GLIM for Preference

Many types of multiple comparisons data can be described by multiplicative models, consequently GLIM can be used to fit log-linear models to such data, and to produce not only estimates of the parameters of interest, but also standard errors and tests of significance. Moreover as the data consists of counts the adequacy of the model can be tested in an objective way. Three examples from the literature are analysed, fitting the basic Bradley-Terry model and a modified Bradley-Terry model with ties and order effects. The parametrisation used in the case of ties is claimed to be more convenient than that of Fienberg. A test of linearity is also included.

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