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Assessing Goodness of Fit of Ranking Models to Data
Ayala Cohen and C. L. Mallows
Journal of the Royal Statistical Society. Series D (The Statistician)
Vol. 32, No. 4 (Dec., 1983), pp. 361-374
Stable URL: http://www.jstor.org/stable/2987538
Page Count: 14
You can always find the topics here!Topics: Statistical models, Parametric models, Logistics, Goodness of fit, Maximum likelihood estimators, Datasets, Data models, Probabilities, Maximum likelihood estimation, Correlations
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We consider the analysis of N observed rankings on k objects. We present several approaches to test the goodness of fit of ranking models to such data. We show how different tests can highlight different features of the data. We refer to three particular ranking models: the Thurstone-Mosteller-Daniels model, the phi-model and the logistic model. The phi-model has been first introduced by Mallows. The logistic model has been derived by Plackett. We distinguish between ranking data with a small and with a large number of ranked items. The methods we propose for assessing the fit are illustrated on three examples.
Journal of the Royal Statistical Society. Series D (The Statistician) © 1983 Royal Statistical Society