I've been investigating the AUTOREG procedure for a while now and I had a question about the support for discrete class effects. The option exists but how well is this supported? Has anyone had any experience with it?
Specifically, I have a system with numerous (>130k records) across about ten groups of organisms (moving through the same facility over time (anywhere from 3-12 months depending on stage)), reared in several (ranges from 10-20) units, with contiguous observation arrays of two to several months, for a single dependent variable. Is the class option in AUTOREG sufficient to support this kind of near-mixed modeling longitudinal array?
Best,
GP
I would follow one of @sbxkoenk 's suggestion. This design looks like a mixed model to me. I would assume correlated errors over time and some possible random effects. Fixed effects that jump out at me are organism, time in facility, and their interaction. Random effects would be unit and observation arrays within units. The latter may have some sort of geospatial correlation. So, a complex model with a lot of parameters. I think you have adequate data, but you may not have adequate computing power.
SteveDenham
Hej,
I would like to hear more before answering this.
Koen
I would follow one of @sbxkoenk 's suggestion. This design looks like a mixed model to me. I would assume correlated errors over time and some possible random effects. Fixed effects that jump out at me are organism, time in facility, and their interaction. Random effects would be unit and observation arrays within units. The latter may have some sort of geospatial correlation. So, a complex model with a lot of parameters. I think you have adequate data, but you may not have adequate computing power.
SteveDenham
Hi Steve - thanks also for this. It's pretty much as you and Koen say: definitely mixed for the arrays and tanks within arrays. I analyzed within the arrays using AUTOREG, but I'll check the other procs and see if they have any longitudinal-mixed options.
Thanks for the comment Koen.
Thanks very much - I agree with your positions and I think we've got some reasonable conclusions out of the results.
G
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