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

## Documentation for package ‘tidyLPA’ version 2.0.2

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

tidyLPA-package | tidyLPA: Functionality to carry out Latent Profile Analysis in R
%>% | Pipe
AHP | Select best model using analytic hyrarchy process
calc_lrt | Lo-Mendell-Rubin likelihood ratio test
compare_solutions | Compare latent profile models
curry_mac | Simulated MAC data
empathy | Simulated empathy data
estimate_profiles | Estimate latent profiles
estimate_profiles_mclust | Estimate latent profiles using mclust
estimate_profiles_mplus2 | Estimate latent profiles using Mplus
estimate_profiles_openmx | Estimate latent profiles using OpenMx
get_data | Get data from objects generated by tidyLPA
get_data.tidyLPA | Get data from objects generated by tidyLPA
get_data.tidyProfile | Get data from objects generated by tidyLPA
get_estimates | Get estimates from objects generated by tidyLPA
get_estimates.tidyLPA | Get estimates from objects generated by tidyLPA
get_estimates.tidyProfile | Get estimates from objects generated by tidyLPA
get_fit | Get fit indices from objects generated by tidyLPA
get_fit.tidyLPA | Get fit indices from objects generated by tidyLPA
get_fit.tidyProfile | Get fit indices from objects generated by tidyLPA
id_edu | Simulated identity data
pisaUSA15 | student questionnaire data with four variables from the 2015 PISA for students in the United States
poms | Apply POMS-coding to data
print.tidyLPA | Print tidyLPA
print.tidyProfile | Print tidyProfile
single_imputation | Apply single imputation to data
tidyLPA | tidyLPA: Functionality to carry out Latent Profile Analysis in R