cov.mtx

This function generates the model-implied covariance and correlation matrices based on a specified structural equation model (SEM).
The function returns the implied covariance and correlation matrices.

Provides tools to conduct Monte Carlo simulations under different conditions (e.g., varying sample size, data normality) for structural equation models (SEMs).
Data can be simulated based on user-defined factor loadings and correlations, with optional non-normality added via Fleishman's power method (1978) <doi:10.1007/BF02293811>.
Once generated, models can be estimated using 'lavaan'. This package facilitates testing model performance across multiple simulation scenarios.
When data generation is completed (or when generated data sets are given) model tests can also be run.
Please cite as "Orçan, F. (2021). MonteCarloSEM An R Package to Simulate Data for SEM. International Journal of Assessment Tools in Education, 8 (3), 704-713."

Fatih Orcan

MonteCarloSEM

Monte Carlo Simulation for Structural Equation Modeling

Fatih Orçan

cov.mtx function

<dl><dt>Model</dt>
<dd>A lavaan model object specifying the measurement and structural components of the SEM.</dd>
<dt>nobs</dt>
<dd>An integer indicating the number of observed indicators (xs) in the model.</dd></dl>

Arguments

Author

Simulates Correlation matrix by a given SEM model. — cov.mtx

<dl>

<dt>Model</dt>
<dd>A lavaan model object specifying the measurement and structural components of the SEM.</dd>


<dt>nobs</dt>
<dd>An integer indicating the number of observed indicators (xs) in the model.</dd>

</dl>

cov.mtx: Simulates Correlation matrix by a given SEM model.

Description

Usage

Value

Arguments

Author

Examples