rlme (version 0.5)

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

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.

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

# NOT RUN {
# See the rlme function.

# }