I have been running some models that decompose multi-wave data into a stable trait component, an autoregressive trait component, and a state component. I have eight waves, with three indicators at each wave, 600 observations, and I'm using raw data (and there are missing data). With the data I have, these models (and some variants) can take a little while to run. But I've noticed that they actually run considerably slower with version .5.0 than with .3.0 (I hadn't upgraded until .5.0 came out). The results I get are identical (at least to about 7 decimals), but it takes more time. For instance, one of the models took 2.41 minutes in .3.0, versus 12.13 minutes in .5.0. Just curious whether with the performance optimizations, some model characteristics actually lead to a slowdown.
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