I am a newbie in meta-analysis and I need your opinion on the design of my random-effect model.
I have conducted an experiment on the performance of a provider who has around 30-40 data centres. I picked two such data centres at random and monitored their performance for 7 consecutive weekdays. I took 2 measurements per day (1 during the peak and 1 during the off-peak). Now I have three factors in my experiment design: data centres, day and time having 2, 7 and 2 levels respectively. I want to know how much each of these factors contribute to the variance in performance. I have the following nested model in my mind:
m1 <- lme(Performance ~ 1, random =~ 1|DataCentre/Day/Time, data=mydata)
I am pretty sure that the time factor is nested within day; however, not quite sure whether the data centre should be a part of the nested structure. I assume that each data centre may have its own pattern of variability across different days, that's why included it in the nested structure.
Do you think this model is correct? Is there any other approach that you can suggest?