[R-sig-ME] How to perform a latent variable model over a random effect,

[Ren-Huai Huang]

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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