Mplus Users Guide v6.. - Muthén & Muthén

CHAPTER 17| names and defines random effect variablesexample: s | y1 ON x1;ATshort for measured at -- defines random effect variablesexample: s | y1-y4 AT t1-t4;XWITHdefines interactions between variables;MODEL INDIRECT:describes the relationships for which indirect and total effects arerequestedINDdescribes a specific indirect effect or a set of indirect effects;VIAdescribes a set of indirect effects that includes specificmediators;MODEL CONSTRAINT: describes linear and non-linear constraints on parametersNEWassigns labels to parameters not in the analysis model;MODEL TEST:describes restrictions on the analysis model for the Wald testMODEL PRIORS:specifies the prior distribution for the parametersFollowing are variations of the MODEL command:MODEL:MODEL label:MODEL:%OVERALL%%class label%MODEL:%WITHIN%%BETWEEN%MODEL POPULATION:MODEL POPULATION-label:MODEL POPULATION:%OVERALL%%class label%MODEL POPULATION:%WITHIN%%BETWEEN%describes the analysis modeldescribes the group-specific model in multiple group analysisand the model for each categorical latent variable andcombinations of categorical latent variables in mixture modelingdescribes the overall part of a mixture modeldescribes the class-specific part of a mixture modeldescribes the within part of a two-level modeldescribes the between part of a two-level modeldescribes the data generation model for a Monte Carlo studydescribes the group-specific data generation model in multiplegroup analysis and the data generation model for eachcategorical latent variable and combinations of categoricallatent variables in mixture modeling for a Monte Carlo studydescribes the overall data generation model of a mixture modeldescribes the class-specific data generation model of a mixturemodeldescribes the within part of a two-level data generation modelfor a Monte Carlo studydescribes the between part of a two-level data generationmodel for a Monte Carlo study570