[R] bootstrapping nlme fits (was boot function)
(see archives for former discussion) I probably didnt express myself very well in the last mail i wrote. The dataset contains the variables subject, day, concentration(measured). I would like to bootstrap the variable subject. Now it is true that the subjects wont be independent in the bootstrap samples but i still wanna conduct the bootstrapping just for the sake of comparison with other results i got. Well, i succeeded to set up the program needed for bootstrapping. However, i get the error message: Error: Unable to form Cholesky decomposition or that convergence was not reached with the maximal interations. What exactly does that mean? Is there possibly any connection to the fact that the subjects are not independent? Thanks a lot for answers Dassy __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
Re: [R] bootstrapping nlme fits (was boot function)
First, this has very little to do with boot: PLEASE use an infromative
subject line. You need to work out how to resample in this situation: are
you resampling subjects or observations? If you are resampling subjects,
you need to create a data frame containing just the resampled subjects and
pass that to nlme.
However, you also need to think if this is valid. If you resample
subjects, you will be fitting subjects twice or more as if they are
independent. I know of no theoretical studies on resampling mixed-effects
models, and urge you to look for such results.
On Fri, 22 Aug 2003, Brunschwig, Hadassa {PDMM~Basel} wrote:
I skimmed through the archives and couldnt really find an answer to my
question.
It's not an R question.
One thing i dont understand of the description of the function
boot() is the second variable for statistics. I have a sample of say 19
subjects out of these, using boot(), i would like to generate say 1000
samples. For these 1000 samples ill calculate an nlme() and ill use
these 1000 estimators of a variable to make further calculation.
Whether this is valid most likely depends on what those calculations are.
Now
what i dont understand is where the index should be set. the nlme()
looks like this:
nlme(Concentr~a*(1-exp(Day*(log(0.1,base=exp(1))/exp(logt09
,data=data
,fixed=a+logt09~1
,random=a+logt09~1|Subject[ind]
,start=list(fixed=c(a=30,logt09=1)))
My idea was to put the index ( second variable of the statistcs
function)
What that variable means depends on the other arguments to boot, and you
haven't told us what those are.
in the subject as i want to generate different samples of
subjects. I get the error that the vector ind was not found. I would be
happy for any help concerning this problem.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
__
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Re: [R] bootstrapping nlme fits (was boot function)
On Fri, 22 Aug 2003 14:39:28 +0100 (BST)
Prof Brian Ripley [EMAIL PROTECTED] wrote:
First, this has very little to do with boot: PLEASE use an infromative
subject line. You need to work out how to resample in this situation: are
you resampling subjects or observations? If you are resampling subjects,
you need to create a data frame containing just the resampled subjects and
pass that to nlme.
However, you also need to think if this is valid. If you resample
subjects, you will be fitting subjects twice or more as if they are
independent. I know of no theoretical studies on resampling mixed-effects
models, and urge you to look for such results.
On Fri, 22 Aug 2003, Brunschwig, Hadassa {PDMM~Basel} wrote:
Hadassa - You may want to look at the slightly simpler generalized least squares with
correlated observations case. For that I have a bootstrap option in the Design
packages's glsD function (which uses the nlme package). There is an option to treat
multiply-sampled subjects as if they were different subjects, or to pool them into one
larger subject (I think the former is more correct but I haven't gotten very far in
this thinking). You can do simulations with glsD to check the performance of the
cluster-sampling bootstrap in this situation. I have done limited simulations and
bootstrap variance estimates seem to be close to actual values, although not as close
as information-matrix-based estimates when the model is true. glsD attempts to
implement the cluster bootstrap fairly efficiently, although it does not yet work for
the case where an across-time covariance pattern is not assumed.
Frank Harrell
I skimmed through the archives and couldnt really find an answer to my
question.
It's not an R question.
One thing i dont understand of the description of the function
boot() is the second variable for statistics. I have a sample of say 19
subjects out of these, using boot(), i would like to generate say 1000
samples. For these 1000 samples ill calculate an nlme() and ill use
these 1000 estimators of a variable to make further calculation.
Whether this is valid most likely depends on what those calculations are.
Now
what i dont understand is where the index should be set. the nlme()
looks like this:
nlme(Concentr~a*(1-exp(Day*(log(0.1,base=exp(1))/exp(logt09
,data=data
,fixed=a+logt09~1
,random=a+logt09~1|Subject[ind]
,start=list(fixed=c(a=30,logt09=1)))
My idea was to put the index ( second variable of the statistcs
function)
What that variable means depends on the other arguments to boot, and you
haven't told us what those are.
in the subject as i want to generate different samples of
subjects. I get the error that the vector ind was not found. I would be
happy for any help concerning this problem.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
---
Frank E Harrell Jr Prof. of Biostatistics Statistics
Div. of Biostatistics Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
__
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Re: [R] bootstrapping nlme fits (was boot function)
On 22 Aug 2003 at 10:18, Frank E Harrell Jr wrote:
The following danish web page
http://www.dina.dk/phd/s/s2/s2pr1.htm
gives an example of bootstrapping nlme models. If what they are doing
is vali, I don't know, I abstained from it since I do not understand
it.
Kjetil Halvorsen
On Fri, 22 Aug 2003 14:39:28 +0100 (BST)
Prof Brian Ripley [EMAIL PROTECTED] wrote:
First, this has very little to do with boot: PLEASE use an infromative
subject line. You need to work out how to resample in this situation: are
you resampling subjects or observations? If you are resampling subjects,
you need to create a data frame containing just the resampled subjects and
pass that to nlme.
