[R] country fixed effects model with binary dependent variable

Jim Lemon
Sun, 24 Jul 2016 04:50:30 -0000

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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