Usage
lmer(formula, data = NULL, REML = TRUE,
control = lmerControl(), start = NULL, verbose = 0L,
subset, weights, na.action, offset, contrasts = NULL,
devFunOnly = FALSE, ...)
Arguments
formula
a two-sided linear formula object
describing both the fixed-effects and fixed-effects part
of the model, with the response on the left of a ~
operator and the terms, separated by +
operators,
on the right. Random-effects
data
an optional data frame containing the
variables named in formula
. By default the
variables are taken from the environment from which
lmer
is called. While data
is optional, the
package authors strongly
REML
logical scalar - Should the estimates be chosen to
optimize the REML criterion (as opposed to the log-likelihood)?
control
a list (of correct class, resulting from
lmerControl()
or glmerControl()
respectively) containing control parameters, including the nonlinea start
a named list
of starting values for the
parameters in the model. For lmer
this can be a numeric
vector or a list with one component named "theta"
. verbose
integer scalar. If > 0
verbose
output is generated during the optimization of the
parameter estimates. If > 1
verbose output is
generated during the individual PIRLS steps.
subset
an optional expression indicating the
subset of the rows of data
that should be used in
the fit. This can be a logical vector, or a numeric
vector indicating which observation numbers are to be
included, or a character vector of the r
weights
an optional vector of prior
weights to be used in the fitting process. Should be
NULL
or a numeric vector.
na.action
a function that indicates what should
happen when the data contain NA
s. The default
action (na.omit
, inherited from the 'factory
fresh' value of getOption("na.action")
) strips any
observations with any missi
offset
this can be used to specify an a
priori known component to be included in the linear
predictor during fitting. This should be NULL
or a
numeric vector of length equal to the number of cases.
One or more
contrasts
an optional list. See the
contrasts.arg
of model.matrix.default
.
devFunOnly
logical - return only the deviance
evaluation function. Note that because the deviance
function operates on variables stored in its environment,
it may not return exactly the same values on
subsequent calls (but the results should always
...
other potential arguments. A method
argument was used in earlier versions of the package. Its
functionality has been replaced by the REML
argument.