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I have the following code for a dataset I am running. VARIABLE: NAMES ARE ID GP Y1Y18 U1U3 MFS OVS AMS WVS LCS OV RLN SM WV LC RDN; USEVARIABLES ARE Y1Y18 U1U3 OV SM RDN; CLASSES = cg (4) c(2); KNOWNCLASS = cg (GP = 1 GP = 2 GP = 4 GP = 5); CATEGORICAL = U1U3; CENTERING = GRANDMEAN (OV SM RDN); MISSING IS BLANK; AUXILIARY = ID; ANALYSIS: TYPE=MIXTURE MISSING; ESTIMATOR=MLR; STARTS = 20 2; MODEL: %OVERALL% i s q Y1@0 Y2@1 Y3@2 Y4@3 Y5@4 Y6@5 Y7@6 Y8@7 Y9@8 Y10@9 Y11@10 Y12@11 Y13@12 Y14@13 Y15@14 Y16@15 Y17@16 Y18@17; i s q ON OV SM RDN; f BY U1U3@1; c#1 ON cg#1 OV SM RDN; c#1 ON cg#2 OV SM RDN; c#1 ON cg#3 OV SM RDN; My question is whether there is a way to specify just 1 latent class in cg#3? Thanks, Don 


cg#3 refers to class 3 of the categorical latent variable cg. If you want the categorical latent variable cg to have one class, you would specify CLASSES = cg (1); 


Yes I understand that, however wouldn't that set the number of classes to 1 in all known groups? What I was hoping to achieve was cg#1(2), cg#2(2), cg#3(1), and cg#4(2). Can this be done within the classes command? Thanks, Don 


I think what you are asking is whether a known class can have a different number of classes on the other categorical latent variable. I think you would specify this as follows: MODEL: %OVERALL% c#2 ON cg#3@15; 


Apologies for the simplicity of this question, but I just need to clarify.... I am running a growth mixture model with known classes (multiple group analysis), using a binary dependent variable U. In the output there is a threshold value (identical across groups), as well as an intercept and slope that are unique to each group. The probability of U = 1/(1+e(threshold + intercept + slope*time)) Logit = threshold + slope*time Correct? 


The logit is your argument: threshold + intercept + slope*time Note that this gives the probability conditional on these intercept and slope values. 

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