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    <title>topic Reason for Higher Correlation weight Being Non-Significant in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Reason-for-Higher-Correlation-weight-Being-Non-Significant/m-p/34405#M1428</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi everyone,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I ran a multilevel model using proc mixed. I obtained the following results. I ran a single regression using two scales as predictors on a single measure I obtained the following:&lt;/P&gt;&lt;P&gt;Scale 1: &lt;SPAN style="color: #222222; font-family: arial, sans-serif; text-align: -webkit-auto; background-color: rgba(255, 255, 255, 0.917969);"&gt; r = -.32, p = .136&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="color: #222222; font-family: arial, sans-serif; text-align: -webkit-auto; background-color: rgba(255, 255, 255, 0.917969);"&gt;Scale 2: r = .29, p = .014&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I'm a bit confused by how this might happen (since the absolute magnitude of the first scale is greater than the second scale). Specifically because their is no difference in missing data. I assume that there is some inflation of the standard error of the first scale, but what can cause this? My first guess was that the standard error of measurement was very high from the first scale, but I wasn't sure if that would also lower the regression coefficient as well.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I would appreciate any and all help!&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;&lt;P&gt;Nick&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Fri, 20 Jan 2012 15:40:05 GMT</pubDate>
    <dc:creator>psychresearcher</dc:creator>
    <dc:date>2012-01-20T15:40:05Z</dc:date>
    <item>
      <title>Reason for Higher Correlation weight Being Non-Significant</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Reason-for-Higher-Correlation-weight-Being-Non-Significant/m-p/34405#M1428</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi everyone,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I ran a multilevel model using proc mixed. I obtained the following results. I ran a single regression using two scales as predictors on a single measure I obtained the following:&lt;/P&gt;&lt;P&gt;Scale 1: &lt;SPAN style="color: #222222; font-family: arial, sans-serif; text-align: -webkit-auto; background-color: rgba(255, 255, 255, 0.917969);"&gt; r = -.32, p = .136&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="color: #222222; font-family: arial, sans-serif; text-align: -webkit-auto; background-color: rgba(255, 255, 255, 0.917969);"&gt;Scale 2: r = .29, p = .014&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I'm a bit confused by how this might happen (since the absolute magnitude of the first scale is greater than the second scale). Specifically because their is no difference in missing data. I assume that there is some inflation of the standard error of the first scale, but what can cause this? My first guess was that the standard error of measurement was very high from the first scale, but I wasn't sure if that would also lower the regression coefficient as well.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I would appreciate any and all help!&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;&lt;P&gt;Nick&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 20 Jan 2012 15:40:05 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Reason-for-Higher-Correlation-weight-Being-Non-Significant/m-p/34405#M1428</guid>
      <dc:creator>psychresearcher</dc:creator>
      <dc:date>2012-01-20T15:40:05Z</dc:date>
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