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Curvature Measures and Confidence Intervals for the Linear Logistic Model
Author(s) -
Ewijk P. H.,
Hoekstra J. A.
Publication year - 1994
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2986272
Subject(s) - curvature , confidence interval , measure (data warehouse) , mathematics , statistics , logistic regression , linear approximation , mathematical analysis , nonlinear system , geometry , physics , computer science , data mining , quantum mechanics
SUMMARY The curvature measures introduced by Bates and Watts and the subset curvature measure proposed by Cook and Goldberg were calculated for the linear logistic model and for the exponential model for a large number of data sets. In addition, likelihood ratio and linear approximation confidence intervals were calculated for one of the parameters in each model. The relationship between the subset curvature and the confidence intervals was studied. As others have found, the parameter effects curvature is in general much larger than the intrinsic curvature. The relationship between the subset curvature and the agreement between the two types of confidence interval which was expected turned out to be very poor. This sheds serious doubt on the usefulness of the subset curvature measure as a diagnostic tool for validating the linear approximation interval.