predict.merMod {lme4} | R Documentation |
The predict
method for merMod
objects, i.e. results of lmer()
, glmer()
, etc.
## S3 method for class 'merMod' predict(object, newdata = NULL, newparams = NULL, re.form = NULL, ReForm, REForm, REform, terms = NULL, type = c("link", "response"), allow.new.levels = FALSE, na.action = na.pass, ...)
object |
a fitted model object |
newdata |
data frame of for which to evaluate predictions. |
newparams |
new parameters to use in evaluating predictions,
specified as in the |
re.form |
formula for random effects to condition on. If |
ReForm, REForm, REform |
allowed for backward compatibility: |
terms |
a |
type |
character string - either |
allow.new.levels |
logical if new levels (or NA values) in
|
na.action |
|
... |
optional additional parameters. None are used at present. |
a numeric vector of predicted values
There is no option for computing standard errors of
predictions because it is difficult to define an
efficient method that incorporates uncertainty in the
variance parameters; we recommend bootMer
for this task.
(gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 |herd), cbpp, binomial)) str(p0 <- predict(gm1)) # fitted values str(p1 <- predict(gm1,re.form=NA)) # fitted values, unconditional (level-0) newdata <- with(cbpp, expand.grid(period=unique(period), herd=unique(herd))) str(p2 <- predict(gm1,newdata)) # new data, all RE str(p3 <- predict(gm1,newdata,re.form=NA)) # new data, level-0 str(p4 <- predict(gm1,newdata,re.form= ~(1|herd))) # explicitly specify RE stopifnot(identical(p2, p4))