Domain latent class models, equivalent set latent class models, and kernel factor analysis

We discuss main contributions to Latent Class Modelings and Factor Analysis. 1) Domain Latent Class Models (DLCMs) extend latent class models to allow for related questions. 2) Equivalence Set Restricted Latent Class Models (ESRLCMs) allow for a much greater variety of restrictions compared with restricted latent trait models. 3) Kernel Exploratory Factor Analysis (KEFA) conduct factor analysis after controlling for covariates.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Statistics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2024

Author dc:creator

• Bowers, Jesse Mark

Contributors dc:contributor

• Culpepper, Steve
• Douglas, Jeffrey
• Zhu, Ruoqing
• Park, Trevor

• Latent Class Modeling
• Clustering
• Factor Analysis
• Categorical Data Analysis
• Dimension Reduction

Statement dc:rights

• Copyright 2024 Jesse Bowers. Chapter 2 is a copy of a paper published in Bayesian Analysis (http://dx.doi.org/10.1214/24-BA1433) which is available by a creative commons license (https://creativecommons.org/licenses/by/4.0/) and reproduced here with only changes to formatting.

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/127472

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F127472