[R] Re : aregImpute (Hmisc package) : error in matxv(X, xcof)...
dwinsemius at comcast.net
Tue May 4 20:28:53 CEST 2010
On May 4, 2010, at 2:13 PM, Marc Carpentier wrote:
> Ok. I was afraid to refer to a known and obvious error.
> Here is a testing dataset (pb1.csv) and commented code (pb1.R) with
> the problems.
> Thanks for any help.
Nothing attached. In all likelihood had you given these file names
with extensions of .txt, they would have made it through the server
> De : Uwe Ligges <ligges at statistik.tu-dortmund.de>
> À : Marc Carpentier <marc.carpentier at ymail.com>
> Cc : r-help at r-project.org
> Envoyé le : Mar 4 mai 2010, 13 h 52 min 31 s
> Objet : Re: [R] aregImpute (Hmisc package) : error in matxv(X,
> Having reproducible examples including data and the actual call that
> lead to the error would be really helpful to be able to help.
> Uwe Ligges
> On 04.05.2010 12:23, Marc Carpentier wrote:
>> Dear r-help list,
>> I'm trying to use multiple imputation for my MSc thesis.
>> Having good exemples using the Hmisc package, I tried the
>> aregImpute function. But with my own dataset, I have the following
>> error :
>> Erreur dans matxv(X, xcof) : columns in a (51) must be<= length of
>> b (50)
>> De plus : Warning message:
>> In f$xcoef[, 1] * f$xcenter :
>> la taille d'un objet plus long n'est pas multiple de la taille
>> d'un objet plus court
>> = longer object length is not a multiple of shorter object length
>> I first tried to "I()" all the continuous variables but the same
>> error occurs with different numbers :
>> Erreur dans matxv(X, xcof) : columns in a (37) must be<= length of
>> b (36)...
>> I'm a student and I'm not familiar with possible constraints in a
>> dataset to be effectively imputed. I just found this previous
>> message, where the author's autoreply suggests that particular
>> distributions might be an explanation of algorithms failure :
>> Does anyone know if these messages reflect a specific problem in my
>> dataset ? And if the number mentioned might give me a hint on which
>> column to look at (and maybe transform or ignore for the
>> imputation) ?
>> Thanks for any advice you might have.
David Winsemius, MD
West Hartford, CT
More information about the R-help