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    <title>topic Welch's T-test with multiple comparisons correction in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248429#M48753</link>
    <description>&lt;P&gt;I know how to do Steel-Dwass with control for comparing multiple population means to a single control population in JMP, but how do I use JMP to do a Welch's t-test with Benjamini-Hochberg correction (for example)?&amp;nbsp; Also, I know that the core difference between these approaches is that the former does not make the assumption of normality but the latter does.&amp;nbsp; I've not found good discussions of why you might choose one over the other assuming the normality assumption is satisfied (which really it never is, but sometimes is reasonable)?&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Thu, 20 Feb 2020 02:43:10 GMT</pubDate>
    <dc:creator>ataylor</dc:creator>
    <dc:date>2020-02-20T02:43:10Z</dc:date>
    <item>
      <title>Welch's T-test with multiple comparisons correction</title>
      <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248429#M48753</link>
      <description>&lt;P&gt;I know how to do Steel-Dwass with control for comparing multiple population means to a single control population in JMP, but how do I use JMP to do a Welch's t-test with Benjamini-Hochberg correction (for example)?&amp;nbsp; Also, I know that the core difference between these approaches is that the former does not make the assumption of normality but the latter does.&amp;nbsp; I've not found good discussions of why you might choose one over the other assuming the normality assumption is satisfied (which really it never is, but sometimes is reasonable)?&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 20 Feb 2020 02:43:10 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248429#M48753</guid>
      <dc:creator>ataylor</dc:creator>
      <dc:date>2020-02-20T02:43:10Z</dc:date>
    </item>
    <item>
      <title>Re: Welch's T-test with multiple comparisons correction</title>
      <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248518#M48766</link>
      <description>&lt;P&gt;Steel-Dwass has very little power with small group sizes.&amp;nbsp; If you have group sizes around n=15 or greater, it will probably be a decent option.&amp;nbsp; Years ago, I was looking for a Tukey HSD analysis with an unequal variances correction and came across Games-Howell, which is not available in JMP.&amp;nbsp; I added it to the JMP Wish List, and is one of the most up-voted proposals on there right now.&amp;nbsp; In the last year, I created an add-in to do Games-Howell on a single X and Y which you can find here:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="https://community.jmp.com/t5/JMP-Add-Ins/Games-Howell-Test-Tukey-HSD-with-Welch-s-correction-for-Unequal/ta-p/213771" target="_blank" rel="noopener"&gt;https://community.jmp.com/t5/JMP-Add-Ins/Games-Howell-Test-Tukey-HSD-with-Welch-s-correction-for-Unequal/ta-p/213771&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I know you are wanting to do the multiple comparisons relative to a control, which I don't have an exact solution for, but if you are willing to do a Tukey-style analysis and just look at which levels are not connected to your control, you may get what you need from that add-in.&lt;/P&gt;</description>
      <pubDate>Thu, 20 Feb 2020 17:47:53 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248518#M48766</guid>
      <dc:creator>cwillden</dc:creator>
      <dc:date>2020-02-20T17:47:53Z</dc:date>
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    <item>
      <title>Re: Welch's T-test with multiple comparisons correction</title>
      <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248567#M48780</link>
      <description>&lt;P&gt;Chris,&amp;nbsp;&lt;BR /&gt;&lt;BR /&gt;Thanks for getting back to me.&amp;nbsp; The info about Steel-Dwass and small group sizes that is super helpful!&amp;nbsp; I agree that when comparing all pairs Games-Howell is the way to go, but I have simulations that show it can be overly conservative when you only want to compare the multiple populations to a single control (so not all pairwise comparisons).&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;It would still be helpful to know if it is possible to do Welch's T-test with multiple comparison correction in JMP.&amp;nbsp;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 20 Feb 2020 23:54:03 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248567#M48780</guid>
      <dc:creator>ataylor</dc:creator>
      <dc:date>2020-02-20T23:54:03Z</dc:date>
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    <item>
      <title>Re: Welch's T-test with multiple comparisons correction</title>
      <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248676#M48817</link>
      <description>&lt;P&gt;It's not currently possible.&amp;nbsp; Best you can probably do with what is currently available in JMP is a Bonferroni correction, and I doubt you would want to go that direction.&amp;nbsp; If you are an R user, the DTK package may give you what you need.&lt;/P&gt;</description>
      <pubDate>Fri, 21 Feb 2020 18:08:59 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248676#M48817</guid>
      <dc:creator>cwillden</dc:creator>
      <dc:date>2020-02-21T18:08:59Z</dc:date>
    </item>
    <item>
      <title>Re: Welch's T-test with multiple comparisons correction</title>
      <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248693#M48821</link>
      <description>Thanks Chris!</description>
      <pubDate>Fri, 21 Feb 2020 18:55:40 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248693#M48821</guid>
      <dc:creator>ataylor</dc:creator>
      <dc:date>2020-02-21T18:55:40Z</dc:date>
    </item>
    <item>
      <title>Re: Welch's T-test with multiple comparisons correction</title>
      <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248794#M48838</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;for a stats assignment I have to do a&amp;nbsp;&lt;SPAN style="display: inline !important; float: none; background-color: #ffffff; color: #333333; font-family: Arial,Helvetica,sans-serif; font-size: 14px; font-style: normal; font-variant: normal; font-weight: 300; letter-spacing: normal; line-height: 1.4; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;"&gt;Bonferroni correction&lt;/SPAN&gt; on my data. I'm using a two sided t-test to compare several t distributed datasets to each other and will write a jsl script to do so. How do I incorporate the Bonferroni correction in JMP?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;&lt;P&gt;Ole&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 22 Feb 2020 11:24:15 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248794#M48838</guid>
      <dc:creator>Ole</dc:creator>
      <dc:date>2020-02-22T11:24:15Z</dc:date>
    </item>
    <item>
      <title>Re: Welch's T-test with multiple comparisons correction</title>
      <link>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248969#M48882</link>
      <description>Bonferroni is just an adjustment on alpha, which you decide.  You just take your desired alpha for the family of tests and divide that by the number of tests.  For example, if I want a family-wise error rate of 0.05 and do 10 pairs of comparisons, I would compare the p-value of each individual comparison to 0.05/10 = 0.005.</description>
      <pubDate>Mon, 24 Feb 2020 18:22:56 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Welch-s-T-test-with-multiple-comparisons-correction/m-p/248969#M48882</guid>
      <dc:creator>cwillden</dc:creator>
      <dc:date>2020-02-24T18:22:56Z</dc:date>
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