Rfast2: cluster.lm – R documentation

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cluster.lm

Linear regression with clustered data

Linear regression with clustered data.

cluster.lm(y, x, id)

`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.

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

A list including:

`be`	The (beta) regression coefficients.
`becov`	Robust covariance matrix of the regression coefficients.
`seb`	Robust standard errors of the regression coefficients.

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr>

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

A Collection of Efficient and Extremely Fast R Functions II

v0.0.9

GPL (>= 2.0)

Authors

Manos Papadakis, Michail Tsagris, Stefanos Fafalios and Marios Dimitriadis.

Initial release

2021-03-21