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  • $\begingroup$ Thanks. This is immensely useful. I have not altered any measurements, initial or otherwise. There is some variation in initial snake weight, range 70-141 grams, but this is minuscule compared to variation at time point 6, 1200-16000 grams. Maybe is why I get minimal variance attributed to individual snakes? I am out of my depth here. It was a randomised trial to test the effect of tagging so snakes were randomly allocated to tag and non-tag groups, but I guess that shouldn't be coming into play here yet as I have not even included tag as a factor in these models yet. $\endgroup$ Commented Sep 18, 2020 at 7:14
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    $\begingroup$ You're welcome. Yes, that is why you get a very small random intercept variance. I assume it's birthweight or very shortly after birth ? In your situation I might be tempted to retain the random intercecpts, centre the time variable at 0 and also consider a nonlinear term (unless you know that growth is linear over the time period in question ?) $\endgroup$ Commented Sep 18, 2020 at 7:31
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    $\begingroup$ It would be good to include a plot of your data $\endgroup$ Commented Sep 18, 2020 at 7:42
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    $\begingroup$ I was thinking about this some more. Although there is very little initial variation relative to final variation, there might be a relation between initial bodyweight and the growth trajectory, that is, there could be correlation between random intercepts and random slopes, but the modelling so far has been unable to detect this. If this sounds plausible in your study, some changes will be necessary. $\endgroup$ Commented Sep 18, 2020 at 9:18
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    $\begingroup$ Yes, fitting birthweight as a fixed effect is a reasonable idea. Cubic splies would be good, although you may want to consider random slopes for the splies too (though don't be surprised if the data doesn't support that). I was thinking you might want to try some kind of transformation to make the earlier readings more spread out (and would then allow random intercepts). You also have increasing variance over time (heteroskedasticity) which can often be fixed with a transformation. $\endgroup$ Commented Sep 20, 2020 at 10:30