Spatially explicit structural equation modeling
Description
Structural equation modeling (SEM) is a powerful statistical
approach for the testing of networks of direct and indirect theoretical
causal relationships in complex datasets with intercorrelated dependent and
independent variables. Here we implement a simple method for spatially
explicit SEM (SE-SEM) based on the analysis of variance covariance matrices
calculated across a range of lag distances. This method provides readily
interpretable plots of the change in path coefficients across scale.