Re: [R] dummy encoding in metafor

2013-01-28 Thread Viechtbauer Wolfgang (STAT)
Dear Alma,

either there is a whole lot of miscommunicaton here, or you (and your 
supervisor) are way in over your head.

You say that you are working with Cohen's d values. And you mentioned CMA. So, 
let me ask you some questions:

1) Has CMA computed those d values for you?
2) If yes, what information did you supply to CMA for the computation of those 
d values? (means, standard deviations, and the sample sizes of the two groups?)
3) Did CMA then provide you with a column of values that are the corresponding 
sampling variances or standard errors? (those values should NOT all be equal to 
1!)

Best,
Wolfgang

 -Original Message-
 From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
 On Behalf Of Alma Wilflinger
 Sent: Sunday, January 27, 2013 21:52
 To: Michael Dewey; r-help@r-project.org
 Subject: Re: [R] dummy encoding in metafor
 
 Hi Michael!
 
 Yes, I do use Cohens d. As a matter of fact my thesis supervisor told me
 to use 1 as the value for standard deviation for all of my studies.
 Unfortunately I am not totally sure myself why to do this have you ever
 used such an approach?
 
 kind regards,
 Alma
 
 
  From: Michael Dewey i...@aghmed.fsnet.co.uk
 
 t.co.uk; r-help@r-project.org r-help@r-project.org
 Sent: Thursday, January 24, 2013 6:57 PM
 Subject: Re: [R] dummy encoding in metafor
 
 At 22:06 23/01/2013, Alma Wilflinger wrote:
 
  Hi Michael,
 
  The supervisor for my Master's Thesis told me that my means are the
 effect size and cause of this I have to take figure 1 for all standard
 deviations. So I hope that was the right information.
 
 Alma
 There is a fairly comprehensive list of all the things which might be an
 effect size on
 http://en.wikipedia.org/wiki/Effect_size
 Is what you call Mean one of them?
 
 
 
  From: Michael Dewey i...@aghmed.fsnet.co.uk
 
 wolfgang.viechtba...@maastrichtuniversity.nl; Michael Dewey
 i...@aghmed.fsnet.co.uk; r-help@r-project.org r-help@r-project.org
  Sent: Wednesday, January 23, 2013 10:22 AM
  Subject: Re: [R] dummy encoding in metafor
 
  At 08:30 23/01/2013, Alma Wilflinger wrote:
   Dear Wolfgang and Michael,
  
 [[elided Yahoo spam]]
  
   Concerning the Variance: I took the variance I used for CMA (which
 is always 1), so I think it should be the right one.
 
  It seems unlikely to me that the variance from each study would be the
 same although I suppose it could be possible. Are you sure you are
 supplying the right values to CMA?
 
 
   Thank you for noticing and mentioning though :)
  
   I really appreciate how helpful you both are.
  
   best,
   Alma

__
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] dummy encoding in metafor

2013-01-28 Thread Alma Wilflinger
Dear Wolfgang,

Thank you very much for answering!

1) No, I am doing a Meta Analysis and take the
 ds from existing studies. To be exactly, I do use D (Means of 
D-Measure which is not exactly d, but very similar) 
3) Yes CMA makes a new column with st. error and variance differ from 1.

for
 example my mean is 0,6, and I take 1 for the st. dev and 154 is my N, the new 
values are 0,080582 for the st. error and 6,49E-03 for the 
variance

So did I make a mistake by taking the parameters for R?
vi is my mean
yi is my variance. I took the uncalculated variance which is 1. is this wrong? 
do I have to take the variances from the new column from CMA?

kind regards,
alma



 From: Viechtbauer Wolfgang (STAT) 
wolfgang.viechtba...@maastrichtuniversity.nl

t.co.uk; r-help@r-project.org r-help@r-project.org 
Sent: Monday, January 28, 2013 10:38 AM
Subject: RE: [R] dummy encoding in metafor

Dear Alma,

either there is a whole lot of miscommunicaton here, or you (and your 
supervisor) are way in over your head.

You say that you are working with Cohen's d values. And you mentioned CMA. So, 
let me ask you some questions:

1) Has CMA computed those d values for you?
2) If yes, what information did you supply to CMA for the computation of those 
d values? (means, standard deviations, and the sample sizes of the two groups?)
3) Did CMA then provide you with a column of values that are the corresponding 
sampling variances or standard errors? (those values should NOT all be equal to 
1!)

Best,
Wolfgang

 -Original Message-
 From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
 On Behalf Of Alma Wilflinger
 Sent: Sunday, January 27, 2013 21:52
 To: Michael Dewey; r-help@r-project.org
 Subject: Re: [R] dummy encoding in metafor
 
 Hi Michael!
 
 Yes, I do use Cohens d. As a matter of fact my thesis supervisor told me
 to use 1 as the value for standard deviation for all of my studies.
 Unfortunately I am not totally sure myself why to do this have you ever
 used such an approach?
 
 kind regards,
 Alma
 
 
  From: Michael Dewey i...@aghmed.fsnet.co.uk
 
 t.co.uk; r-help@r-project.org r-help@r-project.org
 Sent: Thursday, January 24, 2013 6:57 PM
 Subject: Re: [R] dummy encoding in metafor
 
 At 22:06 23/01/2013, Alma Wilflinger wrote:
 
  Hi Michael,
 
  The supervisor for my Master's Thesis told me that my means are the
 effect size and cause of this I have to take figure 1 for all standard
 deviations. So I hope that was the right information.
 
 Alma
 There is a fairly comprehensive list of all the things which might be an
 effect size on
 http://en.wikipedia.org/wiki/Effect_size
 Is what you call Mean one of them?
 