However, you also need to think if this is valid. If you resample
subjects, you will be fitting subjects twice or more as if they are
independent. I know of no theoretical studies on resampling mixed-effects
models, and urge you to look for such results.
On Fri, 22 Aug 2003, Brunschwig, Hadassa {PDMM~Basel} wrote:
Hadassa - You may want to look at the slightly simpler generalized least squares
with correlated observations case. For that I have a bootstrap option in the Design
packages's glsD function (which uses the nlme package). There is an option to treat
multiply-sampled subjects as if they were
different subjects, or to pool them into one larger subject (I think the former is
more correct but I haven't gotten very far in this thinking). You can do simulations
with glsD to check the performance of the cluster-sampling bootstrap in this
situation. I have done limited simulations and
bootstrap variance estimates seem to be close to actual values, although not as close
as information-matrix-based estimates when the model is true. glsD attempts to
implement the cluster bootstrap fairly efficiently, although it does not yet work for
the case where an across-time covariance
pattern is not assumed.
Frank Harrell
I skimmed through the archives and couldnt really find an answer to my
question.
It's not an R question.
One thing i dont understand of the description of the function
boot() is the second variable for statistics. I have a sample of say 19
subjects out of these, using boot(), i would like to generate say 1000
samples. For these 1000 samples ill calculate an nlme() and ill use
these 1000 estimators of a variable to make further calculation.
Whether this is valid most likely depends on what those calculations are.
Now
what i dont understand is where the index should be set. the nlme()
looks like this:
nlme(Concentr~a*(1-exp(Day*(log(0.1,base=exp(1))/exp(logt09
,data=data
,fixed=a+logt09~1
,random=a+logt09~1|Subject[ind]
,start=list(fixed=c(a=30,logt09=1)))
My idea was to put the index ( second variable of the statistcs
function)
What that variable means depends on the other arguments to boot, and you
haven't told us what those are.
in the subject as i want to generate different samples of
subjects. I get the error that the vector ind was not found. I would be
happy for any help concerning this problem.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
---
Frank E Harrell Jr Prof. of Biostatistics Statistics
Div. of Biostatistics Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
__
[EMAIL PROTECTED] mailing list
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__
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Re: [R] bootstrapping nlme fits (was boot function)
On Fri, 22 Aug 2003 12:36:28 -0400
kjetil brinchmann halvorsen [EMAIL PROTECTED] wrote:
On 22 Aug 2003 at 10:18, Frank E Harrell Jr wrote:
The following danish web page
http://www.dina.dk/phd/s/s2/s2pr1.htm
gives an example of bootstrapping nlme models. If what they are doing
is vali, I don't know, I abstained from it since I do not understand
it.
Kjetil Halvorsen
Thanks. I use the unconditional bootstrap which does not assume a correlation
structure and does not use residuals.
Frank
On Fri, 22 Aug 2003 14:39:28 +0100 (BST)
Prof Brian Ripley [EMAIL PROTECTED] wrote:
First, this has very little to do with boot: PLEASE use an infromative
subject line. You need to work out how to resample in this situation: are
you resampling subjects or observations? If you are resampling subjects,
you need to create a data frame containing just the resampled subjects and
pass that to nlme.
However, you also need to think if this is valid. If you resample
subjects, you will be fitting subjects twice or more as if they are
independent. I know of no theoretical studies on resampling mixed-effects
models, and urge you to look for such results.
On Fri, 22 Aug 2003, Brunschwig, Hadassa {PDMM~Basel} wrote:
Hadassa - You may want to look at the slightly simpler generalized least squares
with correlated observations case. For that I have a bootstrap option in the
Design packages's glsD function (which uses the nlme package). There is an option
to treat multiply-sampled subjects as if they were
different subjects, or to pool them into one larger subject (I think the former is
more correct but I haven't gotten very far in this thinking). You can do
simulations with glsD to check the performance of the cluster-sampling bootstrap in
this situation. I have done limited simulations and
bootstrap variance estimates seem to be close to actual values, although not as
close as information-matrix-based estimates when the model is true. glsD attempts
to implement the cluster bootstrap fairly efficiently, although it does not yet work
for the case where an across-time covariance
pattern is not assumed.
Frank Harrell
I skimmed through the archives and couldnt really find an answer to my
question.
It's not an R question.
One thing i dont understand of the description of the function
boot() is the second variable for statistics. I have a sample of say 19
subjects out of these, using boot(), i would like to generate say 1000
samples. For these 1000 samples ill calculate an nlme() and ill use
these 1000 estimators of a variable to make further calculation.
Whether this is valid most likely depends on what those calculations are.
Now
what i dont understand is where the index should be set. the nlme()
looks like this:
nlme(Concentr~a*(1-exp(Day*(log(0.1,base=exp(1))/exp(logt09
,data=data
,fixed=a+logt09~1
,random=a+logt09~1|Subject[ind]
,start=list(fixed=c(a=30,logt09=1)))
My idea was to put the index ( second variable of the statistcs
function)
What that variable means depends on the other arguments to boot, and you
haven't told us what those are.
in the subject as i want to generate different samples of
subjects. I get the error that the vector ind was not found. I would be
happy for any help concerning this problem.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
---
Frank E Harrell Jr Prof. of Biostatistics Statistics
Div. of Biostatistics Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
__
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
---
Frank E Harrell Jr Prof. of Biostatistics Statistics
Div. of Biostatistics Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
__
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