I have a data set that consists of different characteristics of communities. What I want to do is to see how those characteristics influence each other. As in, for example I have the income and population and other demographic data for a community, and also the level of access to some different services and I want to determine the access level to those services for the communities. I want to create a model of those communities, like what kind of factors are influencing the community access to a service - high income, high population density, education etc.
I have performed Principal Component Analysis on the data set and I've obtained the score and loading plots (the correlation between the principal components and the initial variables). What could I do next in my analysis using those? I was thinking about regression, but I am not sure exactly how to use the data from the PCA in the regression analysis.