Extending Stargazer to multiwaycov

Question

I'm using stargazer to create regression outputs for my bachelor thesis. Due to the structure of my data I have to use clustered models (code below). I'm using the vcovclust command from the multiwaycov package, which works perfectly. However, stargazer does not support it. Do you know another way to create outputs as nice as stargazer does? Or do you know an other package/command to cluster the models, which is suppported by stargazer?

model1.1.2 <- lm(leaflet ~ partisan + as.factor(gender) + age + as.factor(education) + meaning + as.factor(polintrest), data = voxit)
summary(model1.1.2)

#clustering
vcov_clust1.1.2 <- cluster.vcov(model1.1.2, cbind(voxit$id, voxit$projetx))
coeftest(model1.1.2, vcov_clust1.1.2)

Answer 1

You can supply the adjusted p- and se-values to stargazer manually.

# model1 and model2 are both objects returned from coeftest()
# Capture them in an object and extract the ses (2nd column) and ps (4th column) in a list
ses <- list(model1[,2], model2[,2])
ps <- list(model1[,4], model2[,4])

# you can then run your normal stargazer command and supply
# the se- and p-values manually to the stargazer function
stargazer(model1, model2, type = "text", se = ses, p = ps, p.auto = F)

Hope this helps!