Journal of Statistical Planning and Inference vol:143 issue:9 pages:1486-1499
Ordinal regression is used for modelling an ordinal response variable as a function of some
explanatory variables.The classical technique for estimating the unknown parameters of this model is Maximum Likelihood(ML). The lack of robustness of this estimator is
formally shown by deriving its breakdown point and its influence function. To robustify the procedure, a weighting step is added to the Maximum Likelihood estimator,yielding
an estimator with bounded influence function. We also show that the loss inefficiency due to the weighting step remains limited. A diagnostic plot based on the Weighted
Maximum Likelihood estimator allows to detect outliers of different types in a single plot.