Looks like you have a data frame where you need a matrix. (The same
issue occurs in most of Joe Schafer's packages, e.g. mix.)
Try as.matrix(usnews).
On Tue, 24 Apr 2007, Brant Inman wrote:
> R-experts:
> I am trying to reproduce some of Paul Allison's results in his little
> green book on missing data (Sage 2002). The dataset for which I am
> having problems, "usnews", can be found at:
> http://www.ats.ucla.edu/stat/books/md/default.htm. I am working on a
> Windows machine with R 2.5 installed, all packages up-to-date.
> The problem has to do with the prelim.norm() function of the package
> "norm". Specifically, I need to use this pre-processing
function to
> later use the EM algorithm and DA procedures in the norm package. I
> am getting an error with the following code.
> ----------------------
>> pre <- prelim.norm(usnews)
>
> Error in as.double.default(list(csat = c(972L, 961L, NA, 881L, NA, NA, :
> (list) object cannot be coerced to 'double'
>
> ---------------------
> I have read the previous postings and I am wondering if the problem
> with prelim.norm is the size of the usnews dataset or the amount of
> missing data.
>
> --------------------
>
>> dim(usnews)
> [1] 1302 7
>
> --------------------
>
>
> Does anyone have any ideas? If not, are there alternatives to norm
> for implementing the MLE and EM methods of dealing with missing data?
>
> Thanks,
>
> Brant Inman
> Mayo Clinic
>
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>
--
Brian D. Ripley, ripley at stats.ox.ac.uk
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, UK Fax: +44 1865 272595