Hello all, First question I have posted, so please let me know if addition information is needed beyond that provided below: I am looking at a dataset of fish density values, recorded over 3 years at 3 different locations. These density values are obtained during surveys that are composed of multiple transect lines at a single site Transect "curtains" are further divided into grids (distance x depth), of which each cell is assigned a density and coordinate Additional parameters (Bottom habitat, salinity, temperature, etc) are assigned to the cells The density values have a very very skewed distribution (many small, few very large), hence the use of GLIMMIX to attempt to address this. I am interested in the effects of these "additional parameters" on density, though I cannot ignore the spatial nature of the data (fish group together, nearby cells will tend to have more similar densities). I am assuming that spatial correlations would only exist within a single survey. My model currently looks like this: proc glimmix data=Data.BankPresent pconv =1e-5 maxopt=30; class Site Habitat Season Survey; model Density= Relief DShallow MeanSalinity MeanTemp Site|Habitat|Season / dist=gamma link=log; random Survey / subject=intercept type=sp(exp) (Easting Northing); run; I am unsure of where to put the spatial autocorrelation component [type=sp(exp) (Easting Northing)], or if this model is doing what I have attempted to describe above. If needed/of interest, the variables included are: Relief: continuous, vertical relief of the seafloor below cell i DShallow: continuous, distance from cell i to the shallowest point at the site MeanSalinity: continuous, salinity of cell i MeanTemp: continuous, temperature of cell i Site: categorical, site at which the survey was conducted (1,2,3) Habitat: categorical, habitat classification of seafloor below cell i (1,2,3,4,5) Season: categorical, season in which the survey was conducted (1,2,3,4) To reiterate, I want to run the above model with a consideration for spatial autocorrelation on a survey-by-survey basis. Thank you for any information you may be able to provide, applicable references, or questions of clarification.
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