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    <title>topic Williams Deisgn 6*3 model, sample size calculation in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Williams-Deisgn-6-3-model-sample-size-calculation/m-p/474674#M24701</link>
    <description>&lt;P&gt;Hi Everyone,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;How can we calculate the sample size for a 6*3 Williams model in non central t-distribution. The equation I have is below code. But I am stuck and is not able to go ahead. Any help would be of great use.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks in advance.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;DIV class="sectionInfo"&gt;3. Algorithm for Sample Size Calculation&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;/DIV&gt;&lt;P&gt;Let&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN class="equationTd"&gt;&lt;SPAN class="MathJax" style="display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 16px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative;"&gt;&lt;SPAN class="math"&gt;&lt;SPAN&gt;&lt;SPAN class="mrow"&gt;&lt;SPAN class="msubsup"&gt;&lt;SPAN class="mover"&gt;&lt;SPAN class="mi"&gt;σ&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;ˆ&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;2&lt;/SPAN&gt;&lt;SPAN class="mi"&gt;e&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="MJX_Assistive_MathML"&gt;σˆe2&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&amp;nbsp;denote the residual intrasubject MSE from a historical study; with Method 1, the sample size can be calculated with the following algorithm:&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;&lt;P&gt;Set values for&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;α&lt;/I&gt;,&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;φ&lt;/I&gt;, and&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;(default&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;α&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 0.05,&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;φ&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 0.80, and&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 1);&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;Select a range of sample size (&lt;I&gt;N&lt;/I&gt;1,&lt;I&gt;N&lt;/I&gt;2), for each&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;N&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;∊ [&lt;I&gt;N&lt;/I&gt;1,&lt;I&gt;N&lt;/I&gt;2], and do the following:&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN class="equationTd"&gt;&lt;SPAN class="MathJax" style="display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 16px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative;"&gt;&lt;SPAN class="math"&gt;&lt;SPAN&gt;&lt;SPAN class="mrow"&gt;&lt;SPAN class="msub"&gt;&lt;SPAN class="mi"&gt;V&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;1&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;=&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;1.5&lt;/SPAN&gt;&lt;SPAN class="msubsup"&gt;&lt;SPAN class="mover"&gt;&lt;SPAN class="mi"&gt;σ&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;ˆ&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;2&lt;/SPAN&gt;&lt;SPAN class="mi"&gt;e&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;/&lt;/SPAN&gt;&lt;SPAN class="mi"&gt;N&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="MJX_Assistive_MathML"&gt;V1=1.5σˆe2/N&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;I&gt;τ&lt;/I&gt;1&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= [log(&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;) – log(▵&lt;I&gt;L&lt;/I&gt;) ] /&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;V&lt;/I&gt;1&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;I&gt;τ&lt;/I&gt;2&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= [log(&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;) – log(▵&lt;I&gt;U&lt;/I&gt;) ] /&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;V&lt;/I&gt;1&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;Calculate&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;PRNT&lt;/I&gt;(–&lt;I&gt;tν,α&lt;/I&gt;,&lt;I&gt;ν&lt;/I&gt;6×3,&lt;I&gt;τ&lt;/I&gt;2) –&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;PRNT&lt;/I&gt;(–&lt;I&gt;tν,α&lt;/I&gt;,&lt;I&gt;ν&lt;/I&gt;6×3,&lt;I&gt;τ&lt;/I&gt;1), where&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;PRNT&lt;/I&gt;(·) is the probability from a noncentral&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;t&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/I&gt;distribution, and&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;ν&lt;/I&gt;6×3&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 2&lt;I&gt;N&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;– 4&lt;/P&gt;&lt;/LI&gt;&lt;/OL&gt;&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Sat, 30 Jun 2018 14:48:41 GMT</pubDate>
    <dc:creator>Laiju</dc:creator>
    <dc:date>2018-06-30T14:48:41Z</dc:date>
    <item>
      <title>Williams Deisgn 6*3 model, sample size calculation</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Williams-Deisgn-6-3-model-sample-size-calculation/m-p/474674#M24701</link>
      <description>&lt;P&gt;Hi Everyone,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;How can we calculate the sample size for a 6*3 Williams model in non central t-distribution. The equation I have is below code. But I am stuck and is not able to go ahead. Any help would be of great use.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks in advance.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;DIV class="sectionInfo"&gt;3. Algorithm for Sample Size Calculation&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;/DIV&gt;&lt;P&gt;Let&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;SPAN class="equationTd"&gt;&lt;SPAN class="MathJax" style="display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 16px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative;"&gt;&lt;SPAN class="math"&gt;&lt;SPAN&gt;&lt;SPAN class="mrow"&gt;&lt;SPAN class="msubsup"&gt;&lt;SPAN class="mover"&gt;&lt;SPAN class="mi"&gt;σ&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;ˆ&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;2&lt;/SPAN&gt;&lt;SPAN class="mi"&gt;e&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="MJX_Assistive_MathML"&gt;σˆe2&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&amp;nbsp;denote the residual intrasubject MSE from a historical study; with Method 1, the sample size can be calculated with the