Sundar Dorai-Raj writes: > Hi, Laura, > > Would ?predict.glm be better? > > plot(logarea, hempresence, > xlab = "Surface area of log (m2)", > ylab="Probability of hemlock seedling presence", > type="n", font.lab=2, cex.lab=1.5, axes=TRUE) > lines(logarea, predict(hemhem, logreg, "response"), lty=1, lwd=2) > lines(logarea, predict(hemyb, logreg, "response"), lty="dashed", lwd=2) > lines(logarea, predict(hemsm, logreg, "response"), lty="dotted", lwd=2) > > Without seeing more description of your data, this is still a guess. > > --sundar >
YES! Thank you. That solves all of the problems I was having. Thanks also to Tom Mulholland and Bill Venables for their replies. Laura The final code is now: logreg <- read.table("C:/Documents and Settings/Laura/Desktop/logreg.txt", header=TRUE, sep=",", na.strings="NA", dec=".", strip.white=TRUE) #This is the full dataset. A hemlock row followed by a birch row might look #like: #Hemybsm logarea hempresence #1 0.054 0 #2 1.370 1 hemhem=glm(hempresence~logarea, family=binomial(logit), subset=Hemybsm<2) #This pulls out only the hemlocks from the full dataset and calculates the #regression. hemyb=glm(hempresence~logarea, family=binomial(logit), subset=Hemybsm==2) #Same code, with only the birches from the full dataset. hemsm=glm(hempresence~logarea, family=binomial(logit), subset=Hemybsm>2) plot(logarea, hempresence, xlab = "Surface area of log (m2)", ylab="Probability of hemlock seedling presence", type="n", font.lab=2, cex.lab=1.5, axes=TRUE) lines(logarea, predict(hemhem, logreg, "response"), lty=1, lwd=2) lines(logarea, predict(hemyb, logreg, "response"), lty="dashed", lwd=2) lines(logarea, predict(hemsm, logreg, "response"), lty="dotted", lwd=2) ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html