I am trying to fit a multilevel random-intercept mediation model with Bayes estimates (due to small between-level sample size), non-informative priors, and an ordered dependent variable. I cannot find information about whether the model uses a probit or logit link function by default.
After reading the Asparouhov and Muthen (2010, version 3) paper on the technical implementation of Bayesian analysis, I get the impression it estimates an ordered probit model (I concluded this because the Gibbs sampling algorithm is based on a probability distribution). Have I interpreted this correctly?
Also, I would like to calculate predicted probabilities based on values of the between-level predictor. I think it can be done using MODEL CONSTRAINT, but I'm not quite sure how to do it. Is it possible using the following model?
USEVARIABLES = dv mediator lvl2iv iv country; CATEGORICAL = dv ; WITHIN = iv ; BETWEEN = lvl2iv ; CLUSTER = country ;
ANALYSIS: TYPE = TWOLEVEL ; ESTIMATOR = BAYES ;
MODEL: %WITHIN% dv ON mediator iv ; mediator ON iv ; %BETWEEN% mediator ON lvl2iv (x) ; dv ON mediator (m) ; dv ON lvl2iv ;