Estimation of non‐parametric multivariate risk functions in matched case‐control studies with application to the assessment of interactions of risk factors in the study of cancer
- 29 May 2001
- journal article
- Published by Wiley in Statistics in Medicine
- Vol. 20 (11) , 1639-1662
- https://doi.org/10.1002/sim.905
Abstract
In epidemiological studies one is interested in investigating the probability of disease depending on risk factors and in particular in detecting interactions of risk factors. Within the setting of parametric logistic regression, interactions can be modelled only in a clumsy and limited way. Modelling the risk function non‐parametrically, estimating it, for example, by a smoothing (thin plate) spline is attractive as a more explorative approach. For prospective studies this amounts to smoothing within the framework and distributional assumptions of generalized regression models (for binary observations). Case‐control studies as retrospective studies with exposure to risk factors being observed do not immediately fit into this setting. In the special case of one‐to‐one matched studies, however, there is an appropriate likelihood again within the range of generalized models. Inferences will be illustrated using simulated and real data. Copyright © 2001 John Wiley & Sons, Ltd.Keywords
This publication has 24 references indexed in Scilit:
- USING SMOOTHING SPLINE ANOVA TO EXAMINE THE RELATION OF RISK FACTORS TO THE INCIDENCE AND PROGRESSION OF DIABETIC RETINOPATHYStatistics in Medicine, 1997
- Odds ratio estimation in Bernoulli smoothing spline analysis- of-variance modelsJournal of the Royal Statistical Society: Series D (The Statistician), 1997
- Multivariate Statistical Modelling Based on Generalized Linear ModelsPublished by Springer Nature ,1994
- Nonparametric Regression and Generalized Linear ModelsPublished by Springer Nature ,1994
- Spline Models for Observational DataPublished by Society for Industrial & Applied Mathematics (SIAM) ,1990
- Making robust the cross-validatory choice of smoothing parameter in spline smoothing regressionCommunications in Statistics - Theory and Methods, 1989
- Nonparametric Estimation of Relative Risk Using Splines and Cross-ValidationSIAM Journal on Scientific and Statistical Computing, 1988
- GENERAL RELATIVE RISK REGRESSION MODELS FOR EPIDEMIOLOGIC STUDIES1American Journal of Epidemiology, 1987
- Automatic Smoothing of Regression Functions in Generalized Linear ModelsJournal of the American Statistical Association, 1986
- General Relative-Risk Models for Survival Time and Matched Case-Control AnalysisPublished by JSTOR ,1981