A Mixture Model for Longitudinal Partially Ranked Data

作者：Francis Brian^*; Dittrich Regina; Hatzinger Reinhold; Humphreys Les

来源：Communications in Statistics - Theory and Methods, 2014, 43(4): 722-734.

DOI：10.1080/03610926.2013.815779

• Bradley-Terry model
• Latent class model
• Mixture model
• Nonparametric maximum likelihood
• Paired comparisons
• Partially ranked data

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.

• 出版日期2014-2-16