SAS Code: Estimating probabilities of detecting submersed aquatic vegetation species using a rake method may vary with biomass

The code files were used to analyze data used with the publication, "Probabilities of detecting submersed aquatic vegetation species using a rake method may vary with biomass," by Brian Gray. The study explored whether probabilities of species detections for four submerged aquatic vegetation species varied among sampling units in a rake-biomass study and, if so, whether such variation reflected variation in species abundance. Variation in detection probabilities, when unaddressed, yielded biased estimators of percent frequency of occurrence and of occurrence-habitat associations. The study found substantial among-unit variation in detection probabilities, and that majorities of that variation on the logit or modeling scale were associated [...]