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Additive isotonic models in epidemiology.

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Additive isotonic models in epidemiology. / Morton-Jones, A. J.; Diggle, Peter J.; Parker, L. et al.
In: Statistics in Medicine, Vol. 19, No. 6, 2000, p. 849-859.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Morton-Jones, AJ, Diggle, PJ, Parker, L, Dickinson, HO & Binks, K 2000, 'Additive isotonic models in epidemiology.', Statistics in Medicine, vol. 19, no. 6, pp. 849-859. https://doi.org/10.1002/(SICI)1097-0258(20000330)19:6<849::AID-SIM410>3.0.CO;2-D

APA

Morton-Jones, A. J., Diggle, P. J., Parker, L., Dickinson, H. O., & Binks, K. (2000). Additive isotonic models in epidemiology. Statistics in Medicine, 19(6), 849-859. https://doi.org/10.1002/(SICI)1097-0258(20000330)19:6<849::AID-SIM410>3.0.CO;2-D

Vancouver

Morton-Jones AJ, Diggle PJ, Parker L, Dickinson HO, Binks K. Additive isotonic models in epidemiology. Statistics in Medicine. 2000;19(6):849-859. doi: 10.1002/(SICI)1097-0258(20000330)19:6<849::AID-SIM410>3.0.CO;2-D

Author

Morton-Jones, A. J. ; Diggle, Peter J. ; Parker, L. et al. / Additive isotonic models in epidemiology. In: Statistics in Medicine. 2000 ; Vol. 19, No. 6. pp. 849-859.

Bibtex

@article{3cdbba0a31524ea5808135f681331aae,
title = "Additive isotonic models in epidemiology.",
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.",
author = "Morton-Jones, {A. J.} and Diggle, {Peter J.} and L. Parker and Dickinson, {H. O.} and K. Binks",
year = "2000",
doi = "10.1002/(SICI)1097-0258(20000330)19:6<849::AID-SIM410>3.0.CO;2-D",
language = "English",
volume = "19",
pages = "849--859",
journal = "Statistics in Medicine",
issn = "1097-0258",
publisher = "John Wiley and Sons Ltd",
number = "6",

}

RIS

TY - JOUR

T1 - Additive isotonic models in epidemiology.

AU - Morton-Jones, A. J.

AU - Diggle, Peter J.

AU - Parker, L.

AU - Dickinson, H. O.

AU - Binks, K.

PY - 2000

Y1 - 2000

N2 - 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.

AB - 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.

U2 - 10.1002/(SICI)1097-0258(20000330)19:6<849::AID-SIM410>3.0.CO;2-D

DO - 10.1002/(SICI)1097-0258(20000330)19:6<849::AID-SIM410>3.0.CO;2-D

M3 - Journal article

VL - 19

SP - 849

EP - 859

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 1097-0258

IS - 6

ER -