On Thu, 19 Jan 2006, Henric Nilsson wrote:
> ivo welch said the following on 2006-01-18 14:56:
>
>> thank you. I am still not sure how to get the scores in princomp, though:
>>
>> ds= as.data.frame( cbind(rnorm(10),rnorm(10)) )
>> names(ds)=c("x1","x2")
>> ds[5,]=c(NA,NA)
>> pc= princomp( formula = ~ ds$x1 + ds$x2, na.action=na.omit)
>> ds$pc1 = pc$scores[,1] #<-- error, scores has 9 obs, ds has 10 obs
>>
>> is there an elegant method to do this, or do I need to learn how to operate
>
> Prof Ripley told you how to do it: `na.action = na.exclude'.
>
>> with pc$loadings? (may I also humbly suggest that the default behavior or
>> $scores should be to contain NA in row 5?)
>
> Choosing sensible defaults in the case of NAs is a tricky business.
>
> Personally, I'd like the default to be `na.fail', so that I don't miss
> out on NAs if I've been sloppy while screening the data. Genrally, just
> ignoring missings and analysing the data as if it were complete may lead
> to seriously biased results.
I tend to agree (and so does S). You can achieve this with
options(na.action=na.fail), almost everywhere.
--
Brian D. Ripley, [EMAIL PROTECTED]
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
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