[R-sig-ME] random effect latent variable model,

[Baldwin, Jim -FS]

I  think you'd get a better response if you gave a complete (but maybe minimal) working example.  Also, I suspect you'd be better off if your example used PROC GLIMMIX in SAS rather than PROC NLMIXED.  And maybe showing what you've tried so far would also create more interest to help.

Jim


-----Original Message-----
From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of Ren-Huai Huang
Sent: Tuesday, January 03, 2017 8:57 PM
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] random effect latent variable model,

Happy new year,

My question is how to replicate the following sas code in R, Julia or other open source languages? Thanks in advance!

proc nlmixed data=input tech=dbldog qpoints=30 noad;
        ...
    model   id ~ general(loglik);
    random  latent_var ~ normal(0, 1) subject= id;
       ...
run;

Regards,

Renhuai


On Fri, Dec 30, 2016 at 4:24 PM, Ren-Huai Huang <huangrenhuai at gmail.com>
wrote:

> Re: Random Effect Latent Variable Model
>
>
>
> Dear mixed model members,
>
>
> I am trying to do a weighted latent variable modeling with random
> effects in R, which is similar to sas nlmixed general log likelihood
> over a random effect (sas code attached here
> <https://huangrh.github.io/relvm/vignettes/sascode.html>). The purpose
> is to calculate a latent variable from 7 observed variables x1, x2, …
> , x7 with weightings w1, w2, … , w7 to the corresponding likelihood of
> the variables (the dataset is attached here
> <https://github.com/huangrh/relvm/blob/master/inst/extdata/dat244.csv>).
>
>
> Both equations of the weighted log likelihood and the random effect
> log likelihood are linked here
> <https://huangrh.github.io/relvm/vignettes/formula.html> (equations 2
> and 3). I was wondering if the subjective function should be the joint
> probability of both equations 2 and 3, as shown in equation 4. How to
> join the equation 2 with the random effect?
>
>
> I tried to optimize the function (link to the R code, lines 36-37
> <https://github.com/huangrh/relvm/blob/master/R/nll.R>) using optim in
> R (link to vignette
> <https://huangrh.github.io/relvm/vignettes/Random_Effect_Latent_Variable_Model.html>).
> But the result is very different from the sas nlmixed mentioned above
> <https://huangrh.github.io/relvm/vignettes/sascode.html>.
>
>
> Any suggestions are very welcome to help me to do this right in R.
> Thank you very much in advance.
>
>
>
> Sincerely,
>
> Ren-Huai Huang
>

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