[R] country fixed effects model with binary dependent variable

[David Winsemius]

> On Jul 23, 2016, at 7:49 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,

That is the most <bite-my-tongue> <deleted> preamble I have ever seen. How can it not be important how you constructed your covariates?   .... ?????

> they are from the first wave of the ESS survey. At this point, I have three questions: 
> - do you think this code is correct?

Really? First you ask us not to question your construction of covariates, and ... THEN ask us if it 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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David Winsemius
Alameda, CA, USA