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On the modelling and estimation of attribute rankings with ties in the Thurstonian framework
Author(s) -
Poon WaiYin,
Xu Liang
Publication year - 2009
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1348/000711008x337703
Subject(s) - ranking (information retrieval) , monte carlo method , econometrics , differentiable function , maximization , process (computing) , statistics , differential (mechanical device) , computer science , mathematics , estimation , data mining , artificial intelligence , mathematical optimization , economics , engineering , mathematical analysis , management , aerospace engineering , operating system
A Thurstonian type approach is applied to modelling ranking data with ties. It uses a non‐totally differentiable discriminational process instead of the conventional totally differential one to relate the observed rankings and the underlying subjective values. A Monte Carlo expectation–maximization algorithm is proposed to find the maximum likelihood estimates together with the standard errors of the parameters. The approach is examined numerically by means of an artificial example and a simulation study and is applied to a study of attribute assessment.