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A mixture model for longitudinal partially ranked data

Research output: Contribution to journalJournal article

Published

Journal publication date2014
JournalCommunications in Statistics - Theory and Methods
Journal number4
Volume43
Number of pages13
Pages722–734
Early online date27/01/14
Original languageEnglish

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

Bibliographic note

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