Titlebook: Statistical Methods for Ranking Data; Mayer Alvo,Philip L.H. Yu Book 2014 Springer Science+Business Media New York 2014 Block designs.Expl

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Decision Tree Models for Ranking Data,are only a few diagnostic procedures available to determine whether a satisfactory model is found. For instance, is it necessary to transform some of the covariates? Which variables or interaction terms should be included into the model?

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Extension of Distance-Based Models for Ranking Data,nkings as previously noted. Recently, Lee and Yu (2012) proposed new distance-based models by using weighted distance measures to allow different weights for different ranks. In this way, the properties of distance can be retained while at the same time enhancing the model flexibility.

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Testing for Randomness, Agreement, and Interaction,dom manner, the points would tend to cluster close together in one or more groups. Intuitively then, a test of randomness could be based on the average pairwise distance between points with large values of that statistic displaying evidence of the random pattern of the points.

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Block Designs,compatibility and the extended notion of distance between rankings. This approach provides a natural extension of the well-known Friedman and Durbin statistics to some partially balanced incomplete designs. The tests developed are also applicable to general block designs with ties and multiple observations per cell.

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