Estimate growth mixture models using OpenMx — mx_growth

This function is a wrapper around mx_mixture, adding the default arguments of lavaan::growth() to simplify the specification of growth mixture models. This function is only useful if all the latent variables in the model are growth factors.

Usage

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

Arguments

model: Syntax for the model; either a character string, or a list of character strings, or a list of mxModel objects. See Details.
classes: A vector of integers, indicating which class solutions to generate. Defaults to 1L. E.g., classes = 1:6, classes = c(1:4, 6:8).
data: The data.frame to be used for model fitting.
run: Logical, whether or not to run the model. If run = TRUE, the function calls mixture_starts and run_mx.
...: 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{
data("empathy")
df <- empathy[1:6]
mx_growth_mixture(model = "i =~ 1*ec1 + 1*ec2 + 1*ec3 +1*ec4 +1*ec5 +1*ec6
                           s =~ 0*ec1 + 1*ec2 + 2*ec3 +3*ec4 +4*ec5 +5*ec6
                           ec1 ~~ vec1*ec1
                           ec2 ~~ vec2*ec2
                           ec3 ~~ vec3*ec3
                           ec4 ~~ vec4*ec4
                           ec5 ~~ vec5*ec5
                           ec6 ~~ vec6*ec6
                           i ~~ 0*i
                           s ~~ 0*s
                           i ~~ 0*s",
                  classes = 2,
                  data = df) -> res
} # }