  Newly available point-level datasets allow us to relate police use of force
to other events describing police behavior. Current methods for relating two
point processes typically rely on the spatial aggregation of one of the two
point processes. We investigate new methods that build upon shared component
models and case-control methods to retain the point-level nature of both point
processes while characterizing the relationship between them. We find that the
shared component approach is particularly useful in flexibly relating two point
processes, and we illustrate this flexibility in simulated examples and an
application to Chicago policing data.
