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 Claire Smith posted on Thursday, August 30, 2018 - 8:38 am

I've established measurement invariance for my variable of interest (burnout) across two time points. The CFA results in good model fit for each time point individually. However, when I attempt a latent change model, the model fit becomes terrible. Any thoughts about what the issue could be?

Thank you!
 Bengt O. Muthen posted on Thursday, August 30, 2018 - 4:26 pm
A typical source of misfit is that the residuals of the factor indicators need to be correlated across time for the same indicator.
 Claire Smith posted on Friday, August 31, 2018 - 5:55 am
Thank you so much. That did help.

I have a more general question about what analyses you would recommend. I am interested if the change in burnout over the course of a month (two time points) is explained by the pattern of change in energy (across 4 time points throughout the month).

Do you have any recommendations for how to approach this? I am reading the Geiser MPlus book and am struggling to find an analytic approach that fits my question.
 Bengt O. Muthen posted on Friday, August 31, 2018 - 1:47 pm
See sequential processes in the Short Course Topic 6 video and handout slides 158-168 on our web site.
 Bengt O. Muthen posted on Friday, August 31, 2018 - 1:52 pm
You can also do this without mixtures and simply say

s2 on s1;

You would also have to think about how i2 relates to i1 and s1. See also the paper on our website:

Muthén, B., Khoo, S.T., Francis, D. & Kim Boscardin, C. (2003). Analysis of reading skills development from Kindergarten through first grade: An application of growth mixture modeling to sequential processes. Multilevel Modeling: Methodological Advances, Issues, and Applications. S.R. Reise & N. Duan (Eds). Mahaw, NJ: Lawrence Erlbaum Associates, pp.71-89.
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