[R] country fixed effects model with binary dependent variable

Cristina Cametti cristina.cametti at gmail.com
Sun Jul 24 11:18:46 CEST 2016


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 <drjimlemon at 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.cametti at 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
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