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<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'>A search for authors Maxwell and Delaney
at the <st1:place w:st="on"><st1:PlaceType w:st="on">University</st1:PlaceType>
 of <st1:PlaceName w:st="on">Kentucky</st1:PlaceName></st1:place> library
online catalog reveals:<o:p></o:p></span></font></p>

<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'><o:p>&nbsp;</o:p></span></font></p>

<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'>Maxwell, S.E., and Delaney, H.D., 1999,
Designing Experiments and Analyzing Data: A Model Comparison Perspective: <st1:City
w:st="on"><st1:place w:st="on">Lawrence</st1:place></st1:City> Erlbaum, 902 p. ISBN
9780805837063 (ebook ISBN 9780585282459).<o:p></o:p></span></font></p>

<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'><o:p>&nbsp;</o:p></span></font></p>

<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'>The volume is available electronically and
I note there is a discussion of Wilks-lambda on page 657.<o:p></o:p></span></font></p>

<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'><o:p>&nbsp;</o:p></span></font></p>

<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'>Not being a statistician, I have reached
the limit of what help I can provide.<o:p></o:p></span></font></p>

<p class=MsoNormal><font size=2 color=navy face=Arial><span style='font-size:
10.0pt;font-family:Arial;color:navy'><o:p>&nbsp;</o:p></span></font></p>

<p class=MsoNormal><st1:City w:st="on"><st1:place w:st="on"><font size=2
  color=navy face=Arial><span style='font-size:10.0pt;font-family:Arial;
  color:navy'>Brandon</span></font></st1:place></st1:City><font size=2
color=navy face=Arial><span style='font-size:10.0pt;font-family:Arial;
color:navy'><o:p></o:p></span></font></p>

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<p class=MsoNormal><b><font size=2 face=Tahoma><span style='font-size:10.0pt;
font-family:Tahoma;font-weight:bold'>From:</span></font></b><font size=2
face=Tahoma><span style='font-size:10.0pt;font-family:Tahoma'>
scipy-user-bounces@scipy.org [mailto:scipy-user-bounces@scipy.org] <b><span
style='font-weight:bold'>On Behalf Of </span></b>Matthieu Brucher<br>
<b><span style='font-weight:bold'>Sent:</span></b> Thursday, September 27, 2007
5:36 PM<br>
<b><span style='font-weight:bold'>To:</span></b> SciPy Users List<br>
<b><span style='font-weight:bold'>Subject:</span></b> Re: [SciPy-user]
Signification of parameters</span></font><o:p></o:p></p>

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<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'><o:p>&nbsp;</o:p></span></font></p>

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face="Times New Roman"><span style='font-size:12.0pt'><o:p>&nbsp;</o:p></span></font></p>

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<p class=MsoNormal><span class=gmailquote><font size=3 face="Times New Roman"><span
style='font-size:12.0pt'>2007/9/27, <st1:PersonName w:st="on">Nuttall, Brandon
 C</st1:PersonName> &lt;<a href="mailto:bnuttall@uky.edu">bnuttall@uky.edu</a>&gt;:</span></font></span><o:p></o:p></p>

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<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>Matthieu</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&nbsp;</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>I've never used the function, but&#8230;</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&nbsp;</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&gt;&gt;&gt; from scipy.stats import f_value_wilks_lambda</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&gt;&gt;&gt; help(f_value_wilks_lambda)</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>Help on function f_value_wilks_lambda in module
scipy.stats.stats:</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&nbsp;</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span lang=DE style='font-size:10.0pt;
font-family:Arial;color:navy'>f_value_wilks_lambda(ER, EF, dfnum, dfden, a, b)</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span lang=DE style='font-size:10.0pt;
font-family:Arial;color:navy'>&nbsp;&nbsp;&nbsp; </span></font><font size=2
color=navy face=Arial><span style='font-size:10.0pt;font-family:Arial;
color:navy'>Calculation of Wilks lambda F-statistic for multivarite data, per</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&nbsp;&nbsp;&nbsp; Maxwell &amp; Delaney p.657.</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&nbsp;</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&gt;&gt;&gt;&nbsp;</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>&nbsp;</span></font><o:p></o:p></p>

<p><font size=2 color=navy face=Arial><span style='font-size:10.0pt;font-family:
Arial;color:navy'>I suggest you try the reference. You might also find
additional info by looking at the Python source code.</span></font><o:p></o:p></p>

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<p class=MsoNormal><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'><br>
Thank you for the answer but I already tried the code, but no explanation, and
looking on the web didn't help me find an explanation of the algorithm. I don't
know if I can access somewhere the book, I'll try, but if someone has it,
please let us know the meaning of the special parameters ;) <br>
<br>
Matthieu<o:p></o:p></span></font></p>

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