esem_cfa2: Exploratory Structural Equiation Modeling ESEM (ESEM) with geominT rotation

Description

Exploratory Structural Equiation Modeling ESEM (ESEM) with geominT rotation

Usage

esem_cfa2(
  data,
  nfactors,
  fm = "ML",
  rotate = "geominT",
  scores = "regression",
  residuals = TRUE,
  Target = NULL,
  missing = TRUE,
  mimic = c("MPlus"),
  std.lv = TRUE,
  ordered = TRUE
)

Value

An object of class lavaan::lavaan-class, for which several methods are available, including a summary method.

Arguments

data: is a raw data matrix.
nfactors: is number of factors to extract
fm: is factoring method to be used in factor estimation. The suggested methods are available in psych::fa()
rotate: is the rotation method to be used. The suggested methods are available in psych::fa()
scores: is the factor scores to be used in EFA estimation. The default scores are estimated using regression as set in "regression".
residuals: is set to FALSE by default. In case the residual matrix is required in the output, this parameter should be set to TRUE
Target: is the target rotation matrix to be used. In case no target matrix is provided, EFA proceeds with alternative approach. The list of target rotations are available from GPArotation
missing: is used with scores set to TRUE. The default is missing=TRUE which imputes missing values using either the median or the mean.
mimic: allows to mimic the final output results (i.e. CFA stage) to MPLUS to allow the user to compare the output.
std.lv: is set to TRUE by default to provide standardized latent variables.
ordered: is set to TRUE by default to allow the use of categorical variables.