Latent variable models for partially ordered responses and trajectory analysis of anger-related feelings
Authors: Meulders, Michel1; Ip, Edward H.2; De Boeck, Paul1
Source: British Journal of Mathematical and Statistical Psychology, Volume 58, Number 1, May 2005 , pp. 117-143(27)
Publisher: British Psychological Society
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- In this Subject: Mathematics and Statistics , Psychology
- By this author: Meulders, Michel ; Ip, Edward H. ; De Boeck, Paul
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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.Document Type: Research article
DOI: 10.1348/000711005X38555
Affiliations: 1: Department of Psychology, University of Leuven, Belgium 2: Biostatistics and Social Sciences and Health Policy, Wake Forest University School of Medicine, USA
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