rpr: Cluster and Subcluster effects
In rlme: Rank-Based Estimation and Prediction in Random Effects Nested Models

Description Usage Arguments Value Author(s) References See Also Examples

Partitions model residuals into cluster and subcluster effects using RPP algorithm.

1	rpr(f, resd, data, rprpair = "hl-disp")

`f`	A model formula which specifices the random effects (see example)
`resd`	The residuals from the fitted model
`data`	The data the model was fitted on
`rprpair`	Character string indicating the location and scale parameters to use. Default to "hl-disp", but may also be "med-mad". See Bilgic (2012).

`siga2`	Variance from cluster
`sigw2`	Variance from subcluster
`sigmae2`	Remaining variance not accounted for by variance of cluster and subcluster

J. W. McKean and Y. K. Bilgic

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

rprmeddis, dispvar

# Load school data
data(schools)

# Fit fixed effects model with lmr
lmr.fit = lmr(y ~ age + sex, data=schools)

# Three level design
# Partition residuals into school and region effects with rpp algorithm
rpr(y ~ age + sex + (1 | school) + (1 | school:region), lmr.fit$ehat, schools)

# Two level design
# Estimate variance in residuals from school
rpr(y ~ age + sex + (1 | school), lmr.fit$ehat, schools)