Mplus Users Guide v6.. - Muthén & Muthén

two-level growth mixture model (GMM) witha between-level categorical latent variable,325–27two-level growth model with a between-levelcategorical latent variable, 317–20two-level item response theory (IRT), 308–10two-level latent class analsyis (LCA) with abetween-level categorical latent variable,314–16two-level latent class analysis (LCA), 311–13two-level latent class growth analysis(LCGA), 328–30two-level latent transition analysis (LTA),330–32two-level latent transition analysis (LTA) witha between-level categorical latent variable,333–35two-level mixture regression, 292–97, 298–301, 302–4multilevel modelingtwo-level confirmatory factor analysis (CFA)with categorical factor indicators, 255–56two-level confirmatory factor analysis (CFA)with continuous factor indicators, 252–54,256–58two-level growth for a zero-inflated countoutcome (three-level analysis), 284–86two-level growth model for a categoricaloutcome (three-level analysis), 272–73two-level growth model for a continuousoutcome (three-level analysis), 269–72two-level multiple group confirmatory factoranalsyis (CFA), 266–68two-level multiple indicator growth model,277–80two-level path analysis with a continuous anda categorical dependent variable, 246–48two-level path analysis with a continuous, acategorical, and a cluster-level observeddependent variable, 248–49two-level path analysis with random slopes,250–52two-level regression for a continuousdependent variable with a randomintercept, 238–43two-level regression for a continuousdependent variable with a random slope,243–45two-level structural equation modeling(SEM), 263–66multinomial logistic regression, 441–45multiple categorical latent variables, 164–66multiple cohort, 129–33multiple group analysisknown class, 176–77, 216–18MIMIC with categorical factor indicators, 75–76MIMIC with continuous factor indicators, 74–75special issues, 421–32multiple imputation, 401, 458–59, 461–65missing values, 347–49, 351–56plausible values, 349–51multiple indicators, 121–23, 123–24multiple solutions, 413–15MULTIPLIERANALYSIS, 554SAVEDATA, 673multivariate normal mixture model, 177–79MUML, 533NAMESDATA MISSING, 472DATA SURVIVAL, 476DATA TWOPART, 470MONTECARLO, 690–91VARIABLE, 482NCSIZES, 696NDATASETS, 462negative binomial, 28–29NEW, 616–17NGROUPSDATA, 459MONTECARLO, 691–92NOBSERVATIONSDATA, 459MONTECARLO, 691NOCHECK, 460NOCHISQUARE, 649NOCOVARIANCES, 540–41746