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• W2031849069 abstract "A general framework is presented for the analysis of partially ordered set (poset) data. The work is motivated by the need to analyse poset data such as multi‐componential responses in psychological measurement and partially accomplished cognitive tasks in educational measurement. It is shown how the generalized loglinear model can be used to represent poset data that form a lattice and how latent‐variable models can be constructed by further specifying the canonical parameters of the loglinear representation. The approach generalizes a class of latent‐variable models for completely ordered data. We apply the methods to analyse data on the frequency and intensity of anger‐related feelings. Furthermore, we propose a trajectory analysis to gain insight into the response function of partially ordered emotional states." @default.
• W2031849069 created "2016-06-24" @default.
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• W2031849069 date "2005-05-01" @default.
• W2031849069 modified "2023-10-17" @default.
• W2031849069 title "Latent variable models for partially ordered responses and trajectory analysis of anger-related feelings" @default.
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• W2031849069 doi "https://doi.org/10.1348/000711005x38555" @default.
• W2031849069 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/15969843" @default.
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