Mplus Users Guide v6.. - Muthén & Muthén

missing data, 39–40, 339–41, 342–43, 343–45, 345–46, 347–49, 349–51, 351–56,365–68, 369–70, 373–75, 435–39missing data correlate, 339–41missing data generation, 697–99missing data patterns, 650–51missing data plots, 680missing value flags, 484–86MITERATIONS, 555MIXC, 557MIXTURE, 526–28mixture modelingconfirmatory factor analysis (CFA), 170multivariate normal, 177–79randomized trials (CACE), 179–81, 181–83regression analysis, 146–49structural equation modeling (SEM), 174–75with known class, 176–77zero-inflated Poisson regression analysis,150–51zero-inflated Poisson regression as a two-classmodel, 183–84MIXU, 558MLESTIMATOR, 533STVALUES, 560MLF, 533MLM, 533MLMV, 533MLR, 533MMISSING, 678MNAMES, 677MODE, 559MODELANALYSIS, 540–41DATA IMPUTATION, 463–64MODEL command, 569–631MODEL command variations, 622–25MODEL CONSTRAINT, 615–18MODEL COVERAGE, 627–29model estimation, 407–21MODEL INDIRECT, 613–15MODEL label, 623–24MODEL MISSING, 629–31MODEL POPULATION, 625–27MODEL PRIORS, 619–22MODEL TEST, 618–22modeling framework, 1–6modification indices, 645–47MODINDICES, 645–47MONITOR, 683Monte Carlo simulation studiesdiscrete-time survival analysis, 381–82EFA with continuous outcomes, 375–76external Monte Carlo, 376–79GMM for a continuous outcome, 371–73growth with attrition under MAR, 369–70mediation with random slopes, 387–89MIMIC with patterns of missing data, 365–68missing data, 365–68, 369–70multiple group EFA with measurementinvariance, 389–90saved parameter estimates, 379–80two-level Cox regression, 385–86two-level growth model for a continuousoutcomes (three-level analysis), 373–75two-part (semicontinuous) model, 383–85MONTECARLODATA, 457–58INTEGRATION, 544MONTECARLO command, 689–710mover-stayer model, 225–28Mplus language, 13–14Mplus programbase, 17combination add-on, 18mixture add-on, 17multilevel add-on, 18MSELECT, 678MUCONVERGENCE, 557MUITERATIONS, 555multilevel mixture modelingtwo-level confirmatory factor analysis (CFA),305–7two-level growth mixture model (GMM),321–24745