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Two-part model with an ordinal outcome |
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Mplususer posted on Tuesday, December 12, 2006 - 4:19 pm
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Dear Dr. Muthen, Would you mind dropping me a hint about modeling two-part GMM with an ordinal outcome. My question is as follows: ********************************************************************** Let's use Example 6.16 in Mplus user's guide DATA: FILE = ex6.16.dat; DATA TWOPART: NAMES = y1-y4; BINARY = bin1-bin4; CONTINUOUS = cont1-cont4; ! Can it be changed to Categorical = cont1-cont4 for my ordinal outcome? VARIABLE: NAMES = x y1-y4; USEVARIABLES = bin1-bin4 cont1-cont4; ! Do I need to add Categorical = cont1-cont4 here ? CATEGORICAL = bin1-bin4; MISSING = ALL(999); ! Can I add Classes = (2) for mixture modeling |
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Mplususer posted on Tuesday, December 12, 2006 - 4:20 pm
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ANALYSIS: TYPE = MISSING; ! Can I specify Type = Mixture Missing; here? ESTIMATOR = MLR; MODEL: ! Can I add %Overall% and %c#1% statements for my two-part growth mixture model iu su | bin1@0 bin2@1 bin3@2 bin4@3; iy sy | cont1@0 cont2@1 cont3@2 cont4@3; su@0; iu WITH sy@0; ************************************************************************* Looking forward to your reply. Respectfully, UseMplus |
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Two-part growth modeling describes growth in two parts: a binary part and a non-zero (typically continuous) part. You can do two-part modeling where the non-zero part is treated as ordered categorical. This would allow the binary and the non-zero parts of the model to have different covariate effects. With floor effects, the lowest category would be scored missing in the non-zero part. This cannot, however, be done in a single DATA TWOPART run because the CONTINUOUS = part is needed. You would have to first do a regular DATA TWOPART run and save the data. Then run these data with a regular input for parallel process growth modeling with a binary and a ordered categorical outcome. Mixture modeling can be added to this, either with one latent class variable or one for each process, possibly correlating the two latent class variables. |
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Mplususer posted on Wednesday, December 13, 2006 - 8:25 am
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Thanks! If you don't mind, I would like to make sure if I truely understand you, as I am a beginner with this modeling. (1) By "first do a regular DATA TWOPART run and save the data": Do you mean dividing my data into the binary part and the non-zero (ordinal) part. If so, I think I have done with it. If not, would you correct me? (2) By parallel process GMM, you mean I can refer to Example 6.13 in User's Guide but treat my data as with a binary and a ordered categorical outcome and I can use regular mixture statements (e.g., Classes = (2), etc.) for these two parallell processes just as you suggested ("with one latent class variabel...two latent class variables"), right? Thanks UseMplus |
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1. Just be sure you have created the variables correctly. You can see the rules in DATA TWOPART. 2. Sounds right. |
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Mplususer posted on Wednesday, December 13, 2006 - 12:06 pm
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Thanks. |
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