Influential data points in predictive logistic models

✍ Scribed by Aipore R. Moraes; Ian R. Dunsmore

• Book ID: 104638804
• Publisher: Springer US
• Year: 1996
• Tongue: English
• Weight: 510 KB
• Volume: 6
• Category: Article
• ISSN: 0960-3174
• DOI: 10.1007/bf00140870

✦ Synopsis

The influence of individual points in an ordinal logistic model is considered when the aim is to determine their effects on the predictive probability in a Bayesian predictive approach. Our concern is to study the effects produced when the data are slightly perturbed, in particular by observing how these perturbations will affect the predictive probabilities and consequently the classification of future cases. We consider the extent of the change in the predictive distribution when an individual point is omitted (deleted) from the sample by use of a divergence measure suggested by Johnson (1985) as a measure of discrepancy between the full data and the data with the case deleted. The methodology is illustrated on some data used in Titterington et al. (1981).