Mplus Users Guide v6.. - Muthén & Muthén

CHAPTER 16• COMPLEX computes standard errors and a chi-square test of modelfit taking into account stratification, non-independence ofobservations, and/or unequal probability of selection.TWOLEVELAnalyses using TYPE=TWOLEVEL include models with randomintercepts and random slopes that vary across clusters in hierarchicaldata. These random effects can be specified for any of the relationshipsof the multilevel modeling framework. Observed outcome variables canbe continuous, censored, binary, ordered categorical (ordinal), unorderedcategorical (nominal), counts, or combinations of these variable types.Special features available for multilevel models for all observed outcomevariable types are:• Single or multiple group analysis• Missing data• Complex survey data• Latent variable interactions and non-linear factor analysis usingmaximum likelihood• Random slopes• Individually-varying times of observations• Linear and non-linear parameter constraints• Maximum likelihood estimation for all outcomes types• Wald chi-square test of parameter equalitiesFollowing is a list of the other TYPE settings that can be used inconjunction with TYPE=TWOLEVEL along with a brief description oftheir functions:• BASIC computes sample statistics and other descriptive information.• RANDOM allows models with both random intercepts and randomslopes.• MIXTURE allows models that have both categorical and continuouslatent variables.• COMPLEX computes standard errors and a chi-square test of modelfit taking into account stratification, non-independence ofobservations, and/or unequal probability of selection.528