Agenda

28 Feb 2018 11:00

Factor copula models for item response data

Campus Scientifico via Torino - edificio ZETA, Sala Riunioni A

Aristidis K Nikoloulopoulos, School of Computing Sciences, University of East Anglia

Abstract:
Factor or conditional independence models based on copulas are proposed for multivariate discrete data such as item response. The factor copula models have interpretations of latent maxima/minima (in comparison with latent means) and can lead to more probability in the joint upper and/or lower tail compared with factor models based on the discretized multivariate normal distribution (or multidimensional normal ogive model). Details on maximum likelihood estimation of parameters for the factor copula model are given, as well as analysis of the behavior of the log-likelihood. Our general methodology is illustrated with several item response data sets and it is shown that there is a substantial improvement on existing models from the criteria of log-likelihood and goodness-of-fit. This talk will be based on collaborative work with Harry Joe (U. of British Columbia).

Lingua

L'evento si terrà in italiano

Organizzatore

Cristiano Varin

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