Hi Steve, Thanks so much again for your time and thoughts. I can see what you mean about the county random effect, however, I may have been a bit misleading with the SAS programme that I pasted into my first post. The 'county' variable is actually the incidence rate in the county in the previous year, it is a categorical variable with 5 categories (since it was non-linear) and the herd (which is my actual unit of measurement) is allocated to a category depending on the county incidence in the previous year. I have tried your suggestion of using the actual county as a random effect, however, the model will not run because of insufficient memory (I have a v large processor so I hardly ever have memory problems!). I have also run my original model for 2 subsets, the first is all counties where incidence decreased between the two years and the second are all the counties where incidence increased. For both of these models the covtest was not significant. Therefore, the only time I get a significant difference is at the national level (all counties and all herds are included in my dataset). These results lead me to think that there may be a power problem. However, my 2 subsets are quite large (>400 testers) so maybe I should just accept that heterogeneous variation is only observed at the national level and possibly then conclude that in general there has been an improvement in consistency of testers (ie reduced variation in the latter year) at the national level, however, these results can not be generalised to smaller populations? Thanks once again for your help, it really is appreciated and I have the book you suggested on order so hopefully that will also help!
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