get_CFA_estimates: Conduct Confirmatory Factor Analysis (CFA) and Obtain...

In tspsyched/autoFC: Automatic Construction of Forced-Choice Tests

Conduct Confirmatory Factor Analysis (CFA) and Obtain Parameter Estimates

Description

Reads in responses to Likert-type scales and a specified factor model, performs CFA, and produces parameter estimates required for producing subsequent simulation data (i.e., use as inputs for get_simulation_matrices()).

This function returns factor loadings, intercepts, residual variances, and covariances among latent variables

Usage

get_CFA_estimates(response_data, fit_model, item_names)

Arguments

response_data	Likert-type response data. Requires the header including variable names.
fit_model	A pre-specified CFA model written in lavaan syntax.
item_names	Names of the items you wish to obtain loadings, intercepts, and residuals. These variable names should appear in response_data.

Details

This function is essentially a wrapper for lavaan::parameterEstimates() to obtain specific set of parameter estimates.

Notice that we assume your CFA model does not have hierarchical factor structure, nor does it have cross loadings or correlated residuals.

Value

A list containing:

loadings Item loadings for item_names

intercepts Item intercepts for item_names

residuals Item residual variances for item_names

covariances Covariances between latent variables defined in fit_model

model_fit Model fit for fit_model on response_data

Author(s)

Mengtong Li

References

Ashton, M. C., & Lee, K. (2009). The HEXACO–60: A short measure of the major dimensions of personality. Journal of personality assessment, 91(4), 340-345. https://doi.org/10.1080/00223890902935878

See Also

get_simulation_matrices()

Examples

## We have a small response sample data (N = 100) on the HEXACO-60 (Ashton & Lee, 2009) scale in the package
## Names of the items are SS1-SS60 (Single-statement)
rating_data <- HEXACO_example_data
cfa_model <- paste0("H =~ ", paste0("SS", seq(6,60,6), collapse = " + "), "\n",
                   "E =~ ", paste0("SS", seq(5,60,6), collapse = " + "), "\n",
                   "X =~ ", paste0("SS", seq(4,60,6), collapse = " + "), "\n",
                   "A =~ ", paste0("SS", seq(3,60,6), collapse = " + "), "\n",
                   "C =~ ", paste0("SS", seq(2,60,6), collapse = " + "), "\n",
                   "O =~ ", paste0("SS", seq(1,60,6), collapse = " + "), "\n")
cfa_estimates <- get_CFA_estimates(response_data = rating_data,
                                   fit_model = cfa_model, 
                                   item_names = paste0("SS",c(1:60)))

tspsyched/autoFC documentation built on Oct. 8, 2024, 10:39 p.m.