Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 29 for “"Latent class models"”.
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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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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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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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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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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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Methods and Theory for Joint Estimation of Incidental and Structural Parameters in Latent Class Models
… become the standard for parameter estimation in latent variable models. However, there are instances when alternative estimators that jointly estimate incidental parameters and structural parameters might be easier to implement. A drawback to joint estimation, and joint maximum likelihood …
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Tag based Bayesian latent class models for movies : economic theory reaches out to big data science
… consumer preferences. In response to this, models of linear optimization, rational addiction and Bayesian learning have been applied to better understand consumer decision- making, belief formation and revision. While valuable, these approaches do not lend themselves to forming verifiable …
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Predicting and Tracking Mathematics Growth Using High - Stakes Test Scores: An Examination of Latent Growth and Latent Class Models
… predicting later high-stakes mathematics scores, latent growth trajectories, the number of latent class growth trajectories present from third to sixth grade, and decision statistics. Participants were 1,414 students, comprised of three cohorts attending a suburban public school district in …
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Estimation of population totals from imperfect census, survey and administrative records
… size of interest. There are a number of models that may be specified based on the incomplete (2<sup>r</sup>-1) table of observed counts, and if a model is found that adequately fits these observed counts an estimate of the unobserved cell can be derived. The thesis will be concentrating …
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Some theoretical and applied developments to support cognitive learning and adaptive testing
… (CAT) are useful tools to measure subjects' latent abilities from two different aspects. CDM plays a very important role in the fine-grained assessment, where the primary purpose is to accurately classify subjects according to the skills or attributes they possess, while CAT is a useful tool …
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Latent Class Model in Transportation Study
… be interpreted 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 …
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Cluster Analysis for Cognitive Diagnosis: Theory and Applications
Latent class models for cognitive diagnosis often begin with specification of a matrix that indicates which attributes or skills are needed for each item. Then by imposing restrictions that take this into account, along with a theory governing how subjects interact with items, parametric …
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Estimating Desirable Cattle Traits Using Latent Class and Mixed Logit Models: A Choice Modeling Application to the U.S. Grass-Fed Beef Industry
… for cattle traits using mixed logit and latent class models. Choice experiment data from a 2013 mail survey of 1,052 U.S. grass-fed beef producers were used. The findings indicate that grass-fed beef producers generally preferred lower-priced, heavy animals that were small-to-medium …
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Statistical Methods for Biological and Relational Data
… and relational data. The methods include classification, multiple testing and social networking. The models for classification are applied to gene expression data. The first method looks at variable selection to show the usefulness of sequential classification and regression trees to more …
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On the Use of Covariates in a Latent Class Signal Detection Model, with Applications to Constructed Response Scoring
A latent class signal detection (SDT) model was recently introduced as an alternative to traditional item response theory (IRT) methods in the analysis of constructed response data. This class of models can be represented as restricted latent class models and differ from the IRT approach in the way …
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Mental health and health care utilization among transition age youth
… survey data spanning a two-year period and latent class models to identify transition age youth (age 18 to 27) with persistent mental health problems, to identify their patterns of mental health and other medical care use, and to examine the socio-demographic and physical health correlates …
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Viewability prediction for display advertising
… in a specific page view. Two novel probabilistic latent class models (PLC) are proposed. The first PLC model computes constant use and page memberships offline, while the second PLC model computes dynamic memberships in real-time. In the second phase, ad viewability is predicted by estimating the …
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