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Showing 1 to 20 of 171 for “"Latent class"”.
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Bayesian Latent Class Models
The latent class model (LCM) is a statistical method that introduces a set of latent categorical variables. The main advantage of LCM is that conditional on latent variables, the manifest variables are mutually independent of each other. In some scenarios, the LCM makes the modeling or computation …
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Domain latent class models, equivalent set latent class models, and kernel factor analysis
This Dissertation was approved for publication on 2024-11-26 at 08:35.
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Identifiability for latent class models
Despite the fact that latent class models have been widely applied and appeared to perform well in various applications, it is well known that inference for latent class models is challenging due to the potential nonidentifiability of the underlying model parameters. In other words, multiple or …
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Latent Class Model in Transportation Study
… as to establish the statistical models for the latent structure of data. Over the past several years, the interest in latent class models has continuously increased due to their great potential in solving practical problems. In this dissertation, I developed several latent class models to …
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The Relation between Uncertainty in Latent Class Membership and Outcomes in a Latent Class Signal Detection Model
Latent class variables are often used to predict outcomes. The conventional practice is to first assign observations to one of the latent classes based on the maximum posterior probabilities. The assigned class membership is then treated as an observed variable and used in predicting the outcomes. …
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Restricted latent class models for polytomous attributes
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-08-01
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Latent class profile analysis : inference, estimation and its applications
… difficult by the fact that the number of latent components is not knowna priori. To address this problem, we propose two solutions, reversible jump MCMC and the Bayesian non-parametric approach, so as to provide a set of principles for the systematic model selection for the …
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A Model That Combines IRT and Latent Class Models
… the widely used Item Response Theory (IRT) and Latent Class models by combining them both. The weakness of IRT is that it is unable to express cognitive structure whether that is rule of operations or particular misunderstanding, or to give descriptive information of knowledge possessed by …
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Longitudinal latent class and joint modelling of antiretroviral adherence
… analysis, joint modeling, and longitudinal latent class analysis to compare di↵erent adherence monitoring tools and examine heterogeneity in adherence behaviors. Key findings include: Electronic Adherence Monitoring (EAM) and tenofovir diphosphate levels in dried blood spots were more …
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Measuring and predicting extreme response style: A latent class approach
… methods, which were all shown to tap a latent factor of response extremity, and a latent class method, which did not achieve significant relationships with the personality predictors.
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Enhancing Neural Network Performance through SHAP-based Latent Class Integration
… in clinical settings like oncology, where latent subpopulations may exist that differ meaningfully in how features affect outcomes. Standard predictive models rarely capture this heterogeneity, resulting in suboptimal performance and limited interpretability. This dissertation presents two …
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Application of ordered latent class regression model in educational assessment
Latent class analysis is a useful tool to deal with discrete multivariate response data. Croon (1990) proposed the ordered latent class model where latent classes are ordered by imposing inequality constraints on the cumulative conditional response probabilities. Taking stochastic ordering of …
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Latent Class Analysis of Health Risk Behaviors Among Survivors of Childhood Adversities
… the Midwest using online surveys. Results from a Latent Class Analysis (LCA) indicated that a three-class model was the best fit. These classes include a “Poor Diet, Inactivity, and Risky Behavior” class, “Poor Diet and Inactivity” class, and an “Inactivity” class. Once classes were created, a …
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Identifiability and estimation for restricted latent class models and hidden Markov models
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms
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Patterns of interpersonal violence and contexts of risk: A latent class analysis
… a large sample of women aged 18-25 (N=1,303), a latent class analysis was employed to explore patterns of polyvictimization of dating violence, sexual assault, stalking, and sexual harassment. Five classes of survivors emerged with each having distinct patterns of victimization: Universal …
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Latent class modelling of respiratory outcomes in a South African birth cohort
… function measurements through the derivation of latent phenotype classes and (2) the impact of early-life lower respiratory tract infections (LRTIs) and other predictors on wheezing and lung function. Methods: Data from the Drakenstein Child Health Study (DCHS) was used to critically evaluate …
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Dispositional Differences in Frequencies of and Reasons for Voluntary Turnover: A Latent-Class Approach
… frequencies and reasons, person-oriented latent class procedures were used to supplement information obtained from traditional, variable-oriented methods. The results of latent class cluster analysis showed that people belonging to a latent class characterized by high extraversion, …
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Bayesian estimation of restricted latent class models: Extending priors, link functions, and structural models
Restricted latent class models (RLCMs) provide a pivotal framework for supporting diagnostic research that enhances human development and opportunities. In earlier research, the focus was on confirmatory methods that required a pre-specified expert-attribute mapping known as a Q matrix. Recent …
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