A general implementation of Structural Equation Models
	with latent variables (MLE, 2SLS, and composite likelihood
	estimators) with both continuous, censored, and ordinal
	outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>).
	Mixture latent variable models and non-linear latent variable models
	(Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>).
	The package also provides methods for graph exploration (d-separation,
	back-door criterion), simulation of general non-linear latent variable
	models, and estimation of influence functions for a broad range of
	statistical models.

Fit a variety of latent variable models, including confirmatory
   factor analysis, structural equation modeling and latent growth curve models.

The primary purpose of 'lavaan.mi' is to extend the functionality 
     of the R package 'lavaan', which implements structural equation modeling
     (SEM).  When incomplete data have been multiply imputed, the imputed data
     sets can be analyzed by 'lavaan' using complete-data estimation methods,
     but results must be pooled across imputations (Rubin, 1987, <doi:10.1002/9780470316696>).
     The 'lavaan.mi' package automates the pooling of point and standard-error
     estimates, as well as a variety of test statistics, using a familiar interface
     that allows users to fit an SEM to multiple imputations as they would to a
     single data set using the 'lavaan' package.

Helpers for customizing selected outputs from
  'lavaan' by Rosseel (2012) <doi:10.18637/jss.v048.i02>
  and print them. The functions are intended to be used
  by package developers in their packages and so are not
  designed to be user-friendly. They are designed to be
  let developers customize the tables by other
  functions. Currently the parameter estimates tables of a
  fitted object are supported.

Interactive shiny application for working with different kinds of
    latent variable analysis, with the 'lavaan' package. Graphical output for models
    are provided and different estimators are supported.