Linear regression with clustered data {Rfast2}

Linear regression with clustered data

Description

Linear regression with clustered data.

Usage

cluster.lm(y, x, id) 

Arguments

y

The dependent variable, a numerical vector with numbers.

x

A matrix or a data.frame with the indendent variables.

id

A numerical variable with 1, 2, ... indicating the subject. Unbalanced design is of course welcome.

Details

A linear regression model for clustered data is fitted. For more information see Chapter 4.21 of Hansen (2019).

Value

A list including:

be

The (beta) regression coefficients.

becov

Robust covariance matrix of the regression coefficients.

seb

Robust standard errors of the regression coefficients.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Hansen, B. E. (2022). Econometrics.

See Also

gee.reg, fe.lmfit, wild.boot

Examples

y <- rnorm(200)
id <- sample(1:20, 200, replace = TRUE)
x <- rnorm(200, 3)
cluster.lm(y, x, id)