fcors.value

This function generates a symmetric factor correlation matrix for a Structural Equation Model. The correlations must be provided as a vector of values between -1 and +1.
The vector can be entered in either row-wise or column-wise order, but the correlations must be supplied in the correct sequence.
If the model includes only a single factor, the function should be called as: "fcors.value(nf = 1, cors = c(1))"

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

fcors.value function

<dl><dt>nf</dt>
<dd>An integer specifying the number of factors.</dd>
<dt>cors</dt>
<dd>A numeric vector of correlations among the factors. Values must be between -1 and +1.</dd></dl>

Arguments

Author

Specifies the Factor Correlation Matrix for a Model — fcors.value

<dl>

<dt>nf</dt>
<dd>An integer specifying the number of factors.</dd>


<dt>cors</dt>
<dd>A numeric vector of correlations among the factors. Values must be between -1 and +1.</dd>

</dl>

fcors.value: Specifies the Factor Correlation Matrix for a Model

Description

Usage

Value

Arguments

Author

Examples