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Bayesian Latent Class Analysis: Sample Size, Model Size, and Classification Precision
Mathematics, 2023 The current literature includes limited information on the classification precision of Bayes estimation for latent class analysis (BLCA). (1) Objectives: The present study compared BLCA with the robust maximum likelihood (MLR) procedure, which is the ...
Diana Mindrila
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The Use of Loglinear Models for Assessing Differential Item Functioning Across Manifest and Latent Examinee Groups [PDF]
, 1990 Loglinear latent class models are used to detect differential item functioning (DIF). These models are formulated in such a manner that the attribute to be assessed may be continuous, as in a Rasch model, or categorical, as in Latent Class Mastery models.
Kelderman, Henk, Macready, George B.
core +4 more sources
Nested partially latent class models for dependent binary data; estimating disease etiology. [PDF]
Biostatistics, 2015 The Pneumonia Etiology Research for Child Health (PERCH) study seeks to use modern measurement technology to infer the causes of pneumonia for which gold-standard evidence is unavailable.
Zhenke Wu, Maria Deloria-Knoll, S. Zeger
semanticscholar +1 more source
glca: An R Package for Multiple-Group Latent Class Analysis
Applied Psychological Measurement, 2022 Group similarities and differences may manifest themselves in a variety of ways in multiple-group latent class analysis (LCA). Sometimes, measurement models are identical across groups in LCA.
Youngsung Kim +3 more
semanticscholar +1 more source
Patterns of physical activity in sedentary older individuals with type 2 diabetes
Clinical Diabetes and Endocrinology, 2018 Background The Community Healthy Activities Model Program for Seniors (CHAMPS) survey, summarized into weekly caloric expenditures, is a common physical activity (PA) assessment tool among older adults.
Pearl G. Lee +4 more
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A nested expectation-maximization algorithm for latent class models with covariates [PDF]
, 2018 We develop a nested EM routine for latent class models with covariates which allows maximization of the full-model log-likelihood and, differently from current methods, guarantees monotone log-likelihood sequences along with improved convergence ...
Canale, Antonio +2 more
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Latent trajectory studies: the basics, how to interpret the results, and what to report [PDF]
European Journal of Psychotraumatology, 2015 Background: In statistics, tools have been developed to estimate individual change over time. Also, the existence of latent trajectories, where individuals are captured by trajectories that are unobserved (latent), can be evaluated (Muthén & Muthén, 2000)
Rens van de Schoot
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JMIR Medical Informatics, 2022 BackgroundHealth care organizations are collecting increasing volumes of clinical text data. Topic models are a class of unsupervised machine learning algorithms for discovering latent thematic patterns in these large unstructured
Christopher Meaney +4 more
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Mixture Rasch Model with Main and Interaction Effects of Covariates on Latent Class Membership
International Journal of Assessment Tools in Education, 2019 Covariateshave been used in mixture IRT models to help explain why examinees are classedinto different latent classes. Previous research has considered manifestvariables as covariates in a mixture Rasch analysis for prediction of groupmembership.
Tugba Karadavut +2 more
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Frontiers in Psychology, 2020 The standard item response theory (IRT) model assumption of a single homogenous population may be violated in real data. Mixture extensions of IRT models have been proposed to account for latent heterogeneous populations, but these models are not ...
Sedat Sen, Allan S. Cohen
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