Abstract
We consider the Babington Smith and Bradley-Terry Models for ranked data. Both models are based on inversions. In a matched pairs design the pair-specific nuisance parameters are eliminated by a conditioning argument. The conditional likelihood has a form similar to that of a logistic model, so that conditional likelihood computations are straight-forward. An example previously considered by Critchlow and Verducci is analysed using the new method.
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© 1993 Springer-Verlag New York, Inc.
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McCullagh, P., Ye, J. (1993). Matched Pairs and Ranked Data. In: Fligner, M.A., Verducci, J.S. (eds) Probability Models and Statistical Analyses for Ranking Data. Lecture Notes in Statistics, vol 80. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2738-0_18
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DOI: https://doi.org/10.1007/978-1-4612-2738-0_18
Publisher Name: Springer, New York, NY
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