 
 
  From: Michael Dewey i...@aghmed.fsnet.co.uk
 
 wolfgang.viechtba...@maastrichtuniversity.nl; Michael Dewey
 i...@aghmed.fsnet.co.uk; r-help@r-project.org r-help@r-project.org
  Sent: Wednesday, January 23, 2013 10:22 AM
  Subject: Re: [R] dummy encoding in metafor
 
  At 08:30 23/01/2013, Alma Wilflinger wrote:
   Dear Wolfgang and Michael,
  
 [[elided Yahoo spam]]
  
   Concerning the Variance: I took the variance I used for CMA (which
 is always 1), so I think it should be the right one.
 
  It seems unlikely to me that the variance from each study would be the
 same although I suppose it could be possible. Are you sure you are
 supplying the right values to CMA?
 
 
   Thank you for noticing and mentioning though :)
  
   I really appreciate how helpful you both are.
  
   best,
   Alma
[[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] dummy encoding in metafor

2013-01-27 Thread Alma Wilflinger
Hi Michael!

Yes, I do use Cohens d. As a matter of fact my thesis supervisor told me to use 
1 as the value for standard deviation for all of my studies.
Unfortunately I am not totally sure myself why to do this have you ever used 
such an approach?

kind regards,
Alma





 From: Michael Dewey i...@aghmed.fsnet.co.uk

t.co.uk; r-help@r-project.org r-help@r-project.org 
Sent: Thursday, January 24, 2013 6:57 PM
Subject: Re: [R] dummy encoding in metafor

At 22:06 23/01/2013, Alma Wilflinger wrote:

 Hi Michael,
 
 The supervisor for my Master's Thesis told me that my means are the effect 
 size and cause of this I have to take figure 1 for all standard deviations. 
 So I hope that was the right information.

Alma
There is a fairly comprehensive list of all the things which might be an effect 
size on
http://en.wikipedia.org/wiki/Effect_size
Is what you call Mean one of them?


 
 From: Michael Dewey i...@aghmed.fsnet.co.uk

wolfgang.viechtba...@maastrichtuniversity.nl; Michael Dewey 
i...@aghmed.fsnet.co.uk; r-help@r-project.org r-help@r-project.org
 Sent: Wednesday, January 23, 2013 10:22 AM
 Subject: Re: [R] dummy encoding in metafor
 
 At 08:30 23/01/2013, Alma Wilflinger wrote:
  Dear Wolfgang and Michael,
 
[[elided Yahoo spam]]
 
  Concerning the Variance: I took the variance I used for CMA (which is 
  always 1), so I think it should be the right one.
 
 It seems unlikely to me that the variance from each study would be the same 
 although I suppose it could be possible. Are you sure you are supplying the 
 right values to CMA?
 
 
  Thank you for noticing and mentioning though :)
 
  I really appreciate how helpful you both are.
 
  best,
  Alma
 
 
 
  From: Viechtbauer Wolfgang (STAT) 
  mailto:wolfgang.viechtba...@maastrichtuniversity.nlwolfgang.viechtba...@maastrichtuniversity.nl
  To: Michael Dewey mailto:i...@aghmed.fsnet.co.uki...@aghmed.fsnet.co
mailto:r-help@r-project.orgr-help@r-project.org 
mailto:r-help@r-project.orgr-help@r-project.org
  Sent: Monday, January 21, 2013 11:10 AM
  Subject: RE: [R] dummy encoding in metafor
 
  As Michael already mentioned, the error:
 
  Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve
 
  indeed indicates that your design matrix is not of full rank (i.e., there 
  are linear dependencies among your predictors). With this many factors in 
  the same model, this is not surprising if k is only 94 (which is actually 
  quite large for a meta-analysis). One options is to leave out some of the 
  predictors. You can also try collapsing some of the levels of the factors. 
  Of course, you lose some details that way, but apparently you don't have 
  enough data in the first place to carry out such a detailed analysis.
 
  One other thing I noticed. You wrote:
 
  rma(yi=Mean, vi=Variance, ni=N.1, ...)
 
  I suspect that your variable Variance is actually the variance of the raw 
  scores. However, the vi argument is used to pass the sampling variances of 
  the yi values to the function -- not the variance of raw scores. The 
  (estimated) sampling variance of a mean is s^2 / n, so if I am not 
  mistaken, you really want to use:
 
  rma(yi=Mean, vi=Variance/N.1, ...)
 
  Best,
  Wolfgang
 
  --
  Wolfgang Viechtbauer, Ph.D., Statistician
  Department of Psychiatry and Psychology
  School for Mental Health and Neuroscience
  Faculty of Health, Medicine, and Life Sciences
  Maastricht University, P.O. Box 616 (VIJV1)
  6200 MD Maastricht, The Netherlands
  +31 (43) 388-4170 | http://www.wvbauer.com
 
   -Original Message-
   From: 
   mailto:r-help-boun...@r-project.orgmailto:r-help-boun...@r-project.orgr-help-boun...@r-project.org
[mailto:r-help-boun...@r-project.org]
   On Behalf Of Michael Dewey
   Sent: Monday, January 21, 2013 10:40
   To: Alma Wilflinger; Michael Dewey; 
   mailto:r-help@r-project.orgmailto:r-help@r-project.orgr-help@r-project.org
   Subject: Re: [R] dummy encoding in metafor
  
   At 14:48 20/01/2013, Alma Wilflinger wrote:
   Hi,
   
   thank you very much for your kind answer.
   
If you look a bit further down the manual page you will see
### using a model formula to specify the same model
rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
btt=c(2,3))
   
which is much easier.
   
   I have seen the possibility of using a model formula for dummy
   encoding and you are right it is much easier than doing it by hand.
   Thing is that if I include some moderator variables into the
   parameters I get the error:
   
   Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve
  
   I suspect that you have a linear dependence between your moderator
   variables. Depending on how many levels there are for country,
   sample, and so on you do have a lot of predictors (you presumably
   know that a factor counts as levels-1 for this purpose?)
  
