Re: [R] permutation test assumption?

2008-04-10 Thread Ramon Diaz-Uriarte
Just an additional note: what I find interesting (that is an
euphemism) is that a paper such as that got published on 2006 when a
whole bunch of detailed papers on the same topic had been published in
the past. For instance, the first I pick from the pile is by J.
Romano, On the behavior of randomization tests without a group
invariance assumption, JASA, 1990, 85 (411): 686-692. There are other
related papers on that same issue of JASA. The relevance of
same-variance assumption also shows up in permutation test textbooks
(including, I think, Manly's, Good's, Noreen's, etc).

Best,

R.


On Wed, Apr 9, 2008 at 9:11 PM, Greg Snow [EMAIL PROTECTED] wrote:
 A few comments,

  My first impression on reading that abstract was that it was complete 
 nonsense.  After thinking a bit about it and skimming the full article I 
 decided that it was nonsense, but nonsense that is important to research and 
 discuss (and therefore the paper is useful).

  Why is it nonsense?  The permutation test is a test of the null hypothesis 
 that the 2 (or k) groups are from the same distribution (or identically 
 distributed, or exchangable).  The abstract says that they looked at the type 
 I error rate when the 2 groups had different variances or other differences.  
 The type I error is defined when the null hypothesis is true, so computing a 
 type I error rate when the null is by definition false does not make sense.

  However, statisticians often do analyses where all the assumptions are not 
 necessarily true (is any population really distributed as a normal), but the 
 tests are close enough.  So with modern tools it is not suprising to see 
 people doing permutation tests without understanding what they are really 
 testing and the results may be close enough (or they might not be).  The 
 contribution of this paper is to test and see if the results are close enough 
 or not when you use a permutation test to test the null that the means are 
 equal when there are other differences in the groups.  Their answer is that 
 no, the results are not close enough and they suggest that if you want to 
 test for equality of means, but not identical distributions, then don't use a 
 permutation test.

  To expand on Thierry's original answer:

  If you are testing the correct hypotheses and doing a permutation test 
 correctly, then
  You can do permutation tests on an unbalanced design and it will still be 
 a correct test.  Unbalance could affect the power, which you would want to 
 take into account when designing a study, but does not affect the correctness 
 of the test (when used properly).

  Hope this helps,

  --
  Gregory (Greg) L. Snow Ph.D.
  Statistical Data Center
  Intermountain Healthcare
  [EMAIL PROTECTED]
  (801) 408-8111




   -Original Message-
   From: [EMAIL PROTECTED]
   [mailto:[EMAIL PROTECTED] On Behalf Of João Fadista
   Sent: Tuesday, April 08, 2008 4:10 PM


  To: ONKELINX, Thierry; r-help@r-project.org
   Subject: Re: [R] permutation test assumption?
  
   Dear Thierry,
  
   Thanks for the reply. But as you may read in the paper
   http://bioinformatics.oxfordjournals.org/cgi/content/abstract/
   22/18/2244 when the sample sizes are not the same there may
   be an increase in the Type I error rate.
  
   Comments will be appreciated.
  
   Best regards,
   João Fadista
  
  
   
  
   De: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
   Enviada: ter 08-04-2008 15:27
   Para: João Fadista; r-help@r-project.org
   Assunto: RE: [R] permutation test assumption?
  
  
  
   Dear João,
  
   You can do permutation tests on an unbalanced design.
  
   HTH,
  
   Thierry
  
  
   --
   --
   ir. Thierry Onkelinx
   Instituut voor natuur- en bosonderzoek / Research Institute
   for Nature and Forest Cel biometrie, methodologie en
   kwaliteitszorg / Section biometrics, methodology and quality
   assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32
   54/436 185 [EMAIL PROTECTED] www.inbo.be
  
   To call in the statistician after the experiment is done may
   be no more than asking him to perform a post-mortem
   examination: he may be able to say what the experiment died of.
   ~ Sir Ronald Aylmer Fisher
  
   The plural of anecdote is not data.
   ~ Roger Brinner
  
   The combination of some data and an aching desire for an
   answer does not ensure that a reasonable answer can be
   extracted from a given body of data.
   ~ John Tukey
  
   -Oorspronkelijk bericht-
   Van: [EMAIL PROTECTED]
   [mailto:[EMAIL PROTECTED] Namens João Fadista
   Verzonden: dinsdag 8 april 2008 15:18
   Aan: r-help@r-project.org
   Onderwerp: [R] permutation test assumption?
  
