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.

Affords an alternative, vector-based syntax to 'lavaan', as well as other 
             convenience functions such as naming paths and defining indirect
             links automatically, in addition to convenience formatting optimized
             for a publication and script sharing workflow.

Provides a graphical user interface with an
    integrated diagrammer for latent variable models from the 'lavaan' package.
    It offers two core functions: first, lavaangui() launches a web application
    that allows users to specify models by drawing path diagrams, fitting them,
    assessing model fit, and more; second, plot_lavaan() creates interactive
    path diagrams from models specified in 'lavaan'. After customizing a diagram
    interactively, export_plot() saves it to a file, enabling reproducible
    scripts without sacrificing fine-grained control over appearance.
    Karch (2024) <doi: 10.1080/10705511.2024.2420678> contains a tutorial.