  
   For example this call works:
   result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country

Re: [R] dummy encoding in metafor

2013-01-24 Thread Michael Dewey

At 22:06 23/01/2013, Alma Wilflinger wrote:


Hi Michael,

The supervisor for my Master's Thesis told me that my means are the 
effect size and cause of this I have to take figure 1 for all 
standard deviations. So I hope that was the right information.


Alma
There is a fairly comprehensive list of all the things which might be 
an effect size on

http://en.wikipedia.org/wiki/Effect_size
Is what you call Mean one of them?




From: Michael Dewey i...@aghmed.fsnet.co.uk
To: Alma Wilflinger alma_an...@yahoo.com; Viechtbauer Wolfgang 
(STAT) wolfgang.viechtba...@maastrichtuniversity.nl; Michael Dewey 
i...@aghmed.fsnet.co.uk; r-help@r-project.org r-help@r-project.org

Sent: Wednesday, January 23, 2013 10:22 AM
Subject: Re: [R] dummy encoding in metafor

At 08:30 23/01/2013, Alma Wilflinger wrote:
 Dear Wolfgang and Michael,

 thank you very much for your help!

 Concerning the Variance: I took the variance I used for CMA 
(which is always 1), so I think it should be the right one.


It seems unlikely to me that the variance from each study would be 
the same although I suppose it could be possible. Are you sure you 
are supplying the right values to CMA?



 Thank you for noticing and mentioning though :)

 I really appreciate how helpful you both are.

 best,
 Alma



 From: Viechtbauer Wolfgang (STAT) 
mailto:wolfgang.viechtba...@maastrichtuniversity.nlwolfgang.viechtba...@maastrichtuniversity.nl
 To: Michael Dewey 
mailto:i...@aghmed.fsnet.co.uki...@aghmed.fsnet.co.uk; Alma 
Wilflinger mailto:alma_an...@yahoo.comalma_an...@yahoo.com; 
mailto:r-help@r-project.orgr-help@r-project.org 
mailto:r-help@r-project.orgr-help@r-project.org

 Sent: Monday, January 21, 2013 11:10 AM
 Subject: RE: [R] dummy encoding in metafor

 As Michael already mentioned, the error:

 Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve

 indeed indicates that your design matrix is not of full rank 
(i.e., there are linear dependencies among your predictors). With 
this many factors in the same model, this is not surprising if k is 
only 94 (which is actually quite large for a meta-analysis). One 
options is to leave out some of the predictors. You can also try 
collapsing some of the levels of the factors. Of course, you lose 
some details that way, but apparently you don't have enough data 
in the first place to carry out such a detailed analysis.


 One other thing I noticed. You wrote:

 rma(yi=Mean, vi=Variance, ni=N.1, ...)

 I suspect that your variable Variance is actually the variance 
of the raw scores. However, the vi argument is used to pass the 
sampling variances of the yi values to the function -- not the 
variance of raw scores. The (estimated) sampling variance of a mean 
is s^2 / n, so if I am not mistaken, you really want to use:


 rma(yi=Mean, vi=Variance/N.1, ...)

 Best,
 Wolfgang

 --
 Wolfgang Viechtbauer, Ph.D., Statistician
 Department of Psychiatry and Psychology
 School for Mental Health and Neuroscience
 Faculty of Health, Medicine, and Life Sciences
 Maastricht University, P.O. Box 616 (VIJV1)
 6200 MD Maastricht, The Netherlands
 +31 (43) 388-4170 | http://www.wvbauer.com

  -Original Message-
  From: 
mailto:r-help-boun...@r-project.orgmailto:r-help-boun...@r-project.orgr-help-boun...@r-project.org 
[mailto:r-help-boun...@r-project.org]

  On Behalf Of Michael Dewey
  Sent: Monday, January 21, 2013 10:40
  To: Alma Wilflinger; Michael Dewey; 
mailto:r-help@r-project.orgmailto:r-help@r-project.orgr-help@r-project.org

  Subject: Re: [R] dummy encoding in metafor
 
  At 14:48 20/01/2013, Alma Wilflinger wrote:
  Hi,
  
  thank you very much for your kind answer.
  
   If you look a bit further down the manual page you will see
   ### using a model formula to specify the same model
   rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
   btt=c(2,3))
  
   which is much easier.
  
  I have seen the possibility of using a model formula for dummy
  encoding and you are right it is much easier than doing it by hand.
  Thing is that if I include some moderator variables into the
  parameters I get the error:
  
  Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve
 
  I suspect that you have a linear dependence between your moderator
  variables. Depending on how many levels there are for country,
  sample, and so on you do have a lot of predictors (you presumably
  know that a factor counts as levels-1 for this purpose?)
 
 
  For example this call works:
  result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
  relevel(factor(Sample), ref=Students) + Gender + Age +
  factor(Category) + relevel(factor(Block), ref=c)+
  relevel(factor(order), ref=x), data=csvDataCmaAll, method=REML)
  
  If I add the trials which is of type INT:
  result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
  relevel(factor(Sample), ref=Students) + Gender + Age +
  factor(Category) + relevel(factor(Block), ref=c)+
  relevel(factor(order), ref=x) + trials, data

Re: [R] dummy encoding in metafor

2013-01-23 Thread Michael Dewey

At 08:30 23/01/2013, Alma Wilflinger wrote:

Dear Wolfgang and Michael,

thank you very much for your help!

Concerning the Variance: I took the variance I used for CMA (which 
is always 1), so I think it should be the right one.


It seems unlikely to me that the variance from each study would be 
the same although I suppose it could be possible. Are you sure you 
are supplying the right values to CMA?




