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    <title>topic Re: Hodges-Lehmann Estimators for non-Wilcoxon cases in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Hodges-Lehmann-Estimators-for-non-Wilcoxon-cases/m-p/131622#M6885</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you Steve, too bad that SAS cannot copy the R code which is available (e.g., &lt;A href="http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=pairwiseCI:pairwiseCImethodsCont" title="http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=pairwiseCI:pairwiseCImethodsCont"&gt;R Graphical Manual&lt;/A&gt;).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;On another two observations on the Hodges-Lehmann estimators, &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;I discovered that when the Wilcoxon p-value is just barely statistically significant (e.g., 0.045 when N/group = 6), then the HL estimators do not always exclude 0.&amp;nbsp; This was confirmed by the SAS developer.&amp;nbsp; A SAS consultant and a 2011 talk by Riji Yao, et. al. suggested that either an Exact solution or a sampling approach &lt;SPAN style="text-decoration: underline;"&gt;might&lt;/SPAN&gt; yield HL estimators which are consistent with the p-values. &lt;/LI&gt;&lt;LI&gt;A Monte Carlo study observed across a range of distributions that the t-test CI gives about 21% narrower CI than the HL when N is small.&amp;nbsp; Only for leptokurtic distributions and large Ns might the HL offer a slightly smaller CI.&amp;nbsp; Although with the central limit theorem, the distribution of means very, very quickly converge on normal, questioning the underlying need for non-parametric approaches.&lt;/LI&gt;&lt;/OL&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 28 Jun 2012 17:14:34 GMT</pubDate>
    <dc:creator>AllenFleishman</dc:creator>
    <dc:date>2012-06-28T17:14:34Z</dc:date>
    <item>
      <title>Hodges-Lehmann Estimators for non-Wilcoxon cases</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Hodges-Lehmann-Estimators-for-non-Wilcoxon-cases/m-p/131620#M6883</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;&lt;SPAN style="font-size: 12pt;"&gt;Can one easily compute Hodges-Lehmann Estimators for statistics other than the Wilcoxon test?&amp;nbsp; For example, for paired data or sign-test?&lt;/SPAN&gt;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sun, 03 Jun 2012 16:08:33 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Hodges-Lehmann-Estimators-for-non-Wilcoxon-cases/m-p/131620#M6883</guid>
      <dc:creator>AllenFleishman</dc:creator>
      <dc:date>2012-06-03T16:08:33Z</dc:date>
    </item>
    <item>
      <title>Re: Hodges-Lehmann Estimators for non-Wilcoxon cases</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Hodges-Lehmann-Estimators-for-non-Wilcoxon-cases/m-p/131621#M6884</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;A quick test on some data at hand says it will take some major work with output to get the HL estimators.&amp;nbsp; I couldn't get them for anything other than the Wilcoxon test.&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, 04 Jun 2012 12:18:30 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Hodges-Lehmann-Estimators-for-non-Wilcoxon-cases/m-p/131621#M6884</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2012-06-04T12:18:30Z</dc:date>
    </item>
    <item>
      <title>Re: Hodges-Lehmann Estimators for non-Wilcoxon cases</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Hodges-Lehmann-Estimators-for-non-Wilcoxon-cases/m-p/131622#M6885</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you Steve, too bad that SAS cannot copy the R code which is available (e.g., &lt;A href="http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=pairwiseCI:pairwiseCImethodsCont" title="http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=pairwiseCI:pairwiseCImethodsCont"&gt;R Graphical Manual&lt;/A&gt;).&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;On another two observations on the Hodges-Lehmann estimators, &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;I discovered that when the Wilcoxon p-value is just barely statistically significant (e.g., 0.045 when N/group = 6), then the HL estimators do not always exclude 0.&amp;nbsp; This was confirmed by the SAS developer.&amp;nbsp; A SAS consultant and a 2011 talk by Riji Yao, et. al. suggested that either an Exact solution or a sampling approach &lt;SPAN style="text-decoration: underline;"&gt;might&lt;/SPAN&gt; yield HL estimators which are consistent with the p-values. &lt;/LI&gt;&lt;LI&gt;A Monte Carlo study observed across a range of distributions that the t-test CI gives about 21% narrower CI than the HL when N is small.&amp;nbsp; Only for leptokurtic distributions and large Ns might the HL offer a slightly smaller CI.&amp;nbsp; Although with the central limit theorem, the distribution of means very, very quickly converge on normal, questioning the underlying need for non-parametric approaches.&lt;/LI&gt;&lt;/OL&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 28 Jun 2012 17:14:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Hodges-Lehmann-Estimators-for-non-Wilcoxon-cases/m-p/131622#M6885</guid>
      <dc:creator>AllenFleishman</dc:creator>
      <dc:date>2012-06-28T17:14:34Z</dc:date>
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