On Fri, 18 Dec 2009, Hien Nguyen wrote:

Dear Drs Winsemius and Berry,

Thanks a lot for your comment and suggestions on running my model. I am not just new to R but new to CLM as well. :( With your suggestions, I figure out that I have huge misunderstandings on the model and data arrangement.

After my finals, I have read again related materials on CLM and rearranged in an appropriate way before running the model in R. This time, I have a data of more than 250,000 observations (created from more than 4000 response) and a model of 15 predictors.

My question is that how long should it takes for the clogit command to run because it has been running for more 10 hours on a quad-core computer and still doesn't show any sign of done or almost done. Is it OK or my command just does not work.

If you have a lot of records with case=1 in a stratum, conditional logistic 
regression will be extremely slow.   And unnecessary: maximizing the 
unconditional likelihood is fine when the stratum sizes are large.

Note that a quad-core computer won't help. Only one core will be used in the 
computations.

     -thomas




Thanks a lot for your response

Hien


Charles C. Berry wrote:
On Fri, 4 Dec 2009, David Winsemius wrote:


On Dec 4, 2009, at 5:49 PM, Hien Nguyen wrote:

Dear Dr. Winsemius,

Thank you very much for your reply.

I have tried many possible combinations (even with the model of only 2 predictors) but it produces the same message. With more than 4000 observations, I think 14 predictors might not be too many.

It is what happens in the factor combinations that concern me. I am guessing that some of those predictors are factors. You really should not ask r-help questions without providing better descriptions of both the outcomes and the predictor variables.


Although my dependent variable (Pin) is not discrete (it ranges from 0 to 1), I do not think it will create problems to the estimation but I'm not sure

I would think it _would_ cause problems. As I understand it, conditional methods create contingency tables. Why are you using an outcome type that is not consistent with the fundamental regression assumptions of the clogit function?

I do not get that particular error when I munge the infert dataset to have case be a random uniform value, but I do get an error.
 infert$case <- runif(nrow(infert))
 clogit(case~spontaneous+induced+strata(stratum),data=infert)
Error in Surv(rep(1, 248L), case) : Invalid status value


David, I think you were on the right track. I get this:

-----------
clogit(I(case*runif(length(case)))~spontaneous+induced+strata(ifelse(stratum>40,NA,stratum)),data=infert)
Error in fitter(X, Y, strats, offset, init, control, weights = weights,  :
  NA/NaN/Inf in foreign function call (arg 6)
In addition: Warning messages:
1: In Surv(rep(1, 248L), I(case * runif(length(case)))) :
  Invalid status value, converted to NA
2: In fitter(X, Y, strats, offset, init, control, weights = weights,  :
  Ran out of iterations and did not converge

------------

which looks pretty much the same as Hien's error msg

So Hien needs to create a logical status value.

Chuck

p.s.

sessionInfo()
R version 2.10.0 (2009-10-26)
i386-pc-mingw32

locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

attached base packages:
[1] splines   stats     graphics  grDevices utils     datasets  methods
[8] base

other attached packages:
[1] survival_2.35-7

loaded via a namespace (and not attached):
[1] tools_2.10.0



So I certainly would not have proceeded to submit a full analysis to clogit if I could not get a test case to run under the situation you propose.

--
David


I have checked the collinearity among predictors and they are all < 0.5 (which I think is OK). Do you know what else could make this errors?

Thanks a lot

Hien Nguyen

David Winsemius wrote:
> > On Dec 4, 2009, at 9:22 AM, Hien Nguyen wrote:
> > > Dear R-helpers,
> > > > I am very new to R and trying to run the conditional logit model using
> > "clogit " command.
> > I have more than 4000 observations in my dataset and try to predict the > > dependent variable from 14 independent variables. My command is as > > follows
> > > > clmtest1 <-
> > clogit(Pin~Income+Bus+Pop+Urbpro+Health+Student+Grad+NE+NW+NCC+SCC+CH+SE+MRD+strata(IDD),data=clmdata) > > > > > > However, it produces the following errors: > > > > Error in fitter(X, Y, strats, offset, init, control, weights = weights, > > :
> > NA/NaN/Inf in foreign function call (arg 6)
> > In addition: Warning messages:
> > 1: In Surv(rep(1, 4096L), Pinmig) : Invalid status value, converted to > > NA > > 2: In fitter(X, Y, strats, offset, init, control, weights = weights, :
> > Ran out of iterations and did not converge
> > > > I search the error message from R forums but it does not say anything
> > for Conditional Logit Model.
> > With that many predictors in a small dataset, you may have created matrix > singularities. Perhaps you created a stratum where all of the subjects > experience the event and others where none did so. The coefficients might > be driven to infinities. Try simplifying the model. > > > > > > Please check for me what it says and what should I do to solve it. > >

David Winsemius, MD
Heritage Laboratories
West Hartford, CT

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Charles C. Berry                            (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:cbe...@tajo.ucsd.edu                UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901



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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.


Thomas Lumley                   Assoc. Professor, Biostatistics
tlum...@u.washington.edu        University of Washington, Seattle

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