Francis, Brian, Dittrich, Regina, Hatzinger, Reinhold, Humphreys, Leslie. 2014. A mixture model for longitudinal partially ranked data DOI:10.1080/03610926.2013.815779. Communications in Statistics. Theory and Methods 43 (4): 722-734.

RIS

@ARTICLE{Francis2014,
title = {A mixture model for longitudinal partially ranked data DOI:10.1080/03610926.2013.815779},
author = {Brian Francis and Regina Dittrich and Reinhold Hatzinger and Leslie Humphreys},
year = {2014},
url = {http://www.tandfonline.com/doi/abs/10.1080/03610926.2013.815779#.U2o4D4fmRaR},
volume = {43},
number = {4},
language = {EN},
pages = {722-734},
journal = {Communications in Statistics. Theory and Methods},
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},
}