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tlyons · ‎12-26-2016

I think in this case I can assume that they're not systematically different. The data are sort of a maximum number of unique small mammals trapped during each survey. In this case, we know individuals trapped early in the year show up in surveys later in the year, and that fall abundances ought to be larger than spring abundances because there is the potential for multiple litters. For this reason, I know there is covariance among the two samples within a year and and I am just searching for a way to model that out, in addition to the covariance associated with returning to the exact same plots year after year.

tlyons · ‎12-24-2016

I don't think so, they're repeated measurements of the same sample unit. But I'm open to it if you can explain why.

tlyons · ‎12-24-2016

I'm trying to run an analysis in glimmix of some ecological data thats throwing me for a loop, but I'm probabaly overthinking it. The data were collected over 4 years, at 4 blocks where each block contained 1 of 4 different vegetative types. Because the same plots were visited each year, I know I can account for potential covaraince at this level using a random effect of study plot or as a repeated measure using one of the following random int/ subject=plot; OR random year/ subject=plot; However, these plots were also visited twice within a given year. How do I account for this second level of repeated-ness? Is it just as simple as : random visit/ subject=plot*yr? and can this kind of statement be combined with one of the above?

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Re: Multiple repeated measures glimmix

Re: Multiple repeated measures glimmix

Multiple repeated measures glimmix

Re: Multiple repeated measures glimmix

Re: Multiple repeated measures glimmix

Multiple repeated measures glimmix