A Mixture Model for Longitudinal Partially Ranked Data

被引:4
|
作者
Francis, Brian [1 ]
Dittrich, Regina [2 ]
Hatzinger, Reinhold [2 ]
Humphreys, Les [1 ]
机构
[1] Univ Lancaster, Dept Math & Stat, Lancaster LA1 4YF, England
[2] WU Vienna, Inst Stat & Math, Vienna, Austria
关键词
Bradley-Terry model; Latent class model; Mixture model; Nonparametric maximum likelihood; Paired comparisons; Partially ranked data; MAXIMUM-LIKELIHOOD;
D O I
10.1080/03610926.2013.815779
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This article 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 multi-valued 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.
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页码:722 / 734
页数:13
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