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Multivariate Outcomes Model - Bayesia... |
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Hi, I am currently analyzing data using a multivariate outcomes application of HLM (e.g., see Brennan, Kim, Wenz-Gross et al. 1997). However, I would like to apply Bayesian estimation to this model. As I've been running it, the within-subject model looks like this: yij = b1(outcome 1) + b2(outcome 2) + b3(outcome 3) + r Where outcomes 1-3 are 0/1 dummy codes and b1-b3 are treated as latent variables. To do this I've been using a known reliability for each of these outcomes calculating the measurement error myself (1-reliability) * observed variance. Also, note that there is no intercept because the model is saturated. The between-subject model includes one continuous covariate. So, in HLM terms it's: B1 = G10 + G11(Covariate) + u1j B2 = G20 + G21(Covariate) + u2j B3 = G30 + G31(Covariate) + u3j Although I intend to take the Bayesian short course at UConn, I would like to analyze these data ASAP with Bayesian estimation. Could you please advise me as to what commands I should use in MPlus, given that this is a "special" application of a MLM? Best, Lindsay |
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You would use in the ANALYSIS command: TYPE=TWOLEVEL; ESTIMATOR=BAYES; |
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