Thank you for noticing and mentioning though :)

I really appreciate how helpful you both are.

best,
Alma



From: Viechtbauer Wolfgang (STAT) 
wolfgang.viechtba...@maastrichtuniversity.nl
To: Michael Dewey i...@aghmed.fsnet.co.uk; Alma Wilflinger 
alma_an...@yahoo.com; r-help@r-project.org r-help@r-project.org

Sent: Monday, January 21, 2013 11:10 AM
Subject: RE: [R] dummy encoding in metafor

As Michael already mentioned, the error:

Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve

indeed indicates that your design matrix is not of full rank (i.e., 
there are linear dependencies among your predictors). With this many 
factors in the same model, this is not surprising if k is only 94 
(which is actually quite large for a meta-analysis). One options is 
to leave out some of the predictors. You can also try collapsing 
some of the levels of the factors. Of course, you lose some 
details that way, but apparently you don't have enough data in the 
first place to carry out such a detailed analysis.


One other thing I noticed. You wrote:

rma(yi=Mean, vi=Variance, ni=N.1, ...)

I suspect that your variable Variance is actually the variance of 
the raw scores. However, the vi argument is used to pass the 
sampling variances of the yi values to the function -- not the 
variance of raw scores. The (estimated) sampling variance of a mean 
is s^2 / n, so if I am not mistaken, you really want to use:


rma(yi=Mean, vi=Variance/N.1, ...)

Best,
Wolfgang

--
Wolfgang Viechtbauer, Ph.D., Statistician
Department of Psychiatry and Psychology
School for Mental Health and Neuroscience
Faculty of Health, Medicine, and Life Sciences
Maastricht University, P.O. Box 616 (VIJV1)
6200 MD Maastricht, The Netherlands
+31 (43) 388-4170 | http://www.wvbauer.com

 -Original Message-
 From: 
mailto:r-help-boun...@r-project.orgr-help-boun...@r-project.org 
[mailto:r-help-boun...@r-project.org]

 On Behalf Of Michael Dewey
 Sent: Monday, January 21, 2013 10:40
 To: Alma Wilflinger; Michael Dewey; 
mailto:r-help@r-project.orgr-help@r-project.org

 Subject: Re: [R] dummy encoding in metafor

 At 14:48 20/01/2013, Alma Wilflinger wrote:
 Hi,
 
 thank you very much for your kind answer.
 
  If you look a bit further down the manual page you will see
  ### using a model formula to specify the same model
  rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
  btt=c(2,3))
 
  which is much easier.
 
 I have seen the possibility of using a model formula for dummy
 encoding and you are right it is much easier than doing it by hand.
 Thing is that if I include some moderator variables into the
 parameters I get the error:
 
 Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve

 I suspect that you have a linear dependence between your moderator
 variables. Depending on how many levels there are for country,
 sample, and so on you do have a lot of predictors (you presumably
 know that a factor counts as levels-1 for this purpose?)


 For example this call works:
 result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
 relevel(factor(Sample), ref=Students) + Gender + Age +
 factor(Category) + relevel(factor(Block), ref=c)+
 relevel(factor(order), ref=x), data=csvDataCmaAll, method=REML)
 
 If I add the trials which is of type INT:
 result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
 relevel(factor(Sample), ref=Students) + Gender + Age +
 factor(Category) + relevel(factor(Block), ref=c)+
 relevel(factor(order), ref=x) + trials, data=csvDataCmaAll,
 method=REML)
 
 I get the error and I was not able to find a definite reason for
 this error or how to solve it I wanted to try it by doing it manually.
 I think I have found out that it somehow relates to the
 
  If you code them yourself R does not know. You know.
 
 Regarding this I think my question was not clear enough. If R does
 the dummy encoding automatically via a model formula it leaves out
 one of the factors and uses it as a baseline automatically. If I do
 it by hand R is still able to execute the function but the baseline
 is missing because I do not define it via a parameter.

 You perhaps would benefit from rereading some of the introductory
 material about formulas. Also look for anything about the model
 matrix (also called the design matrix)

 I simply want to know how R is handling this and what I have to do
 by hand to get the correct results. Sorry, this may be a beginners
 question, but as stated I am new to this field.
 
  You say you have seven moderator variables. Unless you have a shed
  load

Re: [R] dummy encoding in metafor

2013-01-23 Thread Alma Wilflinger
Dear Wolfgang and Michael,

thank you very much for your help!

Concerning the Variance: I took the variance I used for CMA (which is always 
1), so I think it should be the right one.

Thank you for noticing and mentioning though :) 

I really appreciate how helpful you both are.

best,
Alma





 From: Viechtbauer Wolfgang (STAT) 
wolfgang.viechtba...@maastrichtuniversity.nl
To: Michael Dewey i...@aghmed.fsnet.co.uk; Alma Wilflinger 
alma_an...@yahoo.com; r-help@r-project.org r-help@r-project.org 
Sent: Monday, January 21, 2013 11:10 AM
Subject: RE: [R] dummy encoding in metafor

As Michael already mentioned, the error:

Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve

indeed indicates that your design matrix is not of full rank (i.e., there are 
linear dependencies among your predictors). With this many factors in the same 
model, this is not surprising if k is only 94 (which is actually quite large 
for a meta-analysis). One options is to leave out some of the predictors. You 
can also try collapsing some of the levels of the factors. Of course, you lose 
some details that way, but apparently you don't have enough data in the first 
place to carry out such a detailed analysis.

One other thing I noticed. You wrote:

rma(yi=Mean, vi=Variance, ni=N.1, ...)

I suspect that your variable Variance is actually the variance of the raw 
scores. However, the vi argument is used to pass the sampling variances of the 
yi values to the function -- not the variance of raw scores. The (estimated) 
sampling variance of a mean is s^2 / n, so if I am not mistaken, you really 
want to use:

rma(yi=Mean, vi=Variance/N.1, ...)

Best,
Wolfgang

--  
Wolfgang Viechtbauer, Ph.D., Statistician  
Department of Psychiatry and Psychology  
School for Mental Health and Neuroscience  
Faculty of Health, Medicine, and Life Sciences  
Maastricht University, P.O. Box 616 (VIJV1)  
6200 MD Maastricht, The Netherlands  
+31 (43) 388-4170 | http://www.wvbauer.com  

 -Original Message-
 From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
 On Behalf Of Michael Dewey
 Sent: Monday, January 21, 2013 10:40
 To: Alma Wilflinger; Michael Dewey; r-help@r-project.org
 Subject: Re: [R] dummy encoding in metafor
 
 At 14:48 20/01/2013, Alma Wilflinger wrote:
 Hi,
 
 thank you very much for your kind answer.
 
