gee.reg: GEE Gaussian regression

In Rfast2: A Collection of Efficient and Extremely Fast R Functions II

GEE Gaussian regression

Description

GEE Gaussian regression.

Usage

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

Arguments

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.

Details

Gaussin GEE regression is fitted.

Value

A list including:

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

Author(s)

Michail Tsagris.

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

References

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.

See Also

cluster.lm, fe.lmfit, wild.boot, fipois.reg

Examples

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

Rfast2 documentation built on Aug. 8, 2023, 1:11 a.m.