Results 291 to 300 of about 543,991 (343)
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Biometrics, 2000
Summary.In many areas of medical research, such as psychiatry and gerontology, latent class variables are used to classify individuals into disease categories, often with the intention of hierarchical modeling. Problems arise when it is not clear how many disease classes are appropriate, creating a need for model selection and diagnostic techniques ...
Garrett, Elizabeth S., Zeger, Scott L.
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Summary.In many areas of medical research, such as psychiatry and gerontology, latent class variables are used to classify individuals into disease categories, often with the intention of hierarchical modeling. Problems arise when it is not clear how many disease classes are appropriate, creating a need for model selection and diagnostic techniques ...
Garrett, Elizabeth S., Zeger, Scott L.
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Advances in Data Analysis and Classification, 2013
The paper proposes a latent class version of Combination of Uniform and (shifted) Binomial random variables ( CUB ) models for ordinal data to account for unobserved heterogeneity. The extension, called LC-CUB , is useful when the heterogeneity is originated by clusters of respondents not identified by covariates: this may generate a multimodal ...
GRILLI, LEONARDO +3 more
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The paper proposes a latent class version of Combination of Uniform and (shifted) Binomial random variables ( CUB ) models for ordinal data to account for unobserved heterogeneity. The extension, called LC-CUB , is useful when the heterogeneity is originated by clusters of respondents not identified by covariates: this may generate a multimodal ...
GRILLI, LEONARDO +3 more
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2010
A statistical model can be called a latent class (LC) or mixture model if it assumes that some of its parameters differ across unobserved subgroups, LCs, or mixture components. This rather general idea has several seemingly unrelated applications, the most important of which are clustering, scaling, density estimation, and random-effects modeling. This
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A statistical model can be called a latent class (LC) or mixture model if it assumes that some of its parameters differ across unobserved subgroups, LCs, or mixture components. This rather general idea has several seemingly unrelated applications, the most important of which are clustering, scaling, density estimation, and random-effects modeling. This
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Structural Latent Class Models
Sociological Methods & Research, 1998Linear logistic latent class analysis (LCA) relates the item latent probabilities of LCA to basic parameters representing the effects of explanatory variables. Applications of this model to dichotomous data comprise paired comparisons (the compared objects are the explanatory variables); the measurement of change due to, for example, therapeutic ...
ANTON K. FORMANN, THOMAS KOHLMANN
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The latent class multitrait-multimethod model.
Psychological Methods, 2015A latent class multitrait-multimethod (MTMM) model is proposed to estimate random and systematic measurement error in categorical survey questions while making fewer assumptions than have been made so far in such evaluations, allowing for possible extreme response behavior and other nonmonotone effects.
Oberski, D.L. +2 more
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Dirichlet Generalizations of Latent-Class Models
Journal of Classification, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Potthoff, Richard F. +2 more
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Multilevel Latent Class Modelling
2012In Chap. 5 we introduced multilevel modelling, where a continuous latent variable represents variation across the levels of a natural hierarchy, yielding random effects. In Chap. 6, we introduced latent class analysis, where using a binary latent variable gave rise to a mixture model of count data to accommodate an excess of zeros relative to standard ...
Wendy Harrison +3 more
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Mixed Markov Latent Class Models
Sociological Methodology, 1990The process of change in a discrete characteristic is seldom the same for every respondent in a panel survey. Mixed Markov latent class models describe cross-tables of consecutive measurements in terms of several Markov chains. Each of these chains may be a stayer chain or some kind of mover chain. Markov chains may or may not be latent; i.e., they may
Frank van de Pol, Rolf Langeheine
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Bootstrapping Latent Class Models
2005This paper deals with improved measures of statistical accuracy for parameter estimates of latent class models. It introduces more precise confidence intervals for the parameters of this model, based on parametric and nonparametric bootstrap. Moreover, the label-switching problem is discussed and a solution to handle it introduced.
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Inequality Constrained Latent Class Models
2008This chapter deals with inequality constrained latent class analysis. As will be exemplified, researchers often have competing theories that can be translated into inequality constrained latent class models. After this translation it is rather straightforward to evaluate these theories.
Hoijtink, H.J.A., Boom, J.
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