Estimate latent class analyses using OpenMx

This function simplifies the specification of latent class models: models that estimate membership of a categorical latent variable based on binary or ordinal indicators.

Usage

mx_lca(data = NULL, classes = 1L, run = TRUE, ...)

Arguments

data: The data.frame to be used for model fitting.
classes: A vector of integers, indicating which class solutions to generate. Defaults to 1L. E.g., classes = 1:6,
run: Logical, whether or not to run the model. If run = TRUE, the function calls OpenMx::mxTryHardOrdinal().
...: Additional arguments, passed to functions.

Value

Returns an OpenMx::mxModel().

References

Van Lissa, C. J., Garnier-Villarreal, M., & Anadria, D. (2023). Recommended Practices in Latent Class Analysis using the Open-Source R-Package tidySEM. Structural Equation Modeling. doi:10.1080/10705511.2023.2250920

Examples

if (FALSE) { # \dontrun{
df <- data_mix_ordinal
df[1:4] <- lapply(df, ordered)
mx_lca(data = df,
       classes = 2) -> res
} # }