Log-normal distribution for within-pe... PreviousNext
Mplus Discussion > Growth Modeling of Longitudinal Data >
 Qiwen Zheng posted on Thursday, June 16, 2016 - 1:40 pm
Hi all,

Anyone know how to specify a log-normal distribution instead of the default normal distribution of the within-person residual?

My model is a two-part random intercept model, the data is longitudinal with each person with 8 repeated measures. I want to compare model-data fit under normal v.s. log-normal distribution for the within-person residual e_ij.

Below is the model for the continuous part:
where i is person and j is time.

My Mplus code:
u is a binary dependent variable and m is a continuous dependent variable. Both X1 and X2 are time-varying covariates.

Names are ID u m X1 X2;
Missing are all (-999) ;
usevariables are ID u m X1 X2;
cluster = ID;
within = X1 X2;
ANALYSIS: type = twolevel random;
u on X1 X2;
m on X1 X2;
u with m*;

Many thanks!
 Tihomir Asparouhov posted on Thursday, June 16, 2016 - 5:32 pm
You can perform the log transformation in the define command and then compare the likelihoods. They are on different scale however - you need to add Sum Log (data) to put the likelihoods on the same scale. It is not possible to explicitly model only the residual using log-normal.

Some other possibilities are available through the constraint = command as in user's guide example 5.23.
 Qiwen Zheng posted on Thursday, June 16, 2016 - 8:03 pm
Thank you Dr. Asparouhov! I now understand that I should do log transformation to the dependent variable.
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