[R] crr - computationally singular

[Laura Bonnett]

Dear Sir,

Thank you for your response.  You were correct, I had 1 linearly
dependent column.  I have solved this problem and now the rank of
'covaeb' is 17 (qr(covaeb)$rank = 17).  However, I still get the same
error message when I use covaeb in the 'crr' function.

> fit=crr(snearmb$with.Withtime,csaeb,covaeb,failcode=2,cencode=0)
8 cases omitted due to missing values
Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) :
  system is computationally singular: reciprocal condition number = 3.45905e-25

Are there any other reasons why this may be happening?

Thank you,

Laura

2009/6/25 Ravi Varadhan <RVaradhan at jhmi.edu>:
> This means that your design matrix or model matrix is rank deficient, i.e it
> does not have linearly independent columns.  Your predictors are collinear!
>
>
> Just take your design matrices "covaea" or "covaeb" with 17 predcitors and
> compute their rank or try to invert them.  You will see the problem.
>
> Ravi.
>
> ----------------------------------------------------------------------------
> -------
>
> Ravi Varadhan, Ph.D.
>
> Assistant Professor, The Center on Aging and Health
>
> Division of Geriatric Medicine and Gerontology
>
> Johns Hopkins University
>
> Ph: (410) 502-2619
>
> Fax: (410) 614-9625
>
> Email: rvaradhan at jhmi.edu
>
> Webpage:
> http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.h
> tml
>
>
>
> ----------------------------------------------------------------------------
> --------
>
>
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> Behalf Of Laura Bonnett
> Sent: Thursday, June 25, 2009 11:39 AM
> To: r-help at r-project.org
> Subject: [R] crr - computationally singular
>
> Dear R-help,
>
> I'm very sorry to ask 2 questions in a week.  I am using the package 'crr'
> and it does exactly what I need it to when I use the dataset a.
> However, when I use dataset b I get the following error message:
> Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) :
>  system is computationally singular: reciprocal condition number =
> 1.28654e-24
>
> This is obviously as a result of a problem with the data but apart from
> dataset a having 1674 rows and dataset b having 701 rows there is really no
> difference between them.
>
> The code I am using is as follows where covaea and covaeb are matrices of
> covarites, all coded as binary variables.
> In case a:
>> covaea <-
>> cbind(sexa,fsha,fdra,nsigna,eega,th1a,th2a,stype1a,stype2a,stype3a,pgu
>> 1a,pgu2a,log(agea),firstinta/1000,totsezbasea)
>> fita <- crr(snearma$with.Withtime,csaea,covaea,failcode=2,cencode=0)
>
> and in case b:
>> covaeb <-
>> cbind(sexb,fshb,fdrb,nsignb,eegb,th1b,th2b,stype1b,stype2b,stype3b,sty
>> pe4b,stype5b,pgu1b,pgu2b,(ageb/10)^(-1),firstintb,log(totsezbaseb))
>> fitb <- crr(snearmb$with.Withtime,csaeb,covaeb,failcode=2,cencode=0)
>
> csaea and csaeb are the censoring indicators for a and b respectively which
> equal 1 for the event of interest, 2 for the competing risks event and 0
> otherwise.
>
> Can anyone suggest a reason for the error message?  I've tried running fitb
> with variants of covaeb and irrespective of the order of the covariates in
> the matrix, the code runs fine with 16 of the 17 covariates included but
> then produces an error message when the 17th is added.
>
> Thank you for your help,
>
> Laura
>
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