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    <title>topic Re: Logit Model_Predictive Regression in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426093#M22388</link>
    <description>&lt;P&gt;the correlation between the dep var and the lagged dep var is almost 1 for your data. Therefore, I don't think it is appropriate to include the lagged dep var to the model. You will get an almost perfect fit but useless model.&lt;/P&gt;
&lt;P&gt;thanks&lt;/P&gt;
&lt;P&gt;alex&lt;/P&gt;</description>
    <pubDate>Tue, 09 Jan 2018 13:50:28 GMT</pubDate>
    <dc:creator>alexchien</dc:creator>
    <dc:date>2018-01-09T13:50:28Z</dc:date>
    <item>
      <title>Logit Model_Predictive Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426032#M22387</link>
      <description>&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;I have a general question related to logit regression model. I want to know your mind about one point related to logit regression model. I am using logit model for my analyzing. My key independent variable is the lagged; hence, it is predictive regression. So, my dependent variable is 0 and 1. These 0 and 1 is related to the time of the day. To make it more clear, I have minutely time-series data for one day. In one day, we have 24 hours * 60 minutes = 1440 rows as my dependent variable. The dependent variable is "0" from 1st to 600th rows and from 900th to 1440th rows - it is "normal period". However, the dependent variable is "1" from 600th to 900th rows - let's say it is "abnormal period". In its simplest from, my dependent and independent variables are:&lt;BR /&gt;&lt;BR /&gt;Number of rows&amp;nbsp; &amp;nbsp; Dependent variable&amp;nbsp; &amp;nbsp; &amp;nbsp; Independent variable&lt;BR /&gt;1&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0.1&lt;BR /&gt;2&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0.15&lt;BR /&gt;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; .&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;.&lt;BR /&gt;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; .&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;.&lt;BR /&gt;600&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 0&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 0.17&lt;BR /&gt;601&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 1&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 0.13&lt;BR /&gt;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;.&lt;BR /&gt;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;.&lt;BR /&gt;900&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;1&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0.22&lt;BR /&gt;901&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0.19&lt;BR /&gt;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; .&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; .&lt;BR /&gt;.&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; .&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; .&lt;BR /&gt;1440&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;0.21&lt;BR /&gt;&lt;BR /&gt;I am interested the examine the predictive power of my key independent variable. Now I use the first lag of my independent variable as my KEY VARIABLE. Actually, I am confusing about the result of my regression. The issue is, I guess that the majority part of the predictive power of lagged variable will come from the "abnormal period" rather than "normal period".&lt;BR /&gt;What do you think about that?&lt;/P&gt;</description>
      <pubDate>Tue, 09 Jan 2018 11:09:19 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426032#M22387</guid>
      <dc:creator>Khaladdin</dc:creator>
      <dc:date>2018-01-09T11:09:19Z</dc:date>
    </item>
    <item>
      <title>Re: Logit Model_Predictive Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426093#M22388</link>
      <description>&lt;P&gt;the correlation between the dep var and the lagged dep var is almost 1 for your data. Therefore, I don't think it is appropriate to include the lagged dep var to the model. You will get an almost perfect fit but useless model.&lt;/P&gt;
&lt;P&gt;thanks&lt;/P&gt;
&lt;P&gt;alex&lt;/P&gt;</description>
      <pubDate>Tue, 09 Jan 2018 13:50:28 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426093#M22388</guid>
      <dc:creator>alexchien</dc:creator>
      <dc:date>2018-01-09T13:50:28Z</dc:date>
    </item>
    <item>
      <title>Re: Logit Model_Predictive Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426113#M22389</link>
      <description>I do not use lagged dependent variable. I am going to use the lagged of my independent variable, not dependent variable. Why does the correlation matter?</description>
      <pubDate>Tue, 09 Jan 2018 14:36:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426113#M22389</guid>
      <dc:creator>Khaladdin</dc:creator>
      <dc:date>2018-01-09T14:36:27Z</dc:date>
    </item>
    <item>
      <title>Re: Logit Model_Predictive Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426132#M22390</link>
      <description>Now, I got your point &lt;span class="lia-unicode-emoji" title=":slightly_smiling_face:"&gt;🙂&lt;/span&gt; Thanks</description>
      <pubDate>Tue, 09 Jan 2018 15:14:30 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Logit-Model-Predictive-Regression/m-p/426132#M22390</guid>
      <dc:creator>Khaladdin</dc:creator>
      <dc:date>2018-01-09T15:14:30Z</dc:date>
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