search for: mymod1

...nts describing the difficulties that we have found. Are there simpler, less frustrating approaches? ----------------------------- # Paul Johnson <pauljohn at ku.edu> 2005-11-17 # factorFutzing-1.R myfac <- factor(c(1.1, 4.5, 1.1, 1.1, 4.5, 1.1, 4.5, 1.1)) y <- c(0,1,0,1,0,0,1,0) mymod1 <-glm (y~myfac, family=binomial) p1 <- predict(mymod1, type="response") plot(myfac,p1) # Wait, that's not the picture I wanted. I want to see the # proverbial S-shaped curve! # # The contrast variable that R creates is coded 0 and 1. # I'd like to have a sequence from 0...

...2005 2005 2005 2006 2006 ... $ stop : num 2006 2006 2006 2007 2007 ... $ risk : num 1 2 3 1 2 3 1 2 3 1 ... $ evstatus: num 0 0 0 0 0 0 0 0 0 0 ... I am modelling the survival time until the adoption of the policy as follows: mod1<-Surv(newdat$start, newdat$stop, newdat$evstatus) mymod1<-coxph(mod1 ~ news + enviro + partisan + cluster(state) + strata(evstatus), method=c("efron"), robust=TRUE) Again, following Fox, I try to construct a data frame with a hypothetical covariate profile: n<-data.frame(news=rep(c(1,4,8)), evstatus=as.factor(1:3), enviro=mean(newdat$en...

Dear listers, I am trying to fit a model using nlsList() using alternately a SSfol() selfstart function or its developped equivalent formulae. This preliminary trial works well mydata<-groupedData(Conc~Tps|Organ,data=mydata) mymod1<-nls(Conc~SSfol(Dose,Tps,lKe,lKa,lCl),data=mydata) as well as a developped form: mymod2<-nls(Conc~Dose * exp(lKe+lKa-lCl) * (exp(-exp(lKe)*Tps)-exp(-exp(lKa)*Tps)) /(exp(lKa)-exp(lKe)), data=mydata, start= c(lKe=-2.77, lKa=-1.41, lCl=-1.13) ) However when trying to fit the mod...