psychonetrics-package {psychonetrics}

Structural Equation Modeling and Confirmatory Network Analysis

Description

Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data <doi:10.31234/osf.io/8ha93>. Allows for confirmatory testing and fit as well as exploratory model search.

Details

The DESCRIPTION file:

Package:	psychonetrics
Type:	Package
Title:	Structural Equation Modeling and Confirmatory Network Analysis
Version:	0.11.6
Author:	Sacha Epskamp
Maintainer:	Sacha Epskamp <[e-mail]>
Description:	Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data <doi:10.31234/osf.io/8ha93>. Allows for confirmatory testing and fit as well as exploratory model search.
License:	GPL-2
LinkingTo:	Rcpp (>= 0.11.3), RcppArmadillo, pbv, roptim
Depends:	R (>= 4.3.0)
Imports:	methods, qgraph, numDeriv, dplyr, abind, Matrix (>= 1.6-5), lavaan, corpcor, glasso, mgcv, optimx, VCA, pbapply, parallel, magrittr, IsingSampler, tidyr, psych, GA, combinat, rlang
Suggests:	psychTools, semPlot, graphicalVAR, metaSEM, mvtnorm, ggplot2
ByteCompile:	true
URL:	http://psychonetrics.org/
BugReports:	https://github.com/SachaEpskamp/psychonetrics/issues
StagedInstall:	true
NeedsCompilation:	yes
Packaged:	2023-10-03 07:28:38 UTC; sachaepskamp
Repository:	CRAN
Date/Publication:	2023-10-03 11:00:02 UTC

Index of help topics:

CIplot                  Plot Analytic Confidence Intervals
Ising                   Ising model
Jonas                   Jonas dataset
MIs                     Print modification indices
StarWars                Star Wars dataset
addMIs                  Model updating functions
bifactor                Bi-factor models
bootstrap               Bootstrap a psychonetrics model
changedata              Change the data of a psychonetrics object
compare                 Model comparison
covML                   Maximum likelihood covariance estimate
dlvm1                   Lag-1 dynamic latent variable model family of
                        psychonetrics models for panel data
duplicationMatrix       Model matrices used in derivatives
emergencystart          Reset starting values to simple defaults
esa                     Ergodic Subspace Analysis
factorscores            Compute factor scores
fit                     Print fit indices
fixpar                  Parameters modification
generate                Generate data from a fitted psychonetrics
                        object
getVCOV                 Obtain the asymptotic covariance matrix
getmatrix               Extract an estimated matrix
groupequal              Group equality constrains
latentgrowth            Latnet growth curve model
lvm                     Continuous latent variable family of
                        psychonetrics models
meta_varcov             Variance-covariance and GGM meta analysis
ml_lvm                  Multi-level latent variable model family
ml_tsdlvm1              Multi-level Lag-1 dynamic latent variable model
                        family of psychonetrics models for time-series
                        data
modelsearch             Stepwise model search
parameters              Print parameter estimates
parequal                Set equality constrains across parameters
partialprune            Partial pruning of multi-group models
prune                   Stepdown model search by pruning
                        non-significant parameters.
psychonetrics-class     Class '"psychonetrics"'
psychonetrics-package   Structural Equation Modeling and Confirmatory
                        Network Analysis
runmodel                Run a psychonetrics model
setestimator            Convenience functions
setverbose              Should messages of computation progress be
                        printed?
simplestructure         Generate factor loadings matrix with simple
                        structure
stepup                  Stepup model search along modification indices
tsdlvm1                 Lag-1 dynamic latent variable model family of
                        psychonetrics models for time-series data
unionmodel              Unify models across groups
var1                    Lag-1 vector autoregression family of
                        psychonetrics models
varcov                  Variance-covariance family of psychonetrics
                        models

This package can be used to perform Structural Equation Modeling and confirmatory network modeling. Current implemented families of models are (1) the variance–covariance matrix (varcov), (2) the latent variable model (lvm), (3) the lag-1 vector autoregression model (var1), and (4) the dynamical lag-1 latent variable model for panel data (dlvm1) and for time-series data (tsdlvm1).

Author(s)

Sacha Epskamp

Maintainer: Sacha Epskamp <[e-mail]>

References

More information: psychonetrics.org