| modsem_inspect | R Documentation |
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.
modsem_inspect(object, what = NULL, ...)
## S3 method for class 'lavaan'
modsem_inspect(object, what = "free", ...)
## S3 method for class 'modsem_da'
modsem_inspect(object, what = NULL, ...)
## S3 method for class 'modsem_pi'
modsem_inspect(object, what = "free", ...)
object |
A fitted object of class |
what |
Character scalar selecting what to return (see Details).
If |
... |
Passed straight to |
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.
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.
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
## Not run:
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")
## End(Not run)
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