I would like to understand whether (and, if so, how) Finite Mixture Modeling regression differs from Latent Class regression with -gsem-.
In the code below, I first estimate starting values and then estimate an FMM regression (Model A) and a Latent Class regression (Model B), specifying 2 latent classes in each model. The variables score and x1-x4 are all continuous measures.
As coded above, are these two approaches and the estimating models equivalent?
I apologize that I cannot provide the data with dataex and I understand that might make it more difficult to respond to my request, but I would appreciate any insight or advice that can be offered based on the code I have provided above.
By the way, I have not been able to get Model A to resolve to a solution even with the -nonrtolerance- option specified unless I add the -nocons- option. I decided not to pursue that issue further until I have advice about whether my general approaches are equivalent and correctly coded.
Thanks in advance for any help or insight you will offer.
Red Owl
Stata/IC 15.1 (Windows 10, 64-bit)
* Edited to clarify that the variables are all continuous measures.
In the code below, I first estimate starting values and then estimate an FMM regression (Model A) and a Latent Class regression (Model B), specifying 2 latent classes in each model. The variables score and x1-x4 are all continuous measures.
Code:
* Obtain a matrix of starting values for FMM regression (Model A below) quietly { fmm 2, vce(cluster id) difficult nonrtolerance startvalues(randomid, seed(1234567)): /// regress score x1-x4 matrix FMMb02 = e(b) } * Obtain a matrix of starting values for Latent Class regression (Model B below) quietly { gsem (score <- x1-x4) (C <- _cons), lclass(C 2) vce(cluster id) /// lcinvariant(none) covstructure(e._OEn, unstructured) difficult nonrtolerance matrix LCRegb02 = e(b) } * Model A: FMM Regression fmm 2, vce(cluster id) difficult from(FMMb02): regress score x1-x4 * Model B: Latent Class Regression gsem (score <- x1-x4) (C <- _cons), lclass(C 2) vce(cluster id) /// lcinvariant(none) covstructure(e._OEn, unstructured) difficult from(LCRegb02)
I apologize that I cannot provide the data with dataex and I understand that might make it more difficult to respond to my request, but I would appreciate any insight or advice that can be offered based on the code I have provided above.
By the way, I have not been able to get Model A to resolve to a solution even with the -nonrtolerance- option specified unless I add the -nocons- option. I decided not to pursue that issue further until I have advice about whether my general approaches are equivalent and correctly coded.
Thanks in advance for any help or insight you will offer.
Red Owl
Stata/IC 15.1 (Windows 10, 64-bit)
* Edited to clarify that the variables are all continuous measures.
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