GEER_est {rlme} | R Documentation |
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. |
Author(s)
Yusuf K. Bilgic, yekabe@hotmail.com
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.