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Roger Brown posted on Wednesday, March 02, 2016 - 7:15 am
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Can we build a zero-inflated ordered probit model in Mplus? If not, would a ZINB model be a close approximation? |
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Are you thinking about more than 2 outcome categories? Is the outcome ordinal? |
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Roger Brown posted on Wednesday, March 02, 2016 - 5:11 pm
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Yes, 5 ordered categories |
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Zero-inflated modeling is equivalent to a two-class model with all zeros in one of the two classes. You can use zero-inflated ordered probit by introducing a latent class variable C(2) for each variable that has a zero inflated distribution. |
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Dear Professors, I am trying to test a cross-lagged panel model with ZIOP. I have 2 timepoints and 2 outcomes. 1 is binary (drug use – yes, no); 1 is ordinal (drug communication – 0 times, 1 time, 2 times, 3 or more times). The ordinal variable is zero-inflated. 1. Does my syntax appear correct? I cannot get the model to converge, whether I run the simple model, or include additional covariates to provide more information for the model. 2. Is there a way I can include the autocorrelation between the outcomes? Loading the outcomes onto latent variables, in order to correlate the errors makes the model more complicated. I appreciate any help you can offer. Thank you!! Syntax: USEVARIABLES are Y3MJ01 Y4MJ01 Y3com Y4com male age; missing = all (99); CATEGORICAL = Y4com Y4MJ01; classes = c (2) ANALYSIS: TYPE=MIXTURE; ESTIMATOR = MLR; LINK = PROBIT; ALGORITHM = INTEGRATION; INTEGRATION=MONTECARLO; MODEL: %overall% [Y4com$1]; Y4com on Y3com Y3MJ01 male age ; Y4MJ01 on Y3com Y3MJ01 male age; Y3com with Y3MJ01; %C#1% [Y4com$1@0]; Y4com on Y3com Y3MJ01 male age ; Y4MJ01 on Y3com Y3MJ01 male age; Y3com with Y3MJ01; %C#2% [Y4com$1]; Y4com on Y3com Y3MJ01 male age ; Y4MJ01 on Y3com Y3MJ01 male age; Y3com with Y3MJ01; |
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We need to see your full output - please send your output to Mplus Support along with your license number. |
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