I've collected environmental data on the dust level using direct-reading instruments. The outputs from the instruments are concentrations recorded at each minute over 1 hour. The data collected at many locations and locations are grouped into Groups and Department. The data looks like this in wide format
Depart1 Group1 Location1: 3, 3, 4, 3.5, 4, 6, etc... Depart1 Group1 Location2: 2, 7,5, 6, 3, 5, 5, etc.. Depart2 Group2 Location3: 8, 4, 3, 6, 6, 3, 6, etc..
I want to find the within and between variability among the Groups. But for some groups, I have data at 3 locations per group and sometimes I only have data at 1 location per group. Thus, I have uneven datasets for Groups.
I am wondering what is the best statistical model to answer the variability question. I've looked up ANOVA for repeated measurements but how do you deal with the uneven grouping?
Would a linear mixed model with time being considered as a fixed effect and Group and Location being random effects work here? At the end, I am only interested in within and between variability for the Group not the Location.