Structural Equation Modeling and Confirmatory Network Analysis
Aggregate Bootstrapped Models
Model matrices used in derivatives
Bi-factor models
Bootstrap a psychonetrics model
Change the data of a psychonetrics object
Plot Analytic Confidence Intervals
Model comparison
Convenience functions
Maximum likelihood covariance estimate
Latnet growth curve model
Retrieve the psychonetrics logbook
Continuous latent variable family of psychonetrics models
Variance-covariance and GGM meta analysis
Set equality constrains across parameters
Partial pruning of multi-group models
Diagnostic functions
Lag-1 dynamic latent variable model family of psychonetrics models for...
Reset starting values to simple defaults
Ergodic Subspace Analysis
Compute factor scores
Print fit indices
Should messages of computation progress be printed?
Generate factor loadings matrix with simple structure
Parameters modification
Attempt to Fix Starting Values
Generate data from a fitted psychonetrics object
Extract an estimated matrix
Obtain the asymptotic covariance matrix
Group equality constrains
Ising model
Print modification indices
Multi-level latent variable model family
Multi-level Lag-1 dynamic latent variable model family of psychonetric...
Stepwise model search
Model updating functions
Print parameter estimates
Stepup model search along modification indices
Stepdown model search by pruning non-significant parameters.
Class "psychonetrics"
tools:::Rd_package_title("psychonetrics")
Class "psychonetrics_bootstrap"
Class "psychonetrics"
Run a psychonetrics model
Transform between model types
Lag-1 dynamic latent variable model family of psychonetrics models for...
Unify models across groups
Lag-1 vector autoregression family of psychonetrics models
Variance-covariance family of psychonetrics models
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.