Too Close for Comfort? Assessing Spatial Dependence in Geographic Data with Spatial Regression

Psychologists are increasing relying on geographic data to test theories. Using traditional linear models with geographic units is problematic because the data are spatially dependent; they produce non-independent residuals, thus violating assumptions. The present work shows researchers how to code for, assess, and control for spatial dependence using spatial regression.