How can I omit several groups of covariates from the regression table and replace them with the group labels in stargazer? For example, if under city controls there is size and population, and under individual controls there is age and gender, how can I omit size, population, age, and gender and instead have something like city controls in the model?: no yes and individual controls in the model?: no yes.
By the way, all covariates from the same group would join or leave the model together.
Please provide a minimal example. Perhaps you are looking for something like this:
data("Produc", package="plm")
Produc$cat <- cut(Produc$gsp,
breaks=quantile(Produc$gsp),
labels=c('Bad', 'OK', 'Good', 'Great'))
fe <- plm(pcap ~ hwy + water + unemp + cat,
data=Produc, index=c("state", "year"), model = "within")
stargazer(fe, type="text")
========================================
Dependent variable:
---------------------------
pcap
----------------------------------------
hwy 2.025***
(0.054)
water 1.976***
(0.043)
unemp -17.644
(19.716)
catOK 462.982*
(269.838)
catGood 679.697**
(329.131)
catGreat 430.046
(388.285)
----------------------------------------
Observations 815
R2 0.902
Adjusted R2 0.895
F Statistic 1,170.861*** (df = 6; 761)
========================================
Note: *p<0.1; **p<0.05; ***p<0.01
Use the option omit to omit certain variables. And option add.lines to add any note you like.
stargazer(fe, type="text", omit = "cat")
stargazer(fe, type="text", omit = "cat",
add.lines=list(c("Cats", "YES")))
========================================
Dependent variable:
---------------------------
pcap
----------------------------------------
hwy 2.025***
(0.054)
water 1.976***
(0.043)
unemp -17.644
(19.716)
----------------------------------------
Cats YES
Observations 815
R2 0.902
Adjusted R2 0.895
F Statistic 1,170.861*** (df = 6; 761)
========================================
Note: *p<0.1; **p<0.05; ***p<0.01