A mixture model for longitudinal partially ranked data

Francis, Brian and Dittrich, Regina and Hatzinger, Reinhold and Humphreys, Leslie (2014) A mixture model for longitudinal partially ranked data. Communications in Statistics - Theory and Methods, 43 (4). 722–734. ISSN 0361-0926

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Abstract

This paper discusses the use of mixture models in the analysis of longitudinal partially ranked data, where respondents, for example, choose only the preferred and second preferred out of a set of items. To model such data we convert it to a set of paired comparisons. Covariates can be incorporated into the model. We use a nonparametric mixture to account for unmeasured variability in individuals over time. The resulting multivalued mass points can be interpreted as latent classes of the items. The work is illustrated by two questions on (post)materialism in three sweeps of the British Household Panel Survey

Item Type:
Journal Article
Journal or Publication Title:
Communications in Statistics - Theory and Methods
Additional Information:
This is an Author's Accepted Manuscript of an article published in A Mixture Model for Longitudinal Partially Ranked Data DOI:10.1080/03610926.2013.815779 Brian Francisa, Regina Dittrich, Reinhold Hatzinger & Les Humphreys pages 722-734 in Communications in Statistics - Theory and Methods 2014 copyright Taylor & Francis, available online at: http://www.tandfonline.com/doi/abs/10.1080/03610926.2013.815779
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
65643
Deposited By:
Deposited On:
09 Jul 2013 09:16
Refereed?:
Yes
Published?:
Published
Last Modified:
25 Oct 2020 02:26