Estimation of spatial variation in risk using matched case-control data

Mikala F. Jarner; Peter J. Diggle; Amanda G. Chetwynd

doi:10.1002/bimj.200290005

Estimation of spatial variation in risk using matched case-control data

Mikala F. Jarner, Peter J. Diggle, Amanda G. Chetwynd

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

A common problem in environmental epidemiology is to estimate spatial variation in disease risk after accounting for known risk factors. In this paper we consider this problem in the context of matched case-control studies. We extend the generalised additive model approach of KELSALL and DIGGLE (1998) to studies in which each case has been individually matched to a set of controls. We discuss a method for fitting this model to data, apply the method to a matched study on perinatal death in the North West Thames region of England and explain why, if spatial variation is of particular scientific interest, matching is undesirable.

Original language	English (US)
Pages (from-to)	936-945
Number of pages	10
Journal	Biometrical Journal
Volume	44
Issue number	8
DOIs	https://doi.org/10.1002/bimj.200290005
State	Published - 2002
Externally published	Yes

Keywords

Epidemiology
Generalised additive models
Matched case-control design
Spatial variation in risk

ASJC Scopus subject areas

Statistics and Probability

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10.1002/bimj.200290005

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abstract = "A common problem in environmental epidemiology is to estimate spatial variation in disease risk after accounting for known risk factors. In this paper we consider this problem in the context of matched case-control studies. We extend the generalised additive model approach of KELSALL and DIGGLE (1998) to studies in which each case has been individually matched to a set of controls. We discuss a method for fitting this model to data, apply the method to a matched study on perinatal death in the North West Thames region of England and explain why, if spatial variation is of particular scientific interest, matching is undesirable.",

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AU - Diggle, Peter J.

AU - Chetwynd, Amanda G.

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N2 - A common problem in environmental epidemiology is to estimate spatial variation in disease risk after accounting for known risk factors. In this paper we consider this problem in the context of matched case-control studies. We extend the generalised additive model approach of KELSALL and DIGGLE (1998) to studies in which each case has been individually matched to a set of controls. We discuss a method for fitting this model to data, apply the method to a matched study on perinatal death in the North West Thames region of England and explain why, if spatial variation is of particular scientific interest, matching is undesirable.

AB - A common problem in environmental epidemiology is to estimate spatial variation in disease risk after accounting for known risk factors. In this paper we consider this problem in the context of matched case-control studies. We extend the generalised additive model approach of KELSALL and DIGGLE (1998) to studies in which each case has been individually matched to a set of controls. We discuss a method for fitting this model to data, apply the method to a matched study on perinatal death in the North West Thames region of England and explain why, if spatial variation is of particular scientific interest, matching is undesirable.

KW - Epidemiology

KW - Generalised additive models

KW - Matched case-control design

KW - Spatial variation in risk

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JO - Biometrical Journal

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Estimation of spatial variation in risk using matched case-control data

Abstract

Keywords

ASJC Scopus subject areas

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