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.
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;