  If you look a bit further down the manual page you will see
  ### using a model formula to specify the same model
  rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
  btt=c(2,3))
 
  which is much easier.
 
 I have seen the possibility of using a model formula for dummy
 encoding and you are right it is much easier than doing it by hand.
 Thing is that if I include some moderator variables into the
 parameters I get the error:
 
 Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve
 
 I suspect that you have a linear dependence between your moderator
 variables. Depending on how many levels there are for country,
 sample, and so on you do have a lot of predictors (you presumably
 know that a factor counts as levels-1 for this purpose?)
 
 
 For example this call works:
 result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
 relevel(factor(Sample), ref=Students) + Gender + Age +
 factor(Category) + relevel(factor(Block), ref=c)+
 relevel(factor(order), ref=x), data=csvDataCmaAll, method=REML)
 
 If I add the trials which is of type INT:
 result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
 relevel(factor(Sample), ref=Students) + Gender + Age +
 factor(Category) + relevel(factor(Block), ref=c)+
 relevel(factor(order), ref=x) + trials, data=csvDataCmaAll,
 method=REML)
 
 I get the error and I was not able to find a definite reason for
 this error or how to solve it I wanted to try it by doing it manually.
 I think I have found out that it somehow relates to the
 
  If you code them yourself R does not know. You know.
 
 Regarding this I think my question was not clear enough. If R does
 the dummy encoding automatically via a model formula it leaves out
 one of the factors and uses it as a baseline automatically. If I do
 it by hand R is still able to execute the function but the baseline
 is missing because I do not define it via a parameter.
 
 You perhaps would benefit from rereading some of the introductory
 material about formulas. Also look for anything about the model
 matrix (also called the design matrix)
 
 I simply want to know how R is handling this and what I have to do
 by hand to get the correct results. Sorry, this may be a beginners
 question, but as stated I am new to this field.
 
  You say you have seven moderator variables. Unless you have a shed
  load of studies you will not be able to look at them simultaneously.
  Apologies if you already knew that.
 
 No I have not known that. In total I have about 94 studies and want
 to test different sets of moderators. Do you think this is
 sufficient

Re: [R] dummy encoding in metafor

2013-01-23 Thread Alma Wilflinger


Hi Michael, 


The supervisorfor my Master'sThesis told me that my means are the effect size 
and cause of this I have to take figure 1 for all standard deviations. So I 
hope that was the right information.




 From: Michael Dewey i...@aghmed.fsnet.co.uk

lfgang.viechtba...@maastrichtuniversity.nl; Michael Dewey 
i...@aghmed.fsnet.co.uk; r-help@r-project.org r-help@r-project.org 
Sent: Wednesday, January 23, 2013 10:22 AM
Subject: Re: [R] dummy encoding in metafor

At 08:30 23/01/2013, Alma Wilflinger wrote:
 Dear Wolfgang and Michael,
 
[[elided Yahoo spam]]
 
 Concerning the Variance: I took the variance I used for CMA (which is always 
 1), so I think it should be the right one.

It seems unlikely to me that the variance from each study would be the same 
although I suppose it could be possible. Are you sure you are supplying the 
right values to CMA?


 Thank you for noticing and mentioning though :)
 
 I really appreciate how helpful you both are.
 
 best,
 Alma
 
 
 
 From: Viechtbauer Wolfgang (STAT) 
 wolfgang.viechtba...@maastrichtuniversity.nl
 To: Michael Dewey i...@aghmed.fsnet.co.uk; Alma Wilflinger 
 alma_an...@yahoo.com; r-help@r-project.org r-help@r-project.org
 Sent: Monday, January 21, 2013 11:10 AM
 Subject: RE: [R] dummy encoding in metafor
 
 As Michael already mentioned, the error:
 
 Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve
 
 indeed indicates that your design matrix is not of full rank (i.e., there are 
 linear dependencies among your predictors). With this many factors in the 
 same model, this is not surprising if k is only 94 (which is actually quite 
 large for a meta-analysis). One options is to leave out some of the 
 predictors. You can also try collapsing some of the levels of the factors. Of 
 course, you lose some details that way, but apparently you don't have 
 enough data in the first place to carry out such a detailed analysis.
 
 One other thing I noticed. You wrote:
 
 rma(yi=Mean, vi=Variance, ni=N.1, ...)
 
 I suspect that your variable Variance is actually the variance of the raw 
 scores. However, the vi argument is used to pass the sampling variances of 
 the yi values to the function -- not the variance of raw scores. The 
 (estimated) sampling variance of a mean is s^2 / n, so if I am not mistaken, 
 you really want to use:
 
 rma(yi=Mean, vi=Variance/N.1, ...)
 
 Best,
 Wolfgang
 
 --
 Wolfgang Viechtbauer, Ph.D., Statistician
 Department of Psychiatry and Psychology
 School for Mental Health and Neuroscience
 Faculty of Health, Medicine, and Life Sciences
 Maastricht University, P.O. Box 616 (VIJV1)
 6200 MD Maastricht, The Netherlands
 +31 (43) 388-4170 | http://www.wvbauer.com
 
  -Original Message-
  From: mailto:r-help-boun...@r-project.orgr-help-boun...@r-project.org 
  [mailto:r-help-boun...@r-project.org]
  On Behalf Of Michael Dewey
  Sent: Monday, January 21, 2013 10:40
  To: Alma Wilflinger; Michael Dewey; 
  mailto:r-help@r-project.orgr-help@r-project.org
  Subject: Re: [R] dummy encoding in metafor
 
  At 14:48 20/01/2013, Alma Wilflinger wrote:
  Hi,
  
  thank you very much for your kind answer.
  
