Fit a structural equation model using empirical bias-reducing methods

Usage

brsem(
  model,
  data,
  estimator = "ML",
  estimator.args = list(rbm = "implicit", plugin_pen = NULL),
  information = "observed",
  ...
)

Arguments

model

A description of the user-specified model. Typically, the model is described using the lavaan model syntax. See lavaan::model.syntax for more information. Alternatively, a parameter table (eg. the output of the lavaan::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.

estimator

The estimator to use. Currently only "ML" is supported.

estimator.args

A list containing RBM arguments. Possible arguments are

rbm: The type of RBM method to use. One of "none", "explicit", or "implicit" (although, short forms are accepted, e.g. "exp", "iRBM", etc.)
plugin_pen: The type of penalty to use. One of NULL, "pen_ridge", or "pen_ridge_bound".
info_pen The type of information matrix to use for the penalty term.
info_bias The type of information matrix to use for the bias term of the explicit reduced bias method.

information

The type of information matrix to use for calculation of standard errors. Defaults to "observed", although "expected" and "first.order" is also permitted.

...

Additional arguments to pass to the lavaan::lavaan function.

Value

An object of class brlavaan which is a subclass of the lavaan::lavaan class.