Forthcoming major changes

Caspar van Lissa


tidyLPA update

tidyLPA has received a major update. Your old function calls might not work as expected anymore. The new version of tidyLPA is based on the following philosophy:

The goal of tidyLPA is to make latent profile analysis easily accessible to a broad audience, by means of a user-friendly interface.

tidyLPA fits easily into a ‘tidyverse’ workflow.

tidyLPA offers parallel functionality for the open-source package Mclust, and the commercial package Mplus.

The focus on making LPA accessible, and offering a parallel workflow across Mclust and Mplus, has necessitated some simplification of the existing functions. Advanced options are still available, but require slightly more work on the user’s part. The upside of this is that, for most users, the tidyLPA workflow and documentation are substantially simplified.

The best way to understand the changes to tidyLPA is by explaining the new workflow.

New workflow:

Example analysis:

A full analysis might look like this:

full_df %>%
    select(Your, Selected, Variable, Names) %>%
    estimate_profiles(n_profiles = 1:6, models = 1:3) ->



New functionality:

Deprecated functionality:

For Mclust:

* prior_control

For Mplus:

* starts
* m_iterations
* st_iterations
* convergence_criterion
* optseed
* cluster_ID
* include_VLMR
* include_BLRT (but BLRT is returned by default now)