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Erin P posted on Monday, July 09, 2012 - 7:59 pm
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I'm hoping you can help me figure out where I'm going wrong... VARIABLE: ... MISSING ARE .; CENSORED ARE outcome (b); MODEL: F1 BY v1-v3 F2 BY v4; F3 BY v5; F4 BY v6; F5BY v7; v4@0; v5@0; v6@0; v7@0; F6 BY v8; F6 ON F1-F5; F7 BY outcome; F7 ON f6; outcome@0; v8@0; ---------------------------- This is the error message I get: *** FATAL ERROR THE STARTING VALUE FOR THE VARIANCE OF A CENSORED VARIABLE outcome IS NOT POSITIVE. |
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I would imagine it is for setting the residual variance of outcome at zero. It is not necessary to put a latent variable behind an observed variable in Mplus. Simply specify your model using the observed variables. MODEL: F1 BY v1-v3 v8 ON f1 v4 v5 v6 v7; outcome ON v8; |
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Barbara O. posted on Tuesday, January 08, 2013 - 6:06 pm
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I'm conducting a path analysis using a censored outcome variable (time 3 variable), 3 continuous mediators (time 2 variables), and 3 initial (time 1) predictors. The analysis requires montecarlo integration, and I was able to use the constraint command to estimate the indirect effects. I'm wondering: 1) Is there a way to use bootstrapping to test for sig mediation (rather than testing the indirect effects)? I get an error message when I try. 2) The output provides AIC, BIC, and my log-likelihood value, but not RMSEA or GIF- is there a way to get these values using path analysis with a censored outcome variable? |
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1. What is the message? 2. Chi-square and related fit statistics are available only when means, variances, and covariances are sufficient statistics for model estimation. This is not the case when numerical integration is needed. |
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Barbara O. posted on Tuesday, January 08, 2013 - 6:46 pm
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1. The error message I receive is: "BOOTSTRAP is not allowed with ALGORITHM=INTEGRATION." I'm concerned reviewers might ask for RMSEA. If so, is a response similar to yours above something appropriate to give? Thank you for your time! |
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1. BOOTSTRAP has not yet been developed for numerical integration. 2. RMSEA does not exist when means, variances, and covariances are not sufficient statistics for model estimation. |
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Given that model fit indices are not provided for censored models, what is the recommended way of assessing/reporting model fit? Thanks! |
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WLSMV gives model fit tests with censored. But with ML you have to work with "neighboring models", that is, add a less restrictive model and see if its extra parameters are significant. |
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