Hello, I have 1-year ACS micro-level data for two separate years for Texas (e.g., 2005 and 2010) with puma and poverty (outcome variable) and some other variables. Can data be aggregated at the puma level (e.g., puma population) while also including/leaving the individual-level variables in the same data while applying the survey design, for instance, to perform logistic regression? I’m trying to calculate more complex variables at the puma level, but providing the simplest of examples can help me get an idea of whether it is doable.
I use R, and have searched and cannot seem to find examples of how to do this. Aggregated data are used for descriptive information or for maps of ratios, but I cannot locate a logistic regression example that combines both individual and aggregated data (e.g., at the puma level). I’ve tried doing this with the srvyr and survey packages but to no avail.
Thank you in advance for pointing me toward possible solutions.