Rank-Ordered Logit Model With Ties
Key aspects of the model are:
- Its intepretation is identical to that of the Multinomial Logit Model. That is, the parameters have the same intepretation and predictions are made in the same way (e.g., a Choice Simulator can be constructed from the rank-ordered logit model with ties).
- The Dependent Variable is assumed to be a ranking, where ties are permitted (i.e., a partial ranking).
Computation of the log-likelihood
The model assumes that all possible rankings consistent with the an observed ranking containing ties are equally likely. For example, if a respondent that has given the following ranking: C > A = B > D > A (i.e., where A and B are tied), then there are two possible rankings consistent with this data: C > A > B > D > A and C > B > A > D > A.
The likelihood is then computed as the average of all of the possible likelihoods, where the likelihood for a possible ranking is computed using same approach as employed with the Sequential Logit Model.
- Allison, P. D. and N. A. Christakis (1994). "Logit Models for Sets of Ranked Items." Sociological Methodology 24: 199-228.
- SAS (2008). The PHREG Procedure. SAS/STAT® 9.2 User’s Guide. Cary, NC, SAS Institute Inc.
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