[R] Re : aregImpute (Hmisc package) : error in matxv(X, xcof)...

[David Winsemius]

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  
filter
>
> Marc
>
> ________________________________
> 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,  
> xcof)...
>
> 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 :
>> http://www.mail-archive.com/r-help@r-project.org/msg53534.html
>>
>> 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.
>>
>> Marc
>>
>


David Winsemius, MD
West Hartford, CT