modsem_inspect: Inspect model information

Description

function used to inspect fitted object. Similar to lavaan::lavInspect argument what decides what to inspect

modsem_inspect.modsem_da Lets you pull matrices, optimiser diagnostics, expected moments, or fit measures from a modsem_da object.

Usage

modsem_inspect(object, what = NULL, ...)
# S3 method for lavaan
modsem_inspect(object, what = "free", ...)
# S3 method for modsem_da
modsem_inspect(object, what = NULL, ...)
# S3 method for modsem_pi
modsem_inspect(object, what = "free", ...)

Value

A named list with the extracted information. If a single piece of information is returned, it is returned as is; not as a named element in a list.

Arguments

object: A fitted object of class "modsem_da".
what: Character scalar selecting what to return (see Details). If NULL the value "default" is used.
...: Passed straight to modsem_inspect_da().

Methods (by class)

modsem_inspect(lavaan): Inspect a lavaan object
modsem_inspect(modsem_da): Inspect a modsem_da object
modsem_inspect(modsem_pi): Inspect a modsem_pi object

Details

For modsem_pi objects, it is just a wrapper for lavaan::lavInspect. For modsem_da objects an internal function is called, which takes different keywords for the what argument.

Below is a list of possible values for the what argument, organised in several sections. Keywords are case-sensitive.

Presets

"default": Everything in Sample information, Optimiser diagnostics Parameter tables, Model matrices, and Expected-moment matrices except the raw data slot
"coef": Coefficients and variance-covariance matrix of both free and constrained parameters (same as "coef.all").
"coef.all": Coefficients and variance-covariance matrix of both free and constrained parameters (same as "coef").
"coef.free": Coefficients and variance-covariance matrix of the free parameters.
"all": All items listed below, including data.
"matrices": The model matrices.
"optim": Only the items under Optimiser diagnostics
"fit": A list with fit.h0, fit.h1, comparative.fit

Sample information:

"N": Number of analysed rows (integer).

Parameter estimates and standard errors:

"coefficients.free": Free parameter values.
"coefficients.all": Both free and constrained parameter values.
"vcov.free": Variance–covariance of free coefficients only.
"vcov.all": Variance–covariance of both free and constrained coefficients.

Optimiser diagnostics:

"coefficients.free": Free parameter values.
"vcov.free": Variance–covariance of free coefficients only.
"information": Fisher information matrix.
"loglik": Log-likelihood.
"iterations": Optimiser iteration count.
"convergence": TRUE/FALSE indicating whether the model converged.

Parameter tables:

"partable": Parameter table with estimated parameters.
"partable.input": Parsed model syntax.

Model matrices:

"lambda": \(\Lambda\) – Factor loadings.
"tau": \(\tau\) – Intercepts for indicators.
"theta": \(\Theta\) – Residual (Co-)Variances for indicators.
"gamma.xi": \(\Gamma_{\xi}\) – Structural coefficients between exogenous and endogenous variables.
"gamma.eta": \(\Gamma_{\eta}\) – Structural coefficients between endogenous variables.
"omega.xi.xi": \(\Omega_{\xi\xi}\) – Interaction effects between exogenous variables
"omega.eta.xi": \(\Omega_{\eta\xi}\) – Interaction effects between exogenous and endogenous variables
"phi": \(\Phi\) – (Co-)Variances among exogenous variables.
"psi": \(\Psi\) – Residual (co-)variances among engoenous variables.
"alpha": \(\alpha\) – Intercepts for endogenous variables
"beta0": \(\beta_0\) – Intercepts for exogenous variables

Model-implied matrices:

"cov.ov": Model-implied covariance of observed variables.
"cov.lv": Model-implied covariance of latent variables.
"cov.all": Joint covariance of observed + latent variables.
"cor.ov": Correlation counterpart of "cov.ov".
"cor.lv": Correlation counterpart of "cov.lv".
"cor.all": Correlation counterpart of "cov.all".
"mean.ov": Expected means of observed variables.
"mean.lv": Expected means of latent variables.
"mean.all": Joint mean vector.

R-squared and standardized residual variances:

"r2.all": R-squared values for both observed (i.e., indicators) and latent endogenous variables.
"r2.lv": R-squared values for latent endogenous variables.
"r2.ov": R-squared values for observed (i.e., indicators) variables.
"res.all": Standardized residuals (i.e., 1 - R^2) for both observed (i.e., indicators) and latent endogenous variables.
"res.lv": Standardized residuals (i.e., 1 - R^2) for latent endogenous variables.
"res.ov": Standardized residuals (i.e., 1 - R^2) for observed variables (i.e., indicators).

Interaction-specific caveats:

If the model contains an uncentred latent interaction term it is centred internally before any cov.*, cor.*, or mean.* matrices are calculated.
These matrices should not be used to compute fit-statistics (e.g., chi-square and RMSEA) if there is an interaction term in the model.

Examples

Run this code

if (FALSE) {
m1 <- "
 # Outer Model
 X =~ x1 + x2 + x3
 Y =~ y1 + y2 + y3
 Z =~ z1 + z2 + z3

 # Inner model
 Y ~ X + Z + X:Z
"

est <- modsem(m1, oneInt, "lms")

modsem_inspect(est) # everything except "data"
modsem_inspect(est, what = "optim")
modsem_inspect(est, what = "phi")
}

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