Instead of running a multiple regression model (one dependent variable, and several independent variables) why not just run several simple linear regression models (slrm) instead, as slrm are easy to understand, right? For example, disease rate (Y) depends on healthcare funding (X1), and also depends on other things like number of visits to a healthcare provider(X2). So instead of regression Y and X1 and X2 (mlrm), why not run 2 slrm, Y on X1, and Y on X2?
Here I explain why this is likely to give you misleading results.
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https://www.youtube.com/watch?v=1wVisQ12KdE