Autologistic models with interpretable parameters
Author(s): Caragea, P.C., Kaiser, M.S.
Journal of the Agricultural, Biological, and Environmental Statistics, 14 (3): 281-300, 2009

Abstract:
Ecologists are interested in characterizing succession processes, in particular monitoring the spread of invasive species and their effect on resident species. In situations for which binary response variables representing presence or absence of plants are observed over a spatial lattice, it may be desirable to use a model that accounts for the statistical dependence in the data, as well as the effect of potential covariates. One such model is the autologistic regression model. We show that the typical parametrization of the autologistic model presents difficulties in interpreting model parameters across varying levels of statistical dependence, and propose an alternative (centered) parametrization that overcomes this difficulty. We use the centered autologistic model to study the dynamics over time of two species, Rumex Acetosella and Lonicera Japonica in an abandoned agricultural field in New Jersey, and compare the results to those obtained from using the traditional autologistic parametrization.

Keywords:
binary response; conditionally specified models; large-scale, small-scale model structure; Old field succession; parameter interpretation; spatial models.

Link to article in the Journal of the Agricultural, Biological, and Environmental Statistics