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Re: st: exploratory factor analysis with dichotomous and continuous data


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: exploratory factor analysis with dichotomous and continuous data
Date   Mon, 26 Nov 2012 10:26:43 +0000

These are both things you can try.

It's best not to treat Statalist as an oracle which can tell you what
is right and wrong for your project, not least because there is no
glimpse here of the scientific (medical, clinical) problem which
should guide choice of technique.

Nick

On Mon, Nov 26, 2012 at 9:55 AM, Frauke Rudolf <FRAUKE.RUDOLF@ki.au.dk> wrote:
> Dear jay and Nick,
> Thank you for your answers.
> One final question: is it possible and does it make sense to do the FA leaving hemoptysis out? Can I the  afterwards assume that it would end in the same group as cough?
> Frauke
>
> -----Oprindelig meddelelse-----
> Fra: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] På vegne af JVerkuilen (Gmail)
> Sendt: 23. november 2012 03:56
> Til: statalist@hsphsun2.harvard.edu
> Emne: Re: st: exploratory factor analysis with dichotomous and continuous data
>
> On Thu, Nov 22, 2012 at 3:27 PM, Frauke Rudolf <FRAUKE.RUDOLF@ki.au.dk> wrote:
>> The idea is to do an exploratory data-analysis (followed by a CFA) on 11 clinical variables, some dichotomous and some continuous, to reduce the amount of variables in the score. The only variable having this "structural zero problem" is the one described here. Do I really have to change the plan, or is there another way? Do have to write the article for my PhD and appreciate every help I can get here, since I am quite new to the subject (as you probably already guessed...)>
>
> It turns out a colleague and I have done some research work on IRT and
> by extension factor analytic models of data when there is functional
> dependence between items.
>
>       Liu, Y. & Verkuilen, J. (in press). Item response modeling of
> presence-severity data. Applied Psychological Measurement.
>
> However, the problem that we treated isn't directly analogous so I
> can't say that you should be able to adapt what we did in a
> straightforward way. I suspect Ying and I would be willing to take a
> look at it (with appropriate credit of course) as dealing with the
> effect of functional dependence in psychometric models is a research
> area I'm active in, and we've had a devil of a time getting datasets,
> but of course you may not be able to share it.
>
> The best answer I have at the moment is exactly what Nick already
> said: You have to exclude it.

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