   Dear all,
  
   Can I do a permutation test if the number of individuals in
   one group is much bigger than in the other group? I searched
   the literature but I didin´t find any assumption that refers
   to this subject

Re: [R] permutation test assumption?

2008-04-09 Thread Greg Snow
A few comments,

My first impression on reading that abstract was that it was complete nonsense. 
 After thinking a bit about it and skimming the full article I decided that it 
was nonsense, but nonsense that is important to research and discuss (and 
therefore the paper is useful).

Why is it nonsense?  The permutation test is a test of the null hypothesis that 
the 2 (or k) groups are from the same distribution (or identically distributed, 
or exchangable).  The abstract says that they looked at the type I error rate 
when the 2 groups had different variances or other differences.  The type I 
error is defined when the null hypothesis is true, so computing a type I error 
rate when the null is by definition false does not make sense.

However, statisticians often do analyses where all the assumptions are not 
necessarily true (is any population really distributed as a normal), but the 
tests are close enough.  So with modern tools it is not suprising to see people 
doing permutation tests without understanding what they are really testing and 
the results may be close enough (or they might not be).  The contribution of 
this paper is to test and see if the results are close enough or not when you 
use a permutation test to test the null that the means are equal when there are 
other differences in the groups.  Their answer is that no, the results are not 
close enough and they suggest that if you want to test for equality of means, 
but not identical distributions, then don't use a permutation test.

To expand on Thierry's original answer:

If you are testing the correct hypotheses and doing a permutation test 
correctly, then
You can do permutation tests on an unbalanced design and it will still be a 
correct test.  Unbalance could affect the power, which you would want to take 
into account when designing a study, but does not affect the correctness of the 
test (when used properly).

Hope this helps,

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
[EMAIL PROTECTED]
(801) 408-8111
 
 

 -Original Message-
 From: [EMAIL PROTECTED] 
 [mailto:[EMAIL PROTECTED] On Behalf Of João Fadista
 Sent: Tuesday, April 08, 2008 4:10 PM
 To: ONKELINX, Thierry; r-help@r-project.org
 Subject: Re: [R] permutation test assumption?
 
 Dear Thierry,
  
 Thanks for the reply. But as you may read in the paper 
 http://bioinformatics.oxfordjournals.org/cgi/content/abstract/
 22/18/2244 when the sample sizes are not the same there may 
 be an increase in the Type I error rate.
  
 Comments will be appreciated.
  
 Best regards,
 João Fadista
  
 
 
 
 De: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
 Enviada: ter 08-04-2008 15:27
 Para: João Fadista; r-help@r-project.org
 Assunto: RE: [R] permutation test assumption?
 
 
 
 Dear João,
 
 You can do permutation tests on an unbalanced design.
 
 HTH,
 
 Thierry
 
 
 --
 --
 ir. Thierry Onkelinx
 Instituut voor natuur- en bosonderzoek / Research Institute 
 for Nature and Forest Cel biometrie, methodologie en 
 kwaliteitszorg / Section biometrics, methodology and quality 
 assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 
 54/436 185 [EMAIL PROTECTED] www.inbo.be
 
 To call in the statistician after the experiment is done may 
 be no more than asking him to perform a post-mortem 
 examination: he may be able to say what the experiment died of.
 ~ Sir Ronald Aylmer Fisher
 
 The plural of anecdote is not data.
 ~ Roger Brinner
 
 The combination of some data and an aching desire for an 
 answer does not ensure that a reasonable answer can be 
 extracted from a given body of data.
 ~ John Tukey
 
 -Oorspronkelijk bericht-
 Van: [EMAIL PROTECTED] 
 [mailto:[EMAIL PROTECTED] Namens João Fadista
 Verzonden: dinsdag 8 april 2008 15:18
 Aan: r-help@r-project.org
 Onderwerp: [R] permutation test assumption?
 