   If you look a bit further down the manual page you will see
   ### using a model formula to specify the same model
   rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
   btt=c(2,3))
  
   which is much easier.
  
  I have seen the possibility of using a model formula for dummy
  encoding and you are right it is much easier than doing it by hand.
  Thing is that if I include some moderator variables into the
  parameters I get the error:
  
  Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve
 
  I suspect that you have a linear dependence between your moderator
  variables. Depending on how many levels there are for country,
  sample, and so on you do have a lot of predictors (you presumably
  know that a factor counts as levels-1 for this purpose?)
 
 
  For example this call works:
  result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
  relevel(factor(Sample), ref=Students) + Gender + Age +
  factor(Category) + relevel(factor(Block), ref=c)+
  relevel(factor(order), ref=x), data=csvDataCmaAll, method=REML)
  
  If I add the trials which is of type INT:
  result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
  relevel(factor(Sample), ref=Students) + Gender + Age +
  factor(Category) + relevel(factor(Block), ref=c)+
  relevel(factor(order), ref=x) + trials, data=csvDataCmaAll,
  method=REML)
  
  I get the error and I was not able to find a definite reason for
  this error or how to solve it I wanted to try it by doing it manually.
  I think I have found out that it somehow relates to the
  
   If you code them yourself R does not know. You know.
  
  Regarding this I think my question was not clear enough. If R does
  the dummy encoding automatically via a model formula it leaves out
  one of the factors and uses

Re: [R] dummy encoding in metafor

2013-01-21 Thread Michael Dewey

At 14:48 20/01/2013, Alma Wilflinger wrote:

Hi,

thank you very much for your kind answer.

If you look a bit further down the manual page you will see
### using a model formula to specify the same model
rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
btt=c(2,3))

which is much easier.

I have seen the possibility of using a model formula for dummy 
encoding and you are right it is much easier than doing it by hand.
Thing is that if I include some moderator variables into the 
parameters I get the error:


Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve


I suspect that you have a linear dependence between your moderator 
variables. Depending on how many levels there are for country, 
sample, and so on you do have a lot of predictors (you presumably 
know that a factor counts as levels-1 for this purpose?)




For example this call works:
result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) + 
relevel(factor(Sample), ref=Students) + Gender + Age + 
factor(Category) + relevel(factor(Block), ref=c)+ 
relevel(factor(order), ref=x), data=csvDataCmaAll, method=REML)


If I add the trials which is of type INT:
result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) + 
relevel(factor(Sample), ref=Students) + Gender + Age + 
factor(Category) + relevel(factor(Block), ref=c)+ 
relevel(factor(order), ref=x) + trials, data=csvDataCmaAll, method=REML)


I get the error and I was not able to find a definite reason for 
this error or how to solve it I wanted to try it by doing it manually.

I think I have found out that it somehow relates to the

If you code them yourself R does not know. You know.

Regarding this I think my question was not clear enough. If R does 
the dummy encoding automatically via a model formula it leaves out 
one of the factors and uses it as a baseline automatically. If I do 
it by hand R is still able to execute the function but the baseline 
is missing because I do not define it via a parameter.


You perhaps would benefit from rereading some of the introductory 
material about formulas. Also look for anything about the model 
matrix (also called the design matrix)


I simply want to know how R is handling this and what I have to do 
by hand to get the correct results. Sorry, this may be a beginners 
question, but as stated I am new to this field.


You say you have seven moderator variables. Unless you have a shed
load of studies you will not be able to look at them simultaneously.
Apologies if you already knew that.

No I have not known that. In total I have about 94 studies and want 
to test different sets of moderators. Do you think this is 
sufficient or do you suggest another approach?


The truthful but perhaps unhelpful answer is that you need to collect 
more data or use fewer moderators.


I started in CMA (comprehensive meta analysis) but one of the 
benefits of R is that I am able to test multiple moderators at once 
- at least as I was told.


kind regards,
Alma


From: Michael Dewey i...@aghmed.fsnet.co.uk
To: Alma Wilflinger alma_an...@yahoo.com; r-help@r-project.org 
r-help@r-project.org

Sent: Sunday, January 20, 2013 12:52 PM
Subject: Re: [R] dummy encoding in metafor

At 17:14 19/01/2013, Alma Wilflinger wrote:
Hi,

I am quite new to R and in need of some advice. I am trying to
conduct a meta regression over a some studies with about 7 mod
variables which I have to dummy encode.

Alma, although you can generate your own dummy variables by hand you
do not have to as R will do it for you. See below for more comments.


I have found the following piece of code in the manual for the
metafor library:

### manual dummy coding of the allocation factor
alloc.random - ifelse(dat$alloc == random, 1, 0)
alloc.alternate - ifelse(dat$alloc == alternate, 1, 0)
alloc.systematic - ifelse(dat$alloc == systematic, 1, 0)

If you look a bit further down the manual page you will see
### using a model formula to specify the same model
rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
btt=c(2,3))

which is much easier.

### test the allocation factor (in the presence of the other moderators)
### note: alternate is the reference level of the allocation factor
### note: the intercept is the first coefficient, so btt=c(2,3)
rma(yi, vi, mods=cbind(alloc.random, alloc.systematic, year, ablat),
data=dat, method=REML, btt=c(2,3))

What I do not understand is the following:
How does R know which columns in my data.frame are related to the
dummy encoded variables?

If you code them yourself R does not know. You know.


It is clear that in the call of cbind I just do not use the
reference variable as a parameter but I do not get it how R knows
that alloc.random and alloc.systematic refer to the column alloc in
the data frame.

