Literature DB >> 10734288

Additive isotonic regression models in epidemiology.

T Morton-Jones1, P Diggle, L Parker, H O Dickinson, K Binks.   

Abstract

Stone's method for assessing disease risk around a point source through isotonic regression is routinely used in spatial epidemiology. It is useful in situations where the relationship of risk with exposure (distance being commonly used as a surrogate variable) is assumed monotonic but otherwise of unknown form. This paper extends this method to non-spatial epidemiology, where typically two or more risk factors are present. The methodology described is based on the additive isotonic model approach of Bacchetti; versions appropriate to count (Poisson) data and case-control (binomial) data are described. In both cases, adjustment for covariates is incorporated, and a Monte Carlo method of hypothesis testing and interval estimation is presented. The methodology is illustrated through a case-control example concerning the analysis of the possible effect of preconceptional external ionizing radiation doses on the sex ratio at birth among children of fathers working at the Sellafield nuclear installation, Cumbria, U.K. Copyright 2000 John Wiley & Sons, Ltd.

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Year:  2000        PMID: 10734288     DOI: 10.1002/(sici)1097-0258(20000330)19:6<849::aid-sim410>3.0.co;2-d

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  2 in total

1.  Stochastically ordered multiple regression.

Authors:  Björn Bornkamp; Katja Ickstadt; David Dunson
Journal:  Biostatistics       Date:  2010-02-11       Impact factor: 5.899

2.  A non-parametric framework for estimating threshold limit values.

Authors:  Georgia Salanti; Kurt Ulm
Journal:  BMC Med Res Methodol       Date:  2005-11-07       Impact factor: 4.615

  2 in total

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