lm_cluster: Fitting Linear Models with Clustered Errors

In leesh0222/sanghoon:

Fitting Linear Models with Clustered Errors

Description

This function calculates standard errors with clustered erros and add them to the linear model fit object with a named vector "se_cluster". This vector can be used in stargazer.

Usage

lm_cluster(data, formula, cluster, ...)

Examples

## Petersen's data
data("PetersenCL", package = "sandwich")
m <- lm(y ~ x, data = PetersenCL)

## clustered covariances
m1 <- lm_cluster(y ~ x, data = PetersenCL, cluster=firm)
summary(m1)
m1$se_cluster
m1$vcov_cluster

stargazer(m, m1, se=list(NULL, m1$se_cluster))

leesh0222/sanghoon documentation built on April 3, 2022, 1:24 a.m.