GEER_est: GEER: General Estimating Equation Rank-Based Estimation...

In rlme: Rank-Based Estimation and Prediction in Random Effects Nested Models

Description

The package rlme calls this function for gee method, one of the methods proposed in Bilgic's study (2012). Also see Kloke et al. (2013). concise (1-5 lines) description of what the function does. ~~

Usage

GEER_est(x, y, I, sec, mat, school, section, weight = "wil",
  rprpair = "hl-disp", verbose = FALSE)

Arguments

x	Design matrix, pxn, without intercept.
y	Response vector of nx1.
I	Number of clusters.
sec	A vector of subcluster numbers in clusters.
mat	A matrix of numbers of observations in subclusters. Dimension is Ixmax(number ofsubclusters). Each row indicates one cluster.
school	A vector of clusters, nx1.
section	A vector of subclusters, nx1.
weight	When weight="hbr", it uses hbr weights in GEE weights. By default, ="wil", it uses Wilcoxon weights. See the theory in the references.
rprpair	By default, it uses "hl-disp" in the random prediction procedure (RPP). Also, "med-mad" would be an alternative.
verbose	Boolean indicating whether to print out diagnostic messages.

Value

theta	Fixed effect estimates.
ses	Standard error for the fixed esimates.
sigma	Variances of cluster, subcluster, and residual.
ehat	Raw error.
ehats	Independence error from last weighted step.
effect_sch	Cluster random error.
effect_sec	Subcluster random error.
effect_err	Epsilon error.

Author(s)

Yusuf K. Bilgic, [e-mail]

References

Y. K. Bilgic. Rank-based estimation and prediction for mixed effects models in nested designs. 2012. URL http://scholarworks.wmich.edu/dissertations/40. Dissertation.

A. Abebe, J. W. McKean, J. D. Kloke and Y. K. Bilgic. Iterated reweighted rank-based estimates for gee models. 2013. Submitted.

See Also

rlme, GR_est, JR_est, rprmeddisp

Examples

# See the rlme function.

rlme documentation built on May 2, 2019, 3:47 p.m.