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    Rights statement: 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

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A mixture model for longitudinal partially ranked data

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A mixture model for longitudinal partially ranked data. / Francis, Brian; Dittrich, Regina; Hatzinger, Reinhold et al.
In: Communications in Statistics - Theory and Methods, Vol. 43, No. 4, 2014, p. 722–734.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Francis, B, Dittrich, R, Hatzinger, R & Humphreys, L 2014, 'A mixture model for longitudinal partially ranked data', Communications in Statistics - Theory and Methods, vol. 43, no. 4, pp. 722–734. https://doi.org/10.1080/03610926.2013.815779

APA

Francis, B., Dittrich, R., Hatzinger, R., & Humphreys, L. (2014). A mixture model for longitudinal partially ranked data. Communications in Statistics - Theory and Methods, 43(4), 722–734. https://doi.org/10.1080/03610926.2013.815779

Vancouver

Francis B, Dittrich R, Hatzinger R, Humphreys L. A mixture model for longitudinal partially ranked data. Communications in Statistics - Theory and Methods. 2014;43(4):722–734. Epub 2014 Jan 27. doi: 10.1080/03610926.2013.815779

Author

Francis, Brian ; Dittrich, Regina ; Hatzinger, Reinhold et al. / A mixture model for longitudinal partially ranked data. In: Communications in Statistics - Theory and Methods. 2014 ; Vol. 43, No. 4. pp. 722–734.

Bibtex

@article{ebcff0f0a9ec4c1685492cc5de05b6ed,
title = "A mixture model for longitudinal partially ranked data",
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 sweepsof the British Household Panel Survey",
keywords = "Partially ranked data, Mixture model, Bradley-Terry model, Paired comparisons, Latent class model, Nonparametric maximum likelihood",
author = "Brian Francis and Regina Dittrich and Reinhold Hatzinger and Leslie Humphreys",
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",
year = "2014",
doi = "10.1080/03610926.2013.815779",
language = "English",
volume = "43",
pages = "722–734",
journal = "Communications in Statistics - Theory and Methods",
issn = "0361-0926",
publisher = "Taylor and Francis Ltd.",
number = "4",

}

RIS

TY - JOUR

T1 - A mixture model for longitudinal partially ranked data

AU - Francis, Brian

AU - Dittrich, Regina

AU - Hatzinger, Reinhold

AU - Humphreys, Leslie

N1 - 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

PY - 2014

Y1 - 2014

N2 - 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 sweepsof the British Household Panel Survey

AB - 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 sweepsof the British Household Panel Survey

KW - Partially ranked data

KW - Mixture model

KW - Bradley-Terry model

KW - Paired comparisons

KW - Latent class model

KW - Nonparametric maximum likelihood

U2 - 10.1080/03610926.2013.815779

DO - 10.1080/03610926.2013.815779

M3 - Journal article

VL - 43

SP - 722

EP - 734

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

SN - 0361-0926

IS - 4

ER -