Hi David, Phil,
Phil Spector wrote:
>> David -
>> Here's the easiest way I've been able to come up with.
Easiest? You are making unnecessary work for yourselves and seem not to
understand the purpose of ?naresid (i.e. na.action = na.exclude). Why not
take the simple route that I gave, which really is R's + factanal's route.
Using Phil's data as example:
##
dat = data.frame(matrix(rnorm(100),20,5))
dat[3,4] = NA
dat[12,3] = NA
scrs <- factanal(~X1+X2+X3+X4+X5, data=dat,factors=2,scores='regression',
na.action=na.exclude)$scores
TrueDat <- merge(dat,scrs,by=0,all.x=TRUE,sort=FALSE)
TrueDat
Regards, Mark.
David G. Tully wrote:
>
> Thanks, Prof Spector. Your first solution works well for me.
>
> Phil Spector wrote:
>> David -
>> Here's the easiest way I've been able to come up with. I'll provide
>> some sample data to make things clearer (hint, hint):
>>
>>> dat = data.frame(matrix(rnorm(100),20,5))
>>> dat[3,4] = NA
>>> dat[12,3] = NA
>>> scrs = factanal(na.omit(dat),factors=2,scores='regression')$scores
>>> rownames(scrs) = rownames(na.omit(dat))
>>> newdat = merge(dat,scrs,by=0,all.x=TRUE,sort=FALSE)
>>
>> This will result in the observations with missing values being
>> at the end of the data frame. If you want the original order
>> (assuming default row names), you could use
>>
>> newdat[order(as.numeric(newdat$Row.names)),]
>>
>> A somewhat more complicated approach is, in some sense, more direct:
>>
>>> dat$Factor1 = NA
>>> dat$Factor2 = NA
>>> dat[rownames(na.omit(dat[,-c(6,7)])),c('Factor1','Factor2')] =
>> +
>> factanal(na.omit(dat[,-c(6,7)]),factors=2,scores='regression')$scores
>>
>> The order of the data is preserved.
>> - Phil Spector
>> Statistical Computing Facility
>> Department of Statistics
>> UC Berkeley
>> spec...@stat.berkeley.edu
>>
>>
>>
>>
>>
>>
>>
>>
>> On Tue, 25 Aug 2009, David G. Tully wrote:
>>
>>> I am sure there is a simple way to do the following, but i haven't
>>> been able to find it. I am hoping a merciful soul on R-help could
>>> point me in the right direction.
>>>
>>> I am doing a factor analysis on survey data with missing values. to
>>> do this, I run:
>>>
>>> FA1<-factanal(na.omit(DATA), factors = X, rotation = 'oblimin',
>>> scores = 'regression')
>>>
>>> Now that I have my factors and factor scores, I want to add those
>>> scores back to my original dataset so I can plot factor scores by
>>> demographics. However, when I try to add the scores back to the
>>> original data frame, the variables are of different lengths.
>>>
>>> Is there a way to subset from my original data set that will work
>>> with factanal() and preserve the original rows or that will allow me
>>> to append the factor scores back onto the original dataset with the
>>> proper rows and NAs where there could be no data?
>>>
>>> Again, I apologize if I am missing something basic. I am a self
>>> taught R user and couldn't find an answer to this question.
>>>
>>> Thanks in advance,
>>> David
>>>
>>> ______________________________________________
>>> R-help@r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
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