mkReTrms {lme4}  R Documentation 
From the result of findbars
applied to a model formula
and the evaluation frame fr
, create the model matrix
Zt
, etc, associated with the randomeffects terms.
mkReTrms(bars, fr, drop.unused.levels=TRUE,
reorder.terms=TRUE,
reorder.vars=FALSE)
mkNewReTrms(object, newdata, re.form=NULL,
na.action=na.pass,
allow.new.levels=FALSE,
sparse = max(lengths(orig.random.levs)) > 100)
bars 
a list of parsed randomeffects terms 
fr 
a model frame in which to evaluate these terms 
drop.unused.levels 
(logical) drop unused factor levels? 
reorder.terms 
arrange random effects terms in decreasing order of number of groups (factor levels)? 
reorder.vars 
arrange columns of individual random effects terms in alphabetical order? 
object 
a fitted 
newdata 
data frame for which to create new RE terms object 
re.form 
(formula, 
na.action 
function determining what should be done
with missing values for fixed effects in 
allow.new.levels 
(logical) if new levels (or NA values) in

sparse 
generate sparse contrast matrices? 
a list
with components
Zt 
transpose of the sparse model matrix for the random effects 
theta 
initial values of the covariance parameters 
Lind 
an integer vector of indices determining the mapping of
the elements of the 
Gp 
a vector indexing the association of
elements of the conditional mode vector
with randomeffect terms; if 
lower 
lower bounds on the covariance parameters 
Lambdat 
transpose of the sparse relative covariance factor 
flist 
list of grouping factors used in the randomeffects terms 
cnms 
a list of column names of the random effects according to the grouping factors 
Ztlist 
list of components of the transpose of the randomeffects model matrix, separated by randomeffects term 
nl 
names of the terms (in the same order as 
mkNewReTrms
is used in the context of prediction, to
generate a new "random effects terms" object from an already fitted
model
Other utilities: findbars
,
mkRespMod
, nlformula
,
nobars
, subbars
.
getME
can retrieve these components
from a fitted model, although their values and/or forms
may be slightly different in the final fitted model from
their original values as returned from mkReTrms
.
data("Pixel", package="nlme")
mform < pixel ~ day + I(day^2) + (day  Dog) + (1  Side/Dog)
(bar.f < findbars(mform)) # list with 3 terms
mf < model.frame(subbars(mform),data=Pixel)
rt < mkReTrms(bar.f,mf)
names(rt)