[R-sig-ME] Multi-level models for nested variables in time dimension

Vitor Vieira Vasconcelos v|tor@v@v @end|ng |rom gm@||@com
Sat Nov 20 01:21:31 CET 2021

Good night, friends!

     I have been seeing many multi-level models, using the mixed models'
framework, that use groups nested in "space", such as students nested in
classes, which are nested in schools, and with independent variables for
each of these spatial resolutions.
    Then I was thinking whether we could use this same framework to model
variables nested in the time dimension. For example, if we have some
variables sampled at daily resolution, other variables at monthly
resolution and others at year resolution, and we would like to use all them
in the same model to predict a dependent variable at daily resolution.
   Basically, I am just thinking about transposing the same framework from
"space" dimension to "time" dimension, and not thinking yet about
autocorrelation or other time-series analyses.
    Do you think that these ideas make sense to you?

Best regards,
Vitor Vieira Vasconcelos

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