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Graphing Nonlinear Relations Among Latent Variables from Structural Equation Mixture Models
Contains a graphical user interface to generate the diagnostic
plots proposed by Bauer (2005;
Latent Structure Learning
Fits structural equation modeling via penalized likelihood.
Power Analyses for SEM
Provides a-priori, post-hoc, and compromise power-analyses for structural equation models (SEM).
Easy Model-Builder Functions for 'OpenMx'
Utilities for building certain kinds of common matrices and models in the extended structural equation modeling package, 'OpenMx'.
'SEM Shiny'
Interactive 'shiny' application for working with Structural Equation Modelling technique. Runtime examples are provided in the package function as well as at < https://kartikeyab.shinyapps.io/semwebappk/> .
Average and Conditional Effects
Use structural equation modeling to estimate average and conditional effects of a treatment variable on an outcome variable, taking into account multiple continuous and categorical covariates.
SEM Sensitivity Analysis
Performs sensitivity analysis for Structural Equation Modeling (SEM). It determines which sample points need to be removed for the sign of a specific path in the SEM model to change, thus assessing the robustness of the model. Methodological manuscript in preparation.
Fit Measure Cutoffs in SEM
Calculate cutoff values for model fit measures used in structural equation modeling (SEM) by simulating and testing data sets (cf. Hu & Bentler, 1999
Ancestor Regression
Causal discovery in linear structural equation models (Schultheiss, and Bühlmann (2023)
Post-Estimation Utilities for 'lavaan' Fitted Models
Companion toolbox for structural equation models fitted with 'lavaan'. Provides post-estimation diagnostics and graphics that operate directly on a fitted object using its estimates and covariance, and refits auxiliary models when needed. The package relies on 'lavaan' (Rosseel, 2012)