inst/doc/benchmarking-mclust-and-mplus.R

In tidyLPA: Easily Carry Out Latent Profile Analysis (LPA) Using Open-Source or Commercial Software

## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>", 
  eval = FALSE
)

## -----------------------------------------------------------------------------
# library(tidyLPA)
# library(dplyr)
# 
# iris %>%
#   select(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) %>%
#   estimate_profiles(n_profiles = 2) %>%
#   get_fit() %>%
#   as.data.frame()

## -----------------------------------------------------------------------------
# iris %>%
#   select(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) %>%
#   estimate_profiles(n_profiles = 2, package = "mplus") %>%
#   get_fit() %>%
#   as.data.frame()

## -----------------------------------------------------------------------------
# library(tidyLPA)
# library(dplyr)
# 
# iris %>%
#   select(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) %>%
#   estimate_profiles(n_profiles = 2:4, models = c(1, 2, 3, 6)) %>%
#   get_fit() %>%
#   as.data.frame()

## -----------------------------------------------------------------------------
# iris %>%
#   select(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) %>%
#   estimate_profiles(n_profiles = 2:4, models = c(1, 2, 3, 6),
#                     package = "mplus") %>%
#   get_fit() %>%
#   as.data.frame()