Hi Manuel, 

> If I want to compare the metric among the 3 zones, is it the following an
> appropriate model parameterization in lme4?:


It depends on your data and the most sensible grouping structure for your data. 
You could explore different random effect structures and compare them using an 
information criterion approach; however, I think it is more reasonable, before 
allowing the program to make decisions for you, to determine if a temporal 
grouping structure exists in your data and then determine at what scale that is 
present. Plotting the data is always helpful to see this.

Hope this helps.

Best,

> On Jan 19, 2021, at 10:54, Manuel Spínola <[email protected]> wrote:
> 
> Dear list members,
> 
> I have an ecological data set, and I want to account for the
> spatio-temporal structure of my data:
> 
> metric = response variable (continuous)
> zone = 3 zones (A, B and C)
> location = 12 sampling locations per zone
> min = minute
> hour = hour
> day = day
> 
> metric zone location minute hour day
> 2.4         A      1A         1        1     1
> 2.7.        A.     1A         2        1    1
> 
> 1.7.        C      1C.       45       3    5
> 
> 
> If I want to compare the metric among the 3 zones, is it the following an
> appropriate model parameterization in lme4?:
> 
> mod_01 <- lmer(metric ~ zone + (1 | location) + (1 | day/hour/min), data =
> my_data)
> 
> Thank you very much in advance.
> 
> Manuel
> 
> -- 
> *Manuel Spínola, Ph.D.*
> Instituto Internacional en Conservación y Manejo de Vida Silvestre
> Universidad Nacional
> Apartado 1350-3000
> Heredia
> COSTA RICA
> [email protected] <[email protected]>
> [email protected]
> Teléfono: (506) 8706 - 4662
> Personal website: Lobito de río <https://sites.google.com/site/lobitoderio/>
> Institutional website: ICOMVIS <http://www.icomvis.una.ac.cr/>
> 
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