Learn R Programming

psychonetrics (version 0.15)

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 . Allows for confirmatory testing and fit as well as exploratory model search.

Copy Link

Version

Install

install.packages('psychonetrics')

Monthly Downloads

762

Version

0.15

License

GPL-2

Maintainer

Sacha Epskamp

Last Published

February 27th, 2026

Functions in psychonetrics (0.15)

Convenience functions

Change the data of a psychonetrics object

Ergodic Subspace Analysis

Reset starting values to simple defaults

Diagnostic functions

Maximum likelihood covariance estimate

find_penalized_lambda

Automated Lambda Selection for Penalized Estimation

Compute factor scores

Lag-1 dynamic latent variable model family of psychonetrics models for panel data

Model comparison

Print fit indices

Obtain the asymptotic covariance matrix

Group equality constrains

Retrieve the psychonetrics logbook

loop_psychonetrics

Parallel loop for psychonetrics

Extract an estimated matrix

Attempt to Fix Starting Values

Generate data from a fitted psychonetrics object

Latnet growth curve model

Parameters modification

Stepwise model search

Set equality constrains across parameters

Meta-analytic VAR(1) model

Multi-level latent variable model family

Continuous latent variable family of psychonetrics models

Print parameter estimates

Multi-level Lag-1 dynamic latent variable model family of psychonetrics models for time-series data

psychonetrics_update

Model updating functions

Meta-analytic latent variable model

Variance-covariance and GGM meta analysis

psychonetrics-package

tools:::Rd_package_title("psychonetrics")

Partial pruning of multi-group models

Run a psychonetrics model

psychonetrics-class

Class "psychonetrics"

Penalized Maximum Likelihood Functions

Should messages of computation progress be printed?

Stepdown model search by pruning non-significant parameters.

Random intercept cross-lagged panel models

psychonetrics_log-class

Class "psychonetrics"

psychonetrics_bootstrap-class

Class "psychonetrics_bootstrap"

write_psychonetrics

Write comprehensive model output to a text file

simplestructure

Generate factor loadings matrix with simple structure

Lag-1 vector autoregression family of psychonetrics models

Unify models across groups

Stepup model search along modification indices

Variance-covariance family of psychonetrics models

Transform between model types

Lag-1 dynamic latent variable model family of psychonetrics models for time-series data

Network Analysis 2020 Self-Report Data

Bootstrap a psychonetrics model

Bi-factor models

duplicationMatrix

Model matrices used in derivatives

aggregate_bootstraps

Aggregate Bootstrapped Models

Print modification indices

Plot Analytic Confidence Intervals

Star Wars dataset