 Dear all,
 
 Can I do a permutation test if the number of individuals in 
 one group is much bigger than in the other group? I searched 
 the literature but I didin´t find any assumption that refers 
 to this subject for permutation tests.
 
 
 Best regards
 
 João Fadista
 Ph.d. student
 
 

  UNIVERSITY OF AARHUS  
 Faculty of Agricultural Sciences   
 Dept. of Genetics and Biotechnology
 Blichers Allé 20, P.O. BOX 50
 DK-8830 Tjele  

 Phone:   +45 8999 1900 
 Direct:  +45 8999 1900 
 E-mail:  [EMAIL PROTECTED] 
 mailto:[EMAIL PROTECTED]
 Web: www.agrsci.org http://www.agrsci.org/   
 
 
 DJF now offers new degree programmes 
 http://www.agrsci.org/content/view/full/34133 .
 
 News and news media 
 http://www.agrsci.org/navigation/nyheder_og_presse .
 
 This email may contain information that is confidential. Any 
 use or publication of this email without written permission 
 from Faculty of Agricultural Sciences is not allowed. If you

[R] permutation test assumption?

2008-04-08 Thread João Fadista
Dear all,
 
Can I do a permutation test if the number of individuals in one group is much 
bigger than in the other group? I searched the literature but I didin´t find 
any assumption that refers to this subject for permutation tests.
 

Best regards

João Fadista
Ph.d. student



 UNIVERSITY OF AARHUS   
Faculty of Agricultural Sciences
Dept. of Genetics and Biotechnology 
Blichers Allé 20, P.O. BOX 50   
DK-8830 Tjele   

Phone:   +45 8999 1900  
Direct:  +45 8999 1900  
E-mail:  [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]   
Web: www.agrsci.org http://www.agrsci.org/


DJF now offers new degree programmes 
http://www.agrsci.org/content/view/full/34133 . 

News and news media http://www.agrsci.org/navigation/nyheder_og_presse .

This email may contain information that is confidential. Any use or publication 
of this email without written permission from Faculty of Agricultural Sciences 
is not allowed. If you are not the intended recipient, please notify Faculty of 
Agricultural Sciences immediately and delete this email.




[[alternative HTML version deleted]]

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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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Re: [R] permutation test assumption?

2008-04-08 Thread ONKELINX, Thierry
Dear João,

You can do permutation tests on an unbalanced design. 

HTH,

Thierry



ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and 
Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology 
and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
[EMAIL PROTECTED] 
www.inbo.be 

To call in the statistician after the experiment is done may be no more than 
asking him to perform a post-mortem examination: he may be able to say what the 
experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure 
that a reasonable answer can be extracted from a given body of data.
~ John Tukey

-Oorspronkelijk bericht-
Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens João Fadista
Verzonden: dinsdag 8 april 2008 15:18
Aan: r-help@r-project.org
Onderwerp: [R] permutation test assumption?

Dear all,

Can I do a permutation test if the number of individuals in one group is much 
bigger than in the other group? I searched the literature but I didin´t find 
any assumption that refers to this subject for permutation tests.


Best regards

João Fadista
Ph.d. student



 UNIVERSITY OF AARHUS   
Faculty of Agricultural Sciences
Dept. of Genetics and Biotechnology 
Blichers Allé 20, P.O. BOX 50   
DK-8830 Tjele   

Phone:   +45 8999 1900  
Direct:  +45 8999 1900  
E-mail:  [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]   
Web: www.agrsci.org http://www.agrsci.org/


DJF now offers new degree programmes 
http://www.agrsci.org/content/view/full/34133 . 

News and news media http://www.agrsci.org/navigation/nyheder_og_presse .

