Hello, I am having some trouble running a very simple example. I am running a logistic regression entering the SAME data set in two different forms and getting different values for the deviance residual.
Just look with this naive data set: ================================================================ # 1- Entering as a Bernoulli data set y<-c(1,0,1,1,0) x<-c(2,2,5,5,8) ajust1<-glm(y~x,family=binomial(link="logit")) ajust1 # Coefficients: (Intercept) x 1.3107 -0.2017 Degrees of Freedom: 4 Total (i.e. Null); 3 Residual Null Deviance: 6.73 Residual Deviance: 6.491 AIC: 10.49 # # 2- Entering as Binomial data set # ysim<-c(1,2,0) ynao<-c(1,0,1) x<-c(2,5,8) dados<-cbind(ysim,ynao,x) dados<-as.data.frame(dados) attach(dados) ajust2<-glm(as.matrix(dados[,c(1,2)])~x,family=binomial, data=dados) summary(ajust2) # Coefficients: (Intercept) x 1.3107 -0.2017 Degrees of Freedom: 2 Total (i.e. Null); 1 Residual Null Deviance: 3.958 Residual Deviance: 3.718 AIC: 9.104 ================================================================= It seems that there is problem with the first fitting!!! Best Enrico Colosimo Dept Statistics, UFMG Brazil ______________________________________________ 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.
