This function is a wrapper around mx_mixture, adding the
default arguments of 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.
mx_growth_mixture(model, classes = 1L, data = NULL, run = TRUE, ...)Syntax for the model; either a character string, or a list of
character strings, or a list of mxModel objects. See Details.
A vector of integers, indicating which class solutions to
generate. Defaults to 1L. E.g., classes = 1:6,
classes = c(1:4, 6:8).
The data.frame to be used for model fitting.
Logical, whether or not to run the model. If run = TRUE,
the function calls mixture_starts and run_mx.
Additional arguments, passed to functions.
Returns an mxModel.
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
if (FALSE) {
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
}