This email may contain information that is confidential. Any use or publication 
of this email without written permission from Faculty of Agricultural Sciences 
is not allowed. If you are not the intended recipient, please notify Faculty of 
Agricultural Sciences immediately and delete this email.




[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


Re: [R] permutation test assumption?

2008-04-08 Thread João Fadista
Dear Thierry,
 
Thanks for the reply. But as you may read in the paper 
http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/18/2244 when 
the sample sizes are not the same there may be an increase in the Type I error 
rate.
 
Comments will be appreciated.
 
Best regards,
João Fadista
 



De: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
Enviada: ter 08-04-2008 15:27
Para: João Fadista; r-help@r-project.org
Assunto: RE: [R] permutation test assumption?



Dear João,

You can do permutation tests on an unbalanced design.

HTH,

Thierry



ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and 
Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology 
and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
[EMAIL PROTECTED]
www.inbo.be

To call in the statistician after the experiment is done may be no more than 
asking him to perform a post-mortem examination: he may be able to say what the 
experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure 
that a reasonable answer can be extracted from a given body of data.
~ John Tukey

-Oorspronkelijk bericht-
Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens João Fadista
Verzonden: dinsdag 8 april 2008 15:18
Aan: r-help@r-project.org
Onderwerp: [R] permutation test assumption?

Dear all,

Can I do a permutation test if the number of individuals in one group is much 
bigger than in the other group? I searched the literature but I didin´t find 
any assumption that refers to this subject for permutation tests.


Best regards

João Fadista
Ph.d. student


   
 UNIVERSITY OF AARHUS  
Faculty of Agricultural Sciences   
Dept. of Genetics and Biotechnology
Blichers Allé 20, P.O. BOX 50  
DK-8830 Tjele  
   
Phone:   +45 8999 1900 
Direct:  +45 8999 1900 
E-mail:  [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]
Web: www.agrsci.org http://www.agrsci.org/   


DJF now offers new degree programmes 
http://www.agrsci.org/content/view/full/34133 .

News and news media http://www.agrsci.org/navigation/nyheder_og_presse .

This email may contain information that is confidential. Any use or publication 
of this email without written permission from Faculty of Agricultural Sciences 
is not allowed. If you are not the intended recipient, please notify Faculty of 
Agricultural Sciences immediately and delete this email.




[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


Re: [R] permutation test assumption?

2008-04-08 Thread Achim Zeileis
On Wed, 9 Apr 2008, João Fadista wrote:

 Dear Thierry,

 Thanks for the reply. But as you may read in the paper
 http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/18/2244
 when the sample sizes are not the same there may be an increase in the
 Type I error rate.

No, this is false and not what the reference above says. Please read more
carefully.

 Comments will be appreciated.

The basic assumption for permutation tests is exchangeability of the
observations (regardless of sample sizes). The reference above describes a
situation when this assumption is violated.
Z

 Best regards,
 João Fadista


 

 De: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
 Enviada: ter 08-04-2008 15:27
 Para: João Fadista; r-help@r-project.org
 Assunto: RE: [R] permutation test assumption?



 Dear João,

 You can do permutation tests on an unbalanced design.

 HTH,

 Thierry


 
 ir. Thierry Onkelinx
 Instituut voor natuur- en bosonderzoek / Research Institute for Nature and 
 Forest
 Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, 
 methodology and quality assurance
 Gaverstraat 4
 9500 Geraardsbergen
 Belgium
 tel. + 32 54/436 185
 [EMAIL PROTECTED]
 www.inbo.be

 To call in the statistician after the experiment is done may be no more than 
 asking him to perform a post-mortem examination: he may be able to say what 
 the experiment died of.
 ~ Sir Ronald Aylmer Fisher

 The plural of anecdote is not data.
 ~ Roger Brinner

 The combination of some data and an aching desire for an answer does not 
 ensure that a reasonable answer can be extracted from a given body of data.
 ~ John Tukey

 -Oorspronkelijk bericht-
 Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens João Fadista
 Verzonden: dinsdag 8 april 2008 15:18
 Aan: r-help@r-project.org
 Onderwerp: [R] permutation test assumption?

