Finite Mixture Models with Concomitant Information: Assessing Diagnostic Criteria for Diabetes
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Publication:4216154
DOI10.1111/1467-9876.00117zbMath0905.62112OpenAlexW2052026430MaRDI QIDQ4216154
James P. Boyle, Philip J. Smith, Theodore J. Thompson
Publication date: 1 February 1999
Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/1467-9876.00117
Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)
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Extending finite mixtures of \(t\) linear mixed-effects models with concomitant covariates ⋮ Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm. ⋮ Two-stage hierarchical modeling for analysis of subpopulations in conditional distributions ⋮ Inference for serological surveys investigating past exposures to infections resulting in long-lasting immunity – an approach using finite mixture models with concomitant information ⋮ Finite mixture regression model with random effects: application to neonatal hospital length of stay ⋮ Covariate selection in mixture models with the censored response variable ⋮ Gaussian parsimonious clustering models with covariates and a noise component ⋮ Estimating the number of components in finite mixture models via the group-sort-fuse procedure ⋮ Mixtures of factor analyzers: an extension with covariates ⋮ A panel data model of length of stay in hospitals for hip replacements
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