Thank you very much in advance for your help,


You say you have seven moderator variables. Unless you have a shed
load of studies you will not be able to look at them simultaneously.
Apologies if you already

Re: [R] dummy encoding in metafor

2013-01-21 Thread Viechtbauer Wolfgang (STAT)
As Michael already mentioned, the error:

Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve

indeed indicates that your design matrix is not of full rank (i.e., there are 
linear dependencies among your predictors). With this many factors in the same 
model, this is not surprising if k is only 94 (which is actually quite large 
for a meta-analysis). One options is to leave out some of the predictors. You 
can also try collapsing some of the levels of the factors. Of course, you lose 
some details that way, but apparently you don't have enough data in the first 
place to carry out such a detailed analysis.

One other thing I noticed. You wrote:

rma(yi=Mean, vi=Variance, ni=N.1, ...)

I suspect that your variable Variance is actually the variance of the raw 
scores. However, the vi argument is used to pass the sampling variances of the 
yi values to the function -- not the variance of raw scores. The (estimated) 
sampling variance of a mean is s^2 / n, so if I am not mistaken, you really 
want to use:

rma(yi=Mean, vi=Variance/N.1, ...)

Best,
Wolfgang

--   
Wolfgang Viechtbauer, Ph.D., Statistician   
Department of Psychiatry and Psychology   
School for Mental Health and Neuroscience   
Faculty of Health, Medicine, and Life Sciences   
Maastricht University, P.O. Box 616 (VIJV1)   
6200 MD Maastricht, The Netherlands   
+31 (43) 388-4170 | http://www.wvbauer.com   

 -Original Message-
 From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
 On Behalf Of Michael Dewey
 Sent: Monday, January 21, 2013 10:40
 To: Alma Wilflinger; Michael Dewey; r-help@r-project.org
 Subject: Re: [R] dummy encoding in metafor
 
 At 14:48 20/01/2013, Alma Wilflinger wrote:
 Hi,
 
 thank you very much for your kind answer.
 
  If you look a bit further down the manual page you will see
  ### using a model formula to specify the same model
  rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
  btt=c(2,3))
 
  which is much easier.
 
 I have seen the possibility of using a model formula for dummy
 encoding and you are right it is much easier than doing it by hand.
 Thing is that if I include some moderator variables into the
 parameters I get the error:
 
 Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve
 
 I suspect that you have a linear dependence between your moderator
 variables. Depending on how many levels there are for country,
 sample, and so on you do have a lot of predictors (you presumably
 know that a factor counts as levels-1 for this purpose?)
 
 
 For example this call works:
 result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
 relevel(factor(Sample), ref=Students) + Gender + Age +
 factor(Category) + relevel(factor(Block), ref=c)+
 relevel(factor(order), ref=x), data=csvDataCmaAll, method=REML)
 
 If I add the trials which is of type INT:
 result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) +
 relevel(factor(Sample), ref=Students) + Gender + Age +
 factor(Category) + relevel(factor(Block), ref=c)+
 relevel(factor(order), ref=x) + trials, data=csvDataCmaAll,
 method=REML)
 
 I get the error and I was not able to find a definite reason for
 this error or how to solve it I wanted to try it by doing it manually.
 I think I have found out that it somehow relates to the
 
  If you code them yourself R does not know. You know.
 
 Regarding this I think my question was not clear enough. If R does
 the dummy encoding automatically via a model formula it leaves out
 one of the factors and uses it as a baseline automatically. If I do
 it by hand R is still able to execute the function but the baseline
 is missing because I do not define it via a parameter.
 
 You perhaps would benefit from rereading some of the introductory
 material about formulas. Also look for anything about the model
 matrix (also called the design matrix)
 
 I simply want to know how R is handling this and what I have to do
 by hand to get the correct results. Sorry, this may be a beginners
 question, but as stated I am new to this field.
 
  You say you have seven moderator variables. Unless you have a shed
  load of studies you will not be able to look at them simultaneously.
  Apologies if you already knew that.
 
 No I have not known that. In total I have about 94 studies and want
 to test different sets of moderators. Do you think this is
 sufficient or do you suggest another approach?
 
 The truthful but perhaps unhelpful answer is that you need to collect
 more data or use fewer moderators.
 
 I started in CMA (comprehensive meta analysis) but one of the
 benefits of R is that I am able to test multiple moderators at once
 - at least as I was told.
 
 kind regards,
 Alma
 
 
 From: Michael Dewey i...@aghmed.fsnet.co.uk
 To: Alma Wilflinger alma_an...@yahoo.com; r-help@r-project.org
 r-help@r-project.org
 Sent: Sunday, January 20, 2013 12:52 PM
 Subject: Re: [R] dummy encoding in metafor
 
 At 17:14 19/01/2013, Alma Wilflinger wrote:
  Hi,
  
  I am

Re: [R] dummy encoding in metafor

2013-01-20 Thread Michael Dewey

At 17:14 19/01/2013, Alma Wilflinger wrote:

Hi,

I am quite new to R and in need of some advice. I am trying to 
conduct a meta regression over a some studies with about 7 mod 
variables which I have to dummy encode.


Alma, although you can generate your own dummy variables by hand you 
do not have to as R will do it for you. See below for more comments.



I have found the following piece of code in the manual for the 
metafor library:


### manual dummy coding of the allocation factor
alloc.random - ifelse(dat$alloc == random, 1, 0)
alloc.alternate - ifelse(dat$alloc == alternate, 1, 0)
alloc.systematic - ifelse(dat$alloc == systematic, 1, 0)


If you look a bit further down the manual page you will see
### using a model formula to specify the same model
rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML, 
btt=c(2,3))


which is much easier.


### test the allocation factor (in the presence of the other moderators)
### note: alternate is the reference level of the allocation factor
### note: the intercept is the first coefficient, so btt=c(2,3)
rma(yi, vi, mods=cbind(alloc.random, alloc.systematic, year, ablat), 
data=dat, method=REML, btt=c(2,3))


What I do not understand is the following:
How does R know which columns in my data.frame are related to the 
dummy encoded variables?


If you code them yourself R does not know. You know.