 Dear all,

 Can I do a permutation test if the number of individuals in one group is much 
 bigger than in the other group? I searched the literature but I didin´t find 
 any assumption that refers to this subject for permutation tests.


 Best regards

 João Fadista
 Ph.d. student



  UNIVERSITY OF AARHUS
 Faculty of Agricultural Sciences
 Dept. of Genetics and Biotechnology
 Blichers Allé 20, P.O. BOX 50
 DK-8830 Tjele

 Phone:   +45 8999 1900
 Direct:  +45 8999 1900
 E-mail:  [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]
 Web: www.agrsci.org http://www.agrsci.org/
 

 DJF now offers new degree programmes 
 http://www.agrsci.org/content/view/full/34133 .

 News and news media http://www.agrsci.org/navigation/nyheder_og_presse .

 This email may contain information that is confidential. Any use or 
 publication of this email without written permission from Faculty of 
 Agricultural Sciences is not allowed. If you are not the intended recipient, 
 please notify Faculty of Agricultural Sciences immediately and delete this 
 email.




 [[alternative HTML version deleted]]

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 R-help@r-project.org mailing list
 https://stat.ethz.ch/mailman/listinfo/r-help
 PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


Re: [R] permutation test assumption?

2008-04-08 Thread João Fadista
But in that paper they refer to another 
(http://www.bepress.com/cgi/viewcontent.cgi?article=1053context=ucbbiostat) 
where they say that permutation distribution produces an asymptotically 
correct null distribution if (i) the sample sizes are equal
 
Best regards,
João



De: Achim Zeileis [mailto:[EMAIL PROTECTED]
Enviada: qua 09-04-2008 0:26
Para: João Fadista
Cc: ONKELINX, Thierry; r-help@r-project.org
Assunto: Re: [R] permutation test assumption?



On Wed, 9 Apr 2008, João Fadista wrote:

 Dear Thierry,

 Thanks for the reply. But as you may read in the paper
 http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/18/2244
 when the sample sizes are not the same there may be an increase in the
 Type I error rate.

No, this is false and not what the reference above says. Please read more
carefully.

 Comments will be appreciated.

The basic assumption for permutation tests is exchangeability of the
observations (regardless of sample sizes). The reference above describes a
situation when this assumption is violated.
Z

 Best regards,
 João Fadista


 

 De: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
 Enviada: ter 08-04-2008 15:27
 Para: João Fadista; r-help@r-project.org
 Assunto: RE: [R] permutation test assumption?



 Dear João,

 You can do permutation tests on an unbalanced design.

 HTH,

 Thierry


 
 ir. Thierry Onkelinx
 Instituut voor natuur- en bosonderzoek / Research Institute for Nature and 
 Forest
 Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, 
 methodology and quality assurance
 Gaverstraat 4
 9500 Geraardsbergen
 Belgium
 tel. + 32 54/436 185
 [EMAIL PROTECTED]
 www.inbo.be

 To call in the statistician after the experiment is done may be no more than 
 asking him to perform a post-mortem examination: he may be able to say what 
 the experiment died of.
 ~ Sir Ronald Aylmer Fisher

 The plural of anecdote is not data.
 ~ Roger Brinner

 The combination of some data and an aching desire for an answer does not 
 ensure that a reasonable answer can be extracted from a given body of data.
 ~ John Tukey

 -Oorspronkelijk bericht-
 Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens João Fadista
 Verzonden: dinsdag 8 april 2008 15:18
 Aan: r-help@r-project.org
 Onderwerp: [R] permutation test assumption?

 Dear all,

 Can I do a permutation test if the number of individuals in one group is much 
 bigger than in the other group? I searched the literature but I didin´t find 
 any assumption that refers to this subject for permutation tests.


