Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics. / Bustami, R; Lesaffre, E; Molenberghs, G; Loos, R; Danckaerts, M; Vlietinck, R.

In: Statistics in Medicine, Vol. 20, No. 12, 30.06.2001, p. 1825-42.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Bustami, R, Lesaffre, E, Molenberghs, G, Loos, R, Danckaerts, M & Vlietinck, R 2001, 'Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics', Statistics in Medicine, vol. 20, no. 12, pp. 1825-42. https://doi.org/10.1002/sim.793

APA

Bustami, R., Lesaffre, E., Molenberghs, G., Loos, R., Danckaerts, M., & Vlietinck, R. (2001). Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics. Statistics in Medicine, 20(12), 1825-42. https://doi.org/10.1002/sim.793

Vancouver

Bustami R, Lesaffre E, Molenberghs G, Loos R, Danckaerts M, Vlietinck R. Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics. Statistics in Medicine. 2001 Jun 30;20(12):1825-42. https://doi.org/10.1002/sim.793

Author

Bustami, R ; Lesaffre, E ; Molenberghs, G ; Loos, R ; Danckaerts, M ; Vlietinck, R. / Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics. In: Statistics in Medicine. 2001 ; Vol. 20, No. 12. pp. 1825-42.

Bibtex

@article{08fb0cf8929340118903510a8ecebe97,
title = "Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics",
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.",
keywords = "Adolescent, Child, Child Behavior/physiology, Diabetic Retinopathy/epidemiology, Female, Humans, Likelihood Functions, Logistic Models, Male, Models, Biological, Models, Genetic, Models, Statistical, Risk Factors, Statistics, Nonparametric, Twin Studies as Topic",
author = "R Bustami and E Lesaffre and G Molenberghs and R Loos and M Danckaerts and R Vlietinck",
note = "Copyright 2001 John Wiley & Sons, Ltd.",
year = "2001",
month = jun,
day = "30",
doi = "10.1002/sim.793",
language = "English",
volume = "20",
pages = "1825--42",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "JohnWiley & Sons Ltd",
number = "12",

}

RIS

TY - JOUR

T1 - Modelling bivariate ordinal responses smoothly with examples from ophthalmology and genetics

AU - Bustami, R

AU - Lesaffre, E

AU - Molenberghs, G

AU - Loos, R

AU - Danckaerts, M

AU - Vlietinck, R

N1 - Copyright 2001 John Wiley & Sons, Ltd.

PY - 2001/6/30

Y1 - 2001/6/30

N2 - 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.

AB - 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.

KW - Adolescent

KW - Child

KW - Child Behavior/physiology

KW - Diabetic Retinopathy/epidemiology

KW - Female

KW - Humans

KW - Likelihood Functions

KW - Logistic Models

KW - Male

KW - Models, Biological

KW - Models, Genetic

KW - Models, Statistical

KW - Risk Factors

KW - Statistics, Nonparametric

KW - Twin Studies as Topic

U2 - 10.1002/sim.793

DO - 10.1002/sim.793

M3 - Journal article

C2 - 11406844

VL - 20

SP - 1825

EP - 1842

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 12

ER -

ID: 258040802