Constructing a spatial hypothesis test
In the introduction to this chapter, we mentioned that the second part of ESDA revolves around testing for spatial structure. Before we begin talking about the methods used, let’s first discuss what we mean by this term. A spatial structure in simplest terms is the presence of a pattern within data across geographic space. Data that has no spatial structure is said to have been generated by an independent random process (IRP). This IRP result is data that exhibits complete spatial randomness (CSR). In other literature, you’ll often see IRP and CSR used interchangeably. IRP/CSR must satisfy two conditions in order to construct a valid hypothesis test:
- Any observation must have an equal probability of occurring in any location. This is known as a first-order effect. As an example, the distribution of an infectious disease will vary across a study area, based on underlying environmental factors.
- The location of an observation...
