Let's work through a concrete (if somewhat impractical) example:
I'm a medical researcher who has reason to investigate a possible trend in a dataset of tissue samples from the human lung and human brain. We are interested in the number of viral cells of type A found in these tissue samples (measured as a discrete count).
The dataset could look something like this:
patientA_brain_virus_counts patientA_lung_virus_counts age brain_tissue_total_cells lung_tissue_total_cells gender ethnicity 239 5783 67 139218 1323494 M A 2313 3528 72 225815 2328554 F A 15 356 38 535291 5341823 F O 4829 13458 81 371234 3351732 F T
The trend noticed within the data is that there is a greater proportion of
brain_virus_counts. However, I need to model this in order to quantify this effect.
How does one model two dependent variables in this fashion? If there was one dependent variable, I would use something like a Poisson GLM model.
Are there statistical packages (e.g. in R) which allows one to perform this?