It is clear that in the call of cbind I just do not use the 
reference variable as a parameter but I do not get it how R knows 
that alloc.random and alloc.systematic refer to the column alloc in 
the data frame.


Thank you very much in advance for your help,



You say you have seven moderator variables. Unless you have a shed 
load of studies you will not be able to look at them simultaneously. 
Apologies if you already knew that.



kind regards,
Alma
[[alternative HTML version deleted]]


Michael Dewey
i...@aghmed.fsnet.co.uk
http://www.aghmed.fsnet.co.uk/home.html

__
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] dummy encoding in metafor

2013-01-20 Thread Alma Wilflinger
Hi, 

thank you very much for your kind answer.

If you look a bit further down the manual page you will see
### using a model formula to specify the same model
rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML, 
btt=c(2,3))


which is much easier.


I have seen the possibility of using a model formula for dummy encoding and you 
are right it is much easier than doing it by hand.
Thing is that if I include some moderator variables into the parameters I get 
the error:

Error in qr.solve(wX, diag(k)) : singular matrix 'a' in solve

For example this call works:
result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) + 
relevel(factor(Sample), ref=Students) + Gender + Age + factor(Category) + 
relevel(factor(Block), ref=c)+ relevel(factor(order), ref=x), 
data=csvDataCmaAll, method=REML)


If I add the trials which is of type INT:
result = rma(yi=Mean, vi=Variance, ni=N.1, mods=~factor(Country) + 
relevel(factor(Sample), ref=Students) + Gender + Age + factor(Category) + 
relevel(factor(Block), ref=c)+ relevel(factor(order), ref=x) + trials, 
data=csvDataCmaAll, method=REML)

I get the error and I was not able to find a definite reason for this error or 
how to solve it I wanted to try it by doing it manually. 
I think I have found out that it somehow relates to the 

If you code them yourself R does not know. You know.

Regarding this I think my question was not clear enough. If R does the dummy 
encoding automatically via a model formula it leaves out one of the factors and 
uses it as a baseline automatically. If I do it by hand R is still able to 
execute the function but the baseline is missing because I do not define it via 
a parameter.
I simply want to know how R is handling this and what I have to do by hand to 
get the correct results. Sorry, this may be a beginners question, but as stated 
I am new to this field.

You say you have seven moderator variables. Unless you have a shed 

load of studies you will not be able to look at them simultaneously. 
Apologies if you already knew that.


No I have not known that. In total I have about 94 studies and want to test 
different sets of moderators. Do you think this is sufficient or do you suggest 
another approach?
I started in CMA (comprehensive meta analysis) but one of the benefits of R is 
that I am able to test multiple moderators at once - at least as I was told.

kind regards,
Alma



 From: Michael Dewey i...@aghmed.fsnet.co.uk

r-project.org 
Sent: Sunday, January 20, 2013 12:52 PM
Subject: Re: [R] dummy encoding in metafor

At 17:14 19/01/2013, Alma Wilflinger wrote:
Hi,

I am quite new to R and in need of some advice. I am trying to 
conduct a meta regression over a some studies with about 7 mod 
variables which I have to dummy encode.

Alma, although you can generate your own dummy variables by hand you 
do not have to as R will do it for you. See below for more comments.


I have found the following piece of code in the manual for the 
metafor library:

### manual dummy coding of the allocation factor
alloc.random - ifelse(dat$alloc == random, 1, 0)
alloc.alternate - ifelse(dat$alloc == alternate, 1, 0)
alloc.systematic - ifelse(dat$alloc == systematic, 1, 0)

If you look a bit further down the manual page you will see
### using a model formula to specify the same model
rma(yi, vi, mods=~factor(alloc)+year+ablat, data=dat, method=REML,
btt=c(2,3))

which is much easier.

### test the allocation factor (in the presence of the other moderators)
### note: alternate is the reference level of the allocation factor
### note: the intercept is the first coefficient, so btt=c(2,3)
rma(yi, vi, mods=cbind(alloc.random, alloc.systematic, year, ablat), 
data=dat, method=REML, btt=c(2,3))

What I do not understand is the following:
How does R know which columns in my data.frame are related to the 
dummy encoded variables?

If you code them yourself R does not know. You know.


It is clear that in the call of cbind I just do not use the 
reference variable as a parameter but I do not get it how R knows 
that alloc.random and alloc.systematic refer to the column alloc in 
the data frame.

Thank you very much in advance for your help,


You say you have seven moderator variables. Unless you have a shed 
load of studies you will not be able to look at them simultaneously. 
Apologies if you already knew that.

kind regards,
Alma
         [[alternative HTML version deleted]]

Michael Dewey
i...@aghmed.fsnet.co.uk
http://www.aghmed.fsnet.co.uk/home.html
[[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] dummy encoding in metafor

2013-01-19 Thread Alma Wilflinger
Hi,

I am quite new to R and in need of some advice. I am trying to conduct a meta 
regression over a some studies with about 7 mod variables which I have to dummy 
encode.

I have found the following piece of code in the manual for the metafor library:

### manual dummy coding of the allocation factor
alloc.random - ifelse(dat$alloc == random, 1, 0)
alloc.alternate - ifelse(dat$alloc == alternate, 1, 0)
alloc.systematic - ifelse(dat$alloc == systematic, 1, 0)

### test the allocation factor (in the presence of the other moderators)
### note: alternate is the reference level of the allocation factor
### note: the intercept is the first coefficient, so btt=c(2,3)
rma(yi, vi, mods=cbind(alloc.random, alloc.systematic, year, ablat), data=dat, 
method=REML, btt=c(2,3))

What I do not understand is the following: 
How does R know which columns in my data.frame are related to the dummy encoded 
variables?

It is clear that in the call of cbind I just do not use the reference variable 
as a parameter but I do not get it how R knows that alloc.random and 
alloc.systematic refer to the column alloc in the data frame.

Thank you very much in advance for your help,


kind regards, 
Alma
[[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.