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Dear. Muthen. I have an EMA data, which combines several observations to produce one latent variable Y. A total of 65 people respond four times a day for a week and come up with the value each time they respond. 1. I'm not sure which of the two level time series or cross classified time series (N> 1) is more appropriate (see the presentation Johns Hopkins Workshops, 08172017, Part 3 (Muthen)). 2. In the case of the two level time series, smoking example used two variables: urge and negative affect. is it the same as in my case? 3. In addition, my variable is a latent variable, but are the above two methods applicable? I considered latent growth model before. 4. If I were to intervene and divide it into two groups, would I add this to the 'between' command? 5. Can you recommend a paper that analyzes EMA data with DSEM? Thank you very much for your time. 


1. Sounds like you should use twolevel modeling. 2. You mention a latent variable so perhaps you have several factor indicators measured at each time point. 3. You can do factor analysis DSEM. 4. See all the applied DSEM papers at http://www.statmodel.com/TimeSeries.shtml 

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