logistric regression: model revision
On Nov 7, 2011, at 10:58 AM, Sally Ann Sims wrote:
Hello, I am working on fitting a logistic regression model to my dataset. I removed the squared term in the second version of the model, but my model output is exactly the same. Model version 1: GRP_GLM<-glm(HB_NHB~elev +costdis1^2,data=glm_1,family=binomial(link=logit)) summary(GRP_GLM) Model version 2: QM_1<-glm(HB_NHB~elev +costdis1,data=glm_2,family=binomial(link=logit)) summary(QM_1) The call in version 2 has changed: Call: glm(formula = HB_NHB ~ elev + costdis1, family = binomial(link = logit), data = glm_2) But I???m getting the exact same results as I did in the model where costdis1 is squared.
Are you sure that you got output that correctly modeled the costdis1^2? I would ahve guessed that you would have needed to use : GRP_GLM<-glm(HB_NHB~elev+I(costdis1^2), data=glm_1, family=binomial(link=logit)) ?I The "^" in model formulas is for composing interactions. ?formula
Any ideas what I might do to correct this? Thank you. Sally [[alternative HTML version deleted]]
And please post in plain text.
David Winsemius, MD West Hartford, CT