27 citations · 46 across the 7 of their papers we have counts for
7 papers
Unraveling the Skillsets of Data Scientists: Text Mining Analysis of Dutch University Master Programs in Data Science and Artificial Intelligence
Mathijs J. Mol, Barbara Belfi, Zsuzsa Bakk
The growing demand for data scientists in the global labor market and the Netherlands has led to a rise in data science and artificial intelligence (AI) master programs offered by…
Multilevel latent class analysis with covariates: Analysis of cross-national citizenship norms with a two-stage approach
Roberto Di Mari, Zsuzsa Bakk, Jennifer Oser +1
This paper focuses on the substantive application of multilevel LCA to the evolution of citizenship norms in a diverse array of democratic countries. To do so, we present a two-sta…
multilevLCA: An R Package for Single-Level and Multilevel Latent Class Analysis with Covariates
Johan Lyrvall, Roberto Di Mari, Zsuzsa Bakk +2
This contribution presents a guide to the R package multilevLCA, which offers a complete and innovative set of technical tools for the latent class analysis of single-level and mul…
StepMix: A Python Package for Pseudo-Likelihood Estimation of Generalized Mixture Models with External Variables
Sacha Morin, Robin Legault, Félix Laliberté +4
StepMix is an open-source Python package for the pseudo-likelihood estimation (one-, two- and three-step approaches) of generalized finite mixture models (latent profile and latent…
Two-step estimation of latent trait models
Jouni Kuha, Zsuzsa Bakk
We consider likelihood-based two-step estimation of latent variable models, in which just the measurement model is estimated in the first step and the measurement parameters are th…
A two-step estimator for multilevel latent class analysis with covariates
Roberto Di Mari, Zsuzsa Bakk, Jennifer Oser +1
We propose a two-step estimator for multilevel latent class analysis (LCA) with covariates. The measurement model for observed items is estimated in its first step, and in the seco…
Cluster-weighted latent class modeling
Roberto Di Mari, Antonio Punzo, Zsuzsa Bakk
Usually in Latent Class Analysis (LCA), external predictors are taken to be cluster conditional probability predictors (LC models with covariates), and/or score conditional probabi…