Usage
fsr(model = NULL, data = NULL, cmd = "sem",
fsr.method = "Croon", fs.method = "Bartlett",
fs.scores = FALSE, Gamma.NT = TRUE, lvinfo = FALSE, ...)Arguments
model
A description of the user-specified model. Typically, the model
is described using the lavaan model syntax. See
model.syntax for more information. Alternatively, a
parameter table (eg. the output of the lavaanify() function) is also
accepted. data
An optional data frame containing the observed variables used in
the model. If some variables are declared as ordered factors, lavaan will
treat them as ordinal variables.
cmd
Charcater. Which command is used to run the sem models. The possible
choices are "sem" or "lavaan", determining how
we deal with default options.
fsr.method
Character. Factor score regression method. Possible
options are naive, Skrondal-Laake, and Croon.
fs.method
Character. Factor score estimation method. Possible
options are Bartlett and regression.
fs.scores
Logical. If TRUE, explicitly compute factor scores; if
FALSE, only compute the mean vector and variance matrix of the
factor scores.
Gamma.NT
Logical. Only needed when se="robust.sem" and
data is missing; if TRUE, compute Gamma (N times the variance
matrix of the sample statistics) assuming normality.
lvinfo
Logical. If TRUE, return latent variable information
as an attribute to the output.
...
Further arguments that we pass to the "cfa", "sem" or
"lavaan" functions.