates included in the previous study</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128343#M294546</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;One way is to manually compute the logit of your existing model and use that as the single covariate in PROC LOGISTIC to get the ROC and AUC.&amp;nbsp; That would tell you how well that model fits.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If you wish to know if the existing model could be improved, you could include the logit and all the original variables.&amp;nbsp; If any of the original variables are significant, then that is an indication that the model could be improved.&amp;nbsp; You could also compare the two ROCs to get a summary measure of improvement (see Rick Wicklin's previous post on this).&amp;nbsp; One thing to be a careful of here is to make sure that your 'new' data has a big enough sample size to support all the variables.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Doc Muhlbaier&lt;/P&gt;&lt;P&gt;Duke&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 24 Sep 2012 14:14:17 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128343#M294546</guid>
      <dc:creator>Doc_Duke</dc:creator>
      <dc:date>2012-09-24T14:14:17Z</dc:date>
    </item>
    <item>
      <title>Re: How to fit a logistic regression model using the same covariates included in the previous study</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128344#M294547</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Rashu,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I am a little confused.&amp;nbsp; Do you wish to use existing coefficients and score new data?&amp;nbsp; You might use the SCORE statement and the inmodel= option, as in example 54.15 from the SAS/STAT12.1 documentation for PROC LOGISTIC.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If you wish to compare ROC curves, and have version 12.1, then you should look at the ROCCONTRAST statement.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If I have misunderstood your question, I apologize.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 24 Sep 2012 19:29:32 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128344#M294547</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2012-09-24T19:29:32Z</dc:date>
    </item>
    <item>
      <title>Re: How to fit a logistic regression model using the same covariates included in the previous study</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128345#M294548</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Steve,&lt;/P&gt;&lt;P&gt;May be what I am asking is not clear. I don't think I am trying to score a new data.&lt;/P&gt;&lt;P&gt;I already have a data and I have a prediction model from previous study that I am trying to validate on my data (external validation). I do not have access to the derivation data from previous study-I just have the model. The final prediction model from the previous study lets say is: exp(2.5+1.2 x1+3.2 x2)/1+exp(2.5+1.2 x1+3.2 x2) &lt;/P&gt;&lt;P&gt;I am using calibration and discrimination to do the external validation of the model. I need to find the area under the curve to see if I get the same results as in the derivation data.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;After finding this area, I will run the logistic regression with the variables as well to see if I get the same coefficients and AUC&amp;nbsp; but the first step of validation is to see if the model works in the new data and hence I am trying to find the area under ROC. &lt;/P&gt;&lt;P&gt;I hope I made my question little clear this time.&lt;/P&gt;&lt;P&gt;Thanks for the help&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 24 Sep 2012 20:26:58 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128345#M294548</guid>
      <dc:creator>Rashu</dc:creator>
      <dc:date>2012-09-24T20:26:58Z</dc:date>
    </item>
    <item>
      <title>Re: How to fit a logistic regression model using the same covariates included in the previous study</title>
      <link>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128346#M294549</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Much clearer.&amp;nbsp; Let's see. You have estimates of the parameters, and you have your data.&amp;nbsp; You wish to run your data through the final model, with the known parameter estimates, and get an ROC. The Details section of the documentation has a section "Receiver Operating Characteristic Curves" and in the Comparing ROC Curves section says:&lt;/P&gt;&lt;P&gt;"ROC curves can be created from each model fit in a selection routine, from the specified model in the &lt;A _jive_internal="true" class="olink" href="/ms-its:C:\Program Files\SASHome\SASFoundation\9.3\core\help\en\statug.chm::/statug.hlp/statug_logistic_syntax22.htm"&gt;MODEL&lt;/A&gt; statement, from specified models in ROC statements, or from input variables which act as (pi hat) in the preceding discussion."&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;This sounds like what you want (it also sounds, to me, like scoring your data using the final model).&amp;nbsp; Unfortunately, I cannot find an example where input variables are used.&amp;nbsp; I do know that you would need to calculate the predicted probabilities in a dataset, but the devil is in the details, and that is where I am stuck as well.&amp;nbsp; Perhaps someone can step in and help.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 25 Sep 2012 11:17:41 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/How-to-fit-a-logistic-regression-model-using-the-same-covariates/m-p/128346#M294549</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2012-09-25T11:17:41Z</dc:date>
    </item>
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