Dear all, thank you very much for all your answers. Probably, I don’t know how to write in this mailing list, so I apologize if I was not clear. My questions were all code related: I am not an R user, this means that I started using R just few months ago. So, I am seeking advise about the coding and that is why I was writing here. The part about not to mind how I wrote the variables meant only that the names may appear weird because I used the same in the ESS survey and in other cases, I created new names that do not make sense. So it was just a simple suggestions about my way to write the name of the variables, because the focus of my questions were others. So, I am sorry if I upset you and basically, all wrote by Jim was correct about my questions. So thank you Jim, in the meantime I was working on the code and in the end I came up with the same code as you. I used “glm” and added “family=binomial”. So now that I have the confirmation from an expert that this is a reliable code for my analysis, I am more sure about my results.
Thank you all again for your attention. Kind Regards, Cristina Il giorno 24/lug/2016, alle ore 06:50, Jim Lemon <drjimle...@gmail.com> ha scritto: > Hi Cristina, > As Rolf has noted, you probably don't want to persist with "lm" since > I think you have dichotomized your initial dependent variable. I also > think that you meant "don't worry about the change of variable names" > with "how I wrote the variables". I also think that you want to test > interactions between the variables you are adding. _Maybe_ something > like this: > > modelfe1.2<-glm(aesfdrk_dummy ~ agea + gndr + eduyrs + domicil + > partner + tvpol + hincfel_dum + ppltrst_GM:prison_pop + > ppltrst_GM:foreign_pop_ + victim*prison_pop_ + victim*foreign_pop + > mixed_neigh*prison_pop + mixed_neigh*foreign_pop + > ethnic_neigh*prison_pop + ethnic_neigh*foreign_pop + factor(cntry)-1, > data=mydata, family="binomial") > > Jim > > > On Sun, Jul 24, 2016 at 12:49 AM, Cristina Cametti > <cristina.came...@gmail.com> wrote: >> Dear all, >> >> I am having problems finding a reliable code for a country fixed effects >> model with binary dependent variable. I was able to run it for another part >> of my research, because in that case the dependent variable is continuous. >> This is my code for the continuous dependent variable “imwbcrm_rec”: >> >> modelfe2 <- lm(imwbcrm_rec ~ tvpol + victim + agea + gndr + eduyrs + >> lrscale_GM + imgfrnd_dum + qfimwht +factor(cntry)-1, data=mydata) >> >> Please don’t mind to how I wrote the variables, they are from the first wave >> of the ESS survey. At this point, I have three questions: >> - do you think this code is correct? Since the data are all from the same >> year (2002), I did not used the ppm package since it is only for panel data. >> The results of the previous code make sense, so I am satisfied. However, I >> want to be sure that I am running the right code. >> - second questions: someone knows the code for the same analysis, but having >> a BINARY dependent variable (aesfdrk_dummy)? I found very different >> information on the internet, and unfortunately, I do not know how to use >> STATA, so I need to find a reliable code in r. This is the code that I have >> now: >> >> modelfe1 <-lm(aesfdrk_dummy ~mixed_neigh + ethnic_neigh + agea+ gndr + >> eduyrs + domicil + partner + tvpol + hincfel_dum + factor(cntry) -1, >> data=mydata) >> >> -last question: I have to add some interaction between country level >> variables and individual level variables. So, do you think that this code is >> right? >> >> mydata$ppltrst_GMXprison_pop <- mydata$ppltrst_GM*mydata$prison_pop >> mydata$ppltrst_GMXforeign_pop <- mydata$ppltrst_GM*mydata$foreign_pop >> mydata$victimXprison_pop<- mydata$victim*mydata$prison_pop >> mydata$victimXforeign_pop<- mydata$victim*mydata$foreign_pop >> mydata$mixed_neighXprison_pop<- mydata$mixed_neigh*mydata$prison_pop >> mydata$mixed_neighXforeign_pop <- mydata$mixed_neigh*mydata$foreign_pop >> mydata$ethnic_neighXprison_pop <- mydata$ethnic_neigh*mydata$prison_pop >> mydata$ethnic_neighXforeign_pop <- mydata$ethnic_neigh*mydata$foreign_pop >> >> modelfe1.2<-lm(aesfdrk_dummy ~mixed_neigh + ethnic_neigh + agea + gndr + >> eduyrs + domicil + partner + tvpol + hincfel_dum + victim + ppltrst + >> ppltrstXprison_pop + ppltrst_Xforeign_pop_ + victimXprison_pop_ + >> victimXforeign_pop + mixed_neighXprison_pop + mixed_neighXforeign_pop + >> ethnic_neighXprison_pop + ethnic_neighXforeign_pop + factor(cntry)-1, >> data=mydata) >> >> >> Thank you very much for your attention. >> Kind Regards, >> >> Cristina >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> 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. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
