Mplus Users Guide v6.. - Muthén & Muthén

ANALYSIS Commandare imputed using a single-level unrestricted H1 model in which case thedefault is OBSERVED. When the OBSERVED setting is specified, themediator is treated as a continuous observed variable. To request thatthe mediator be treated as observed, specify:MEDIATOR = OBSERVED;ALGORITHMThe ALGORITHM option is used to specify the Markov chain MonteCarlo (MCMC) algorithm to use for generating the posterior distributionof the parameters (Gelman et al., 2004). The ALGORITHM option hastwo settings: GIBBS and MH. The default is GIBBS. The GIBBSsetting uses the Gibbs sampler algorithm which divides the parametersand the latent variables into groups that are conditionally andsequentially generated. The MH setting uses the Metropolis-Hastingsalgorithm to generate all of the parameters simultaneously using theobserved-data loglikelihood. The MH setting uses maximum likelihoodstarting values. The MH proposal distribution uses the estimatedcovariance matrix of the maximum likelihood parameter estimates.The MH algorithm is not available for TYPE=MIXTURE orTYPE=TWOLEVEL. To request that the Metropolis-Hastingsalgorithm be used, specify:ALGORITHM = MH;BCONVERGENCEThe BCONVERGENCE option is used to specify the value of theconvergence criterion to use for determining convergence of theBayesian estimation using the Gelman-Rubin convergence criterion(Gelman & Rubin, 1992). The Gelman-Rubin convergence criteriondetermines convergence by considering within and between chainvariability of the parameter estimates in terms of the potential scalereduction (PSR) to determine convergence (Gelman et al., 2004, pp. 296-298). The default is 0.05. The BCONVERGENCE value is used in thefollowing formula (Asparouhov & Muthén, 2010):a = 1 + BCONVERGENCE* factor,561