There are 2 repositories under latent-class-analysis topic.
A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).
Latent Class Analysis(LCA), LCA for ordinal indicators, Latent class growth modeling, Laten Profile Analysis, Rasch model, Linear Logistic Test Model, Rasch mixture model, linear and equipercentile equating can be performed within module.
This R package simulates data from a latent class CTMC model
This R tutorial automates the 3-step ML auxiliary variable procedure using the MplusAutomation package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters. To learn more about auxiliary variable integration methods and why multi-step methods are necessary for producing un-biased estimates see Asparouhov & Muthén (2014).
C++ Implementation of poLCA (R package)
Demonstrate the speed of running an LCA analysis using MplusAutomation
Python implementation of Multinomial Logit Model
Survival Analysis with Neural Networks
Latent Class Analysis on German Credit Data Set to find the latent variables affecting the credit outcomes and behaviour
Investigating the efficacy of diagnostic kits used for parasitic disease surveillance in the Philippines.
This `R` tutorial automates the BCH two-step axiliary variable procedure (Bolk, Croon, Hagenaars, 2004) using the `MplusAutomation` package (Hallquist & Wiley, 2018) to estimate models and extract relevant parameters.
GH pages repository to host all tutorial scripts as websites for sharing (PDF/HTML formats).
This walkthrough is presented by the IMMERSE team and will go through some common tasks carried out in R.
A Time-Dependent Structural Model Between Latent Classes and Competing Risks Outcomes
This is a statistical analysis research project on Analyzing Client Behavior in The Connection, sponsored by the Connection Inc. and Wesleyan Quantitative Analysis Center.
Code for comparing three different diagnostics in the detection of two ruminant flukes in the South of Italy
Code for evaluating the reproducibility of the POC-CCA diagnostic for Schistosomiasis across two settings in Uganda
The project uncovers distinct groups of voter profiles utilizing COVID-19 orientations in a representative sample of German voters. The distinct groups in the population differ in their beliefs towards the effectiveness of government measures, compliance with a possible curfew, and trust in various institutions.
Supplementary materials for the manuscript "Latent-class trajectory modeling with a heterogeneous mean-variance relation" by N. G. P. Den Teuling, F. Ungolo, S.C. Pauws, and E.R. van den Heuvel
Civic education is an important subject for every citizen in our modern society. It is important that every individual acknowledge the importance of civil rights and obligations. One of the most commented topics is how society faces and behaves towards the great diversity of individuals and cultures. Students are a great population to be studied as they are forming their own mindset and attitudes. Using ICCS 2016, an international large-scale assessment, it is possible to identify which are the most common patterns among students’ attitudes considering different aspects of equality towards women and ethnic and racial groups. As expected, the larger subpopulation is composed of students that share a high chance to accept and promote equality towards women and ethnics groups. Nonetheless, there is a number of students that tend to disagree with this equality. Another set of students shares a high level of agreement with both groups’ equal rights but disagree with their political role in society. In the case of gender equality, there is a group of students that shares a high level of agreement towards equality in basic rights but in favor of men when competing for jobs or political roles. Another pattern identified for ethnic and racial groups equality is a group of students that disagree with their equal right to have good jobs. These patterns are similar across the 14 countries studied in Europe, but they differ in the number of individuals in each pattern.
SLTCA: Scalable and Robust Latent Trajectory Class Analysis Using Artificial Likelihood