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    <title>topic Re: Should I use Bonferroni correction when making two linear contrasts with Fit Model? in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17702#M16133</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thanks so much for the suggestions, that all definitely helps!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Mon, 04 Apr 2016 21:25:47 GMT</pubDate>
    <dc:creator>amm9010</dc:creator>
    <dc:date>2016-04-04T21:25:47Z</dc:date>
    <item>
      <title>Should I use Bonferroni correction when making two linear contrasts with Fit Model?</title>
      <link>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17698#M16129</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I'm conducting a series of univariate REML models and have two preplanned orthogonal contrasts. I am wondering if I need to correct the acceptable alpha to guard against Type I error, or if this correction is taken into consideration by the JMP program when I add a second contrast?&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 29 Mar 2016 13:35:46 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17698#M16129</guid>
      <dc:creator>amm9010</dc:creator>
      <dc:date>2016-03-29T13:35:46Z</dc:date>
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    <item>
      <title>Re: Should I use Bonferroni correction when making two linear contrasts with Fit Model?</title>
      <link>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17699#M16130</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;&lt;SPAN style="font-family: 'Arial',sans-serif; color: #44546a;"&gt;JMP doesn't automatically make the adjustment when you use &lt;/SPAN&gt;&lt;EM style="font-family: 'Arial',sans-serif;"&gt;Custom Test&lt;/EM&gt;&lt;SPAN class="apple-converted-space"&gt; from the &lt;/SPAN&gt;&lt;EM style="font-family: 'Arial',sans-serif;"&gt;Estimates&lt;/EM&gt;&lt;SPAN class="apple-converted-space"&gt; menu to add additional contrasts. You may apply the Bonferroni correction. (As a note, when there are a large number of comparisons, the Bonferroni correction &lt;/SPAN&gt;&lt;SPAN style="color: #252525; font-family: sans-serif; font-size: 14px;"&gt;can be too conservative&lt;/SPAN&gt;.)&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 30 Mar 2016 21:05:16 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17699#M16130</guid>
      <dc:creator>jiancao</dc:creator>
      <dc:date>2016-03-30T21:05:16Z</dc:date>
    </item>
    <item>
      <title>Re: Should I use Bonferroni correction when making two linear contrasts with Fit Model?</title>
      <link>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17700#M16131</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;A slightly less conservative option is the Bonferroni-Holm procedure:&amp;nbsp; the smaller p value needs to be tested on the alpha/2 level first, the other p value can then be tested on your planned&amp;nbsp; alpha level if the first test was statistically significant.&lt;/P&gt;&lt;P&gt;A further option for dealing with the multiple testing issue is the false discovery rate approach (FDR-approach) for which a nice and easy usable JMP Add-In is available.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 31 Mar 2016 15:43:19 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17700#M16131</guid>
      <dc:creator>dr_winfried_koc</dc:creator>
      <dc:date>2016-03-31T15:43:19Z</dc:date>
    </item>
    <item>
      <title>Re: Should I use Bonferroni correction when making two linear contrasts with Fit Model?</title>
      <link>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17701#M16132</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thanks for mentioning the FDR Pvalue add-in. It has been incorporated into JMP known as the Response Screening under Modeling.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 01 Apr 2016 00:25:36 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17701#M16132</guid>
      <dc:creator>jiancao</dc:creator>
      <dc:date>2016-04-01T00:25:36Z</dc:date>
    </item>
    <item>
      <title>Re: Should I use Bonferroni correction when making two linear contrasts with Fit Model?</title>
      <link>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17702#M16133</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thanks so much for the suggestions, that all definitely helps!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 04 Apr 2016 21:25:47 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Should-I-use-Bonferroni-correction-when-making-two-linear/m-p/17702#M16133</guid>
      <dc:creator>amm9010</dc:creator>
      <dc:date>2016-04-04T21:25:47Z</dc:date>
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