Hi R-people, I performed controlled experiments to evaluated the seeds germination of two palms under four levels of water treatments. I conducted a generalized linear model (GLM) with a Poisson distribution to verify whether there were significant differences in the number of seed germination (NS-count variable) between treatments and species (explanatory variables). Thus, my model and output were:
model1<-glm(NS~Treatments*Species, family="poisson") Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 2.56247 0.57544 4.453 8.46e-06 *** Treatments -2.07267 0.35065 -5.911 3.40e-09 *** Species -0.00312 0.30527 -0.010 0.992 Treatments:Species 0.90397 0.17896 5.051 4.39e-07 *** Null deviance: 379.870 on 98 degrees of freedom Residual deviance: 68.302 on 95 degrees of freedom There is a significant interaction between treatments:species. Which is the post hoc test appropriate for this model? Thanks, Maria Isabel [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.