evaluate.lcmm: A LCGA Optimal Model Searching Function

In noahlorinczcomi/sgmm: Tools for preparing longitudinal data for analysis and growth mixture modelling using the lcmm package

A LCGA Optimal Model Searching Function

Description

This function helps you identify model fit values for different linear, beta, and spline models.

Usage

evaluate.lcmm(data, x_name, y_name, g_name, ng_max = 8,
  spline_max = NULL, spline_type = NULL)

Arguments

data	enter data set with date values converted to day/month/year values.
x_name	enter the time-indictating column name (str)
y_name	enter the time-varying outcome variable column name (str)
g_name	enter the subject grouping variable column name (str; ususally 'ID')
ng_max	enter the maximum number of groups you would like to evaluate.
spline_max	enter the maximum number of splines you would like the model to evaluate.
spline_type	if spline_max != NULL, enter either the spline type you would like to evaluate (either 'quant' or 'equi')

Examples

evaluate.lcmm()

noahlorinczcomi/sgmm documentation built on Aug. 23, 2023, 1:28 a.m.