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http://hdl.handle.net/1942/382
Title: | Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics | Authors: | Bustami, Rami LESAFFRE, Emmanuel MOLENBERGHS, Geert Loos, Ruth Danckaerts, Marina Vlietinck, Robert |
Issue Date: | 2001 | Publisher: | JOHN WILEY | Source: | Statistics in Medicine, 20(12). p. 1825-1842 | Abstract: | A non-parametric implementation of the bivariate Dale model (BDM) is presented as an extension of the generalized additive model (GAM) of Hastie and Tibshirani. The original BDM is an example of a bivariate generalized linear model. In this paper smoothing is introduced on the marginal as well as on the association level. Our non-parametric procedure can be used as a diagnostic tool for identifying parametric transformations of the covariates in the linear BDM, hence it also provides a kind of goodness-of-fit test for a bivariate generalized linear model. Cubic smoothing spline functions for the covariates are estimated by maximizing a penalized version of the log-likelihood. The method is applied to two studies. The first study is the classical Wisconsin Epidemiologic Study of Diabetic Retinopathy. The second study is a twin study, where the association between the elements of twin pairs is of primary interest. The results show that smoothing on the association level can give a significant improvement to the model fit. | Document URI: | http://hdl.handle.net/1942/382 | ISSN: | 0277-6715 | e-ISSN: | 1097-0258 | DOI: | 10.1002/sim.793 | ISI #: | 000169422100008 | Rights: | (C) 2001 John Wiley & Sons, Ltd. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2002 |
Appears in Collections: | Research publications |
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