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GMM with skew t distribution |
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Siny Tsang posted on Monday, April 03, 2017 - 9:01 am
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Hello, I am trying to modify the Mplus code in Muthen & Asparouhov (2015) to fit some longitudinal BMI data, but I'm a bit confused with the Mplus codes provided in the Appendix. The data is positively skewed, so we're looking to use DISTRIBUTION = SKEWT. With time varying covariates (i.e., age), I am assuming that we should use the codes in Tables B1 and B2 as an example. Instead of using the AT command to specify time-varying covariates, I see that the ON command is used. However, I don't quite understand why the regression paths are constrained to be equal for the different time points? Is there a way to get the equivalent of the slope estimates as in GMM with normal distribution? Thanks. |
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Siny Tsang posted on Monday, April 03, 2017 - 10:03 am
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Follow up to my previous message, I am guessing that the estimated coefficient for the ON path is the same as the estimated means for the slope if we use the usually GMM script: i s | w1 w2 w3 w4 AT age1 age2 age3 age4; So what happened to the variances of S if we use the ON method like this? i BY w1-w4@1; w1 ON age1; w2 ON age2; w3 ON age3; w4 ON age4; Is this essentially a fixed slope within class (but vary between class)? If so, can we model a class-varying slope effect as well? Thanks. |
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Which Tables B1 and B2 are you referring to - in which document? For the second question, say s | w1 ON age1; s | w2 ON age2; s | w3 ON age3; s | w4 ON age4; |
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Siny Tsang posted on Monday, April 10, 2017 - 6:54 am
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The Tables B1 and B2 were in the "Growth mixture modeling with non-normal distributions" paper (Muthen & Asparuhov, 2014). Is there a way to get the class-varying slope effect with DISTRIBUTION = SKEWT? Thanks! |
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I'm sorry but I don't see such tables in that paper - can you email me what you are looking at? Class-varying slopes can be handled. If not directly, then indirectly using a factor with class-varying loadings. |
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