I need some help to decide which experimental design should I consider to analyze an experiment with Mahogany (Swietenia macrophylla) regeneration tree. The main objective is to investigate the density of mahogany regeneration around the mother-tree in Amazonia forest. Was selected 20 trees (not randomized trees) and from each tree four oriented-strips (North, South, East, West) was installed with 5 meters x 40 meters long each. Into each plot the number of Mahogany regeneration was counted at sub-plot 5 meter away of each other (5-10; 15-20; 25-30; 35-40). The idea is to investigate if theres a specific orientation where occur more regeneration and until wich distance they reach. To consider the variation between trees I put the DBH into the statistical model as a covariate. Each tree has 16 treatments (four orientation x four distance). I run a Poisson in Glimmix of SAS (I had to sum 1 to each value because SAS was did not converge with zero values!) PROC GLIMMIX DATA=MAHOGANY; CLASS TREE ORIENT DIST; MODEL NREG= ORIENT|DIST / DIST=POISSON LINK=LOG; RANDOM TREE DIST(TREE) ORIENT(TREE); RUN; QUIT; However, I should consider the factor distance (DIST) as an dependent factor. So, I need to consider Spatial Correlation during the analysis. I add the line: RANDOM INTERCEPT / SUBJECT=TREE TYPE=SP(EXP)(DIST); But SAS does not converge! GL,I There is some suggestion for analyzes? Thiago Which experimental design should I follow when analysing Mahogany tree regeneration? - ResearchGate. Available from: https://www.researchgate.net/post/Which_experimental_design_should_I_follow_when_analysing_Mahogany_tree_regeneration#5580135a5cd9e3c4608b45a4 [accessed Jun 18, 2015].
... View more