Rfast2: gee.reg – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

gee.reg

GEE Gaussian regression

GEE Gaussian regression.

gee.reg(y, x, id, tol = 1e-07, maxiters = 100)

`y`	The dependent variable, a numerical vector.
`x`	A matrix with the indendent variables.
`id`	A numerical variable with 1, 2, ... indicating the subject. Unbalanced design is of course welcome.
`tol`	The tolerance value to terminate the Newton-Raphson algorithm. This is set to 10^{-7} by default.
`maxiters`	The maximum number of iterations that can take place during the fitting.

Gaussin GEE regression is fitted.

A list including:

`be`	The regression coefficients.
`seb`	The standard errors of the regression coefficients.
`phi`	The φ parameter.
`a`	The α parameter.
`covbeta`	The covariance matrix of the regression coefficients.
`iters`	The number of iteration the Newton-Raphson required.

Michail Tsagris

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

Wang M. (2014). Generalized estimating equations in longitudinal data analysis: a review and recent developments. Advances in Statistics, 2014.

Hardin J. W. and Hilbe J. M. (2002). Generalized estimating equations. Chapman and Hall/CRC.

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