Date:         Tue, 1 Dec 2009 02:43:49 -0800
Reply-To:     Ryan <ryan.andrew.black@GMAIL.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Ryan <ryan.andrew.black@GMAIL.COM>
Organization: http://groups.google.com
Subject:      Re: Latent Class Analysis - Question
Comments: To: sas-l@uga.edu
Content-Type: text/plain; charset=ISO-8859-1

On Dec 1, 2:48 am, Oliver Kuss <Oliver.K...@medizin.uni-halle.de>
wrote:
> On 1 Dez., 02:16, Ryan <ryan.andrew.bl...@gmail.com> wrote:
>
>
>
>
>
> > Hi,
>
> > Let me apologize in advance for asking the same question twice. I
> > figured I'd give it another shot.
>
> > Has anyone seen/developed code to run a random effects latent class
> > analysis in SAS. Let's say we have three dichotomous indicator
> > variables (0=No, 1=Yes) that we hypothesize load on a latent class
> > variable (with 3 classes).
>
> > A simple example I just made up: We suspect that there are three
> > classes of people who use illicit substances (class 1 = non-users/
> > abstainers, class 2 = casual users, class 3 = addicts). Assume we
> > cannot measure directly if someone belongs to any of these classes,
> > but we have 3 indicator variables as indicated previously. Let's also
> > assume that we have two cases per person (measured at equal
> > intervals)...
>
> > /----------------------------------------------/
> > Person    Time     X1     X2     X3
> > 1               1         0       1      1
> > 1               2         1       0      1
> > 2               1         0       0      0
> > 2               2         0       0      1
> > .
> > .
>
> > N
> > /----------------------------------------------/
>
> > Does anyone know how to construct code (presumably in nlmixed) to run
> > a random intercept LCA and compute the following:
>
> > (1) Probability that a positive response on each item is associated
> > with a particular class
> > (2) Probability that each case is associated with a particular class
> > (3) Any indication that the number of classes we selected does not
> > yield the best fitting model. I assume re-running the model assuming 2
> > classes, 4 classes, etc. and comparing AICs/BICs might work.
>
> > Any thoughts/recommendations/references would be great.
>
> > Thanks,
>
> > Ryan
>
> Dear Ryan,
> it seems that you also have a longitudinal structure in your data set
> with two (or even more) observations for each person. Then you should
> definitely look at PROC TRAJ (http://www.andrew.cmu.edu/user/bjones/),
> a user-written SAS prodecure that fits discrete mixture models to
> longitudinal data. I once worked with it and it did fine. Before final
> publication of the results I also coded the model with PROC NLP and it
> yielded the same results. So you might also use PROC NLP or PROC
> NLMIXED for latent class models.
>
> Hope that helps,
> Oliver- Hide quoted text -
>
> - Show quoted text -

Thanks for responding, Oliver. Thank you for the info about TRAJ
procedure. I would prefer to run the model using the NLMIXED
procedure. I assume it is possible to run such a model as evidenced by
a post by Dale a while back:

http://www.listserv.uga.edu/cgi-bin/wa?A2=ind0503a&L=sas-l&D=0&P=26375

What's confusing to me about Dale's post is the dependent variable.
What exactly would be the dependent variable in an LCA such as the
example I made up?

Ryan