 Best regards

 João Fadista
 Ph.d. student



  UNIVERSITY OF AARHUS
 Faculty of Agricultural Sciences
 Dept. of Genetics and Biotechnology
 Blichers Allé 20, P.O. BOX 50
 DK-8830 Tjele

 Phone:   +45 8999 1900
 Direct:  +45 8999 1900
 E-mail:  [EMAIL PROTECTED] mailto:[EMAIL PROTECTED]
 Web: www.agrsci.org http://www.agrsci.org/
 

 DJF now offers new degree programmes 
 http://www.agrsci.org/content/view/full/34133 .

 News and news media http://www.agrsci.org/navigation/nyheder_og_presse .

 This email may contain information that is confidential. Any use or 
 publication of this email without written permission from Faculty of 
 Agricultural Sciences is not allowed. If you are not the intended recipient, 
 please notify Faculty of Agricultural Sciences immediately and delete this 
 email.




 [[alternative HTML version deleted]]

 __
 R-help@r-project.org mailing list
 https://stat.ethz.ch/mailman/listinfo/r-help
 PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
 and provide commented, minimal, self-contained, reproducible code.



__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


Re: [R] permutation test assumption?

2008-04-08 Thread Achim Zeileis
On Wed, 9 Apr 2008, João Fadista wrote:

 But in that paper they refer to another
 (http://www.bepress.com/cgi/viewcontent.cgi?article=1053context=ucbbiostat)
 where they say that permutation distribution produces an asymptotically
 correct null distribution if (i) the sample sizes are equal

I haven't read that paper in detail (but so do you, it seems). From
looking at abstract and intro, my understanding is that they also study
the behaviour of tests under weaker assumptions than exchangeability.
Z

 Best regards,
 João

 

 De: Achim Zeileis [mailto:[EMAIL PROTECTED]
 Enviada: qua 09-04-2008 0:26
 Para: João Fadista
 Cc: ONKELINX, Thierry; r-help@r-project.org
 Assunto: Re: [R] permutation test assumption?



 On Wed, 9 Apr 2008, João Fadista wrote:

  Dear Thierry,
 
  Thanks for the reply. But as you may read in the paper
  http://bioinformatics.oxfordjournals.org/cgi/content/abstract/22/18/2244
  when the sample sizes are not the same there may be an increase in the
  Type I error rate.

 No, this is false and not what the reference above says. Please read more
 carefully.

  Comments will be appreciated.

 The basic assumption for permutation tests is exchangeability of the
 observations (regardless of sample sizes). The reference above describes a
 situation when this assumption is violated.
 Z

  Best regards,
  João Fadista
 
 
  
 
  De: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
  Enviada: ter 08-04-2008 15:27
  Para: João Fadista; r-help@r-project.org
  Assunto: RE: [R] permutation test assumption?
 
 
 
  Dear João,
 
  You can do permutation tests on an unbalanced design.
 
  HTH,
 
  Thierry
 
 
  
  ir. Thierry Onkelinx
  Instituut voor natuur- en bosonderzoek / Research Institute for Nature and 
  Forest
  Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, 
  methodology and quality assurance
  Gaverstraat 4
  9500 Geraardsbergen
  Belgium
  tel. + 32 54/436 185
  [EMAIL PROTECTED]
  www.inbo.be
 
  To call in the statistician after the experiment is done may be no more 
  than asking him to perform a post-mortem examination: he may be able to say 
  what the experiment died of.
  ~ Sir Ronald Aylmer Fisher
 
  The plural of anecdote is not data.
  ~ Roger Brinner
 
  The combination of some data and an aching desire for an answer does not 
  ensure that a reasonable answer can be extracted from a given body of data.
  ~ John Tukey
 
  -Oorspronkelijk bericht-
  Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens João Fadista
  Verzonden: dinsdag 8 april 2008 15:18
  Aan: r-help@r-project.org
  Onderwerp: [R] permutation test assumption?
 
  Dear all,
 
  Can I do a permutation test if the number of individuals in one group is 
  much bigger than in the other group? I searched the literature but I 
  didin´t find any assumption that refers to this subject for permutation 
  tests.
 
 
  Best regards
 
  João Fadista
  Ph.d. student
 
 
 
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