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rstargazerpanderbayesglm

Regression table for bayesglm?

stargazer is a great tool to generate a regression table if you are not using bayesglm. For example, suppose I have the following data:

library(dplyr)
set.seed(9782)
N<-1000
df1 <- data.frame(v1=sample(c(0,1),N,replace = T),
                  v2=sample(c(0,1),N,replace = T),
                  Treatment=sample(c("A", "B", "C"), N, replace = T),
                  noise=rnorm(N)) %>% 
  mutate(Y=0.5*v1-0.7*v2+2*I(Treatment=="B")+3*I(Treatment=="C")+noise)

I can run lm and then create html (or text) output for my r markdown:

lm(data = df1, formula = Y~Treatment+v1+v2) %>% 
  stargazer::stargazer(type="html", style = "qje")

Is there a way to do something similar for bayesglm? In this case, pointEstimate has the coefficients and standardError the standard errors

library(arm)
fit <- bayesglm(data = df1, formula = Y~Treatment+v1+v2)
posteriorDraws <- coef(sim(fit, n.sims=5000))
pointEstimate <- colMeans(posteriorDraws)
standardError <- apply(posteriorDraws, 2, sd)
Solution

  • It looks like this does the trick:

    library(texreg)
htmlreg(fit)

    and for text:

    screenreg(list(fit))