following algorithm:&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;&lt;P&gt;Set values for&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;α&lt;/I&gt;,&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;φ&lt;/I&gt;, and&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;(default&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;α&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 0.05,&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;φ&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 0.80, and&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 1);&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;Select a range of sample size (&lt;I&gt;N&lt;/I&gt;1,&lt;I&gt;N&lt;/I&gt;2), for each&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;N&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;∊ [&lt;I&gt;N&lt;/I&gt;1,&lt;I&gt;N&lt;/I&gt;2], and do the following:&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN class="equationTd"&gt;&lt;SPAN class="MathJax" style="display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 16px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px 2px 0px 0px; margin: 0px; position: relative;"&gt;&lt;SPAN class="math"&gt;&lt;SPAN&gt;&lt;SPAN class="mrow"&gt;&lt;SPAN class="msub"&gt;&lt;SPAN class="mi"&gt;V&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;1&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;=&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;1.5&lt;/SPAN&gt;&lt;SPAN class="msubsup"&gt;&lt;SPAN class="mover"&gt;&lt;SPAN class="mi"&gt;σ&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;ˆ&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mn"&gt;2&lt;/SPAN&gt;&lt;SPAN class="mi"&gt;e&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="mo"&gt;/&lt;/SPAN&gt;&lt;SPAN class="mi"&gt;N&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN class="MJX_Assistive_MathML"&gt;V1=1.5σˆe2/N&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;I&gt;τ&lt;/I&gt;1&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= [log(&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;) – log(▵&lt;I&gt;L&lt;/I&gt;) ] /&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;V&lt;/I&gt;1&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;I&gt;τ&lt;/I&gt;2&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= [log(&lt;I&gt;µT&lt;/I&gt;/&lt;I&gt;µR&lt;/I&gt;) – log(▵&lt;I&gt;U&lt;/I&gt;) ] /&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;V&lt;/I&gt;1&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;Calculate&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;PRNT&lt;/I&gt;(–&lt;I&gt;tν,α&lt;/I&gt;,&lt;I&gt;ν&lt;/I&gt;6×3,&lt;I&gt;τ&lt;/I&gt;2) –&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;PRNT&lt;/I&gt;(–&lt;I&gt;tν,α&lt;/I&gt;,&lt;I&gt;ν&lt;/I&gt;6×3,&lt;I&gt;τ&lt;/I&gt;1), where&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;PRNT&lt;/I&gt;(·) is the probability from a noncentral&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;t&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/I&gt;distribution, and&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;I&gt;ν&lt;/I&gt;6×3&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;= 2&lt;I&gt;N&lt;/I&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;– 4&lt;/P&gt;&lt;/LI&gt;&lt;/OL&gt;&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 30 Jun 2018 14:48:41 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Williams-Deisgn-6-3-model-sample-size-calculation/m-p/474674#M24701</guid>
      <dc:creator>Laiju</dc:creator>
      <dc:date>2018-06-30T14:48:41Z</dc:date>
    </item>
    <item>
      <title>Re: Williams Deisgn 6*3 model, sample size calculation</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Williams-Deisgn-6-3-model-sample-size-calculation/m-p/474918#M24712</link>
      <description>&lt;P&gt;You can &lt;A href="http://go.documentation.sas.com/?cdcId=pgmsascdc&amp;amp;cdcVersion=9.4_3.2&amp;amp;docsetId=lefunctionsref&amp;amp;docsetTarget=p0ifuqakq7u785n1qgdo3rkcidy3.htm&amp;amp;locale=en" target="_self"&gt;use the CDF function to compute the probability of a noncentral t distribution.&lt;/A&gt;&amp;nbsp; I am not an expert in this area, but I know that&amp;nbsp;&lt;A href="http://go.documentation.sas.com/?docsetId=statug&amp;amp;docsetTarget=statug_power_details24.htm&amp;amp;docsetVersion=14.3&amp;amp;locale=en" target="_self"&gt;PROC POWER also has support for noncentral t as part of its CUSTOM statement.&lt;/A&gt;&amp;nbsp;An expert like&amp;nbsp;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/9374"&gt;@IanWakeling&lt;/a&gt;&amp;nbsp;might be able to give more explicit advice.&lt;/P&gt;</description>
      <pubDate>Mon, 02 Jul 2018 14:38:42 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Williams-Deisgn-6-3-model-sample-size-calculation/m-p/474918#M24712</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2018-07-02T14:38:42Z</dc:date>
    </item>
    <item>
      <title>Re: Williams Deisgn 6*3 model, sample size calculation</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Williams-Deisgn-6-3-model-sample-size-calculation/m-p/475252#M24737</link>
      <description>&lt;P&gt;Just in case somebody is going to proceed with this thread: The article from which &lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/218566"&gt;@Laiju&lt;/a&gt;&amp;nbsp;apparently copied the algorithm can be found &lt;A href="https://www.researchgate.net/publication/258132134_Sample_Size_Calculation_for_Bioequivalence_Studies_Assessing_Drug_Effect_and_Food_Effect_at_the_Same_Time_With_a_3-Treatment_Williams_Design" target="_blank"&gt;here&lt;/A&gt;&amp;nbsp;(with much better readable formulas).&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;In principle, a SAS program implementing the algorithm would consist of only a few lines of code. Most of the terms in the formulas seem to be clearly defined. Moreover, the article contains a table of calculated values (Table 2, p. 245) for comparison. However, I was unable to replicate these values. I even tried to solve the equation for unclear parameters &lt;EM&gt;numerically&lt;/EM&gt; (given a few values from Table 2; without sophisticated tools such as SAS/OR, though), but didn't obtain satisfactory results.&lt;/P&gt;</description>
      <pubDate>Tue, 03 Jul 2018 16:37:21 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Williams-Deisgn-6-3-model-sample-size-calculation/m-p/475252#M24737</guid>
      <dc:creator>FreelanceReinh</dc:creator>
      <dc:date>2018-07-03T16:37:21Z</dc:date>
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