Spatial Relative Risk of Upper Aerodigestive Tract Cancers Incidence in French Northern Region

被引：0

作者：

Dabo-Niang S. ^{[1
]}

Darwich E. ^{[2
]}

Hamdad L. ^{[3
]}

Thiam B. ^{[4
]}

机构：

[1] Université de Lille, CNRS, UMR 8524-Laboratoire Paul Painlevé, INRIA-MODAL, Lille

[2] Université de Lille, IUT, Lille

[3] Ecole nationale Supérieure en Informatique (ESI), Laboratoire LCSI, BP 68M, Oued El Smar, El Harrach

[4] Université de Lille, CNRS, UMR 8524-Laboratoire Paul Painlevé, Lille

来源：

SN Computer Science | / 4卷 / 1期

基金：

澳大利亚研究理事会;

关键词：

Cancer; Kernel spatial estimate; Relative risk function; UADT;

D O I：

10.1007/s42979-022-01426-0

中图分类号：

学科分类号：

摘要：

In this work, kernel spatial relative risk function estimation is of interest. We consider the case where covariates that may affect the spatial patterns of disease are contaminated by measurement errors. Finite sample properties were carried out in order to illustrate our methodology with real cancer data. We perform relative risk functions estimation on upper aerodigestive tract cancer (UADT) data to investigate locations of high and low incidence concentration in NPDC (Nord-Pas-de-Calais) French region. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

引用

共 29 条

[1]

Davies T.M., Hazelton M.L., Adaptive kernel estimation of spatial relative risk, Stat Med, 29, 23, pp. 2423-2437, (2010)

[2]

Kelsall J.E., Diggle P.J., Spatial variation in risk of disease: a nonparametric binary regression approach, J R Stat Soc: Ser C (Appl Stat), 47, 4, pp. 559-573, (1998)

[3]

Hazelton M.L., Testing for changes in spatial relative risk, Stat Med, 36, 17, pp. 2735-2749, (2017)

[4]

Kelsall J.E., Diggle P.J., Kernel estimation of relative risk, Bernoulli, 1, 1-2, pp. 3-16, (1995)

[5]

Davies T.M., Jones K., Hazelton M.L., Symmetric adaptive smoothing regimens for estimation of the spatial relative risk function, Comput Statist Data Anal, 101, pp. 12-28, (2016)

[6]

Borchers D., Buckland S., Priede I., Ahmadi S., Improving the precision of the daily egg production method using generalized additive models, Can J Fish Aquat Sci, 54, 12, pp. 2727-2742, (1997)

[7]

Bellido J., Pierce G., Wang J., Modelling intra-annual variation in abundance of squid loligo forbesi in scottish waters using generalised additive models, Fish Res, 52, 1, pp. 23-39, (2001)

[8]

Zheng X., Pierce G., Reid D., Jolliffe I., Does the north atlantic current affect spatial distribution of whiting? testing environmental hypotheses using statistical and gis techniques, ICES J Mar Sci: J du Conseil, 59, 2, pp. 239-253, (2002)

[9]

Ozonoff A., Webster T., Vieira V., Weinberg J., Ozonoff D., Aschengrau A., Cluster detection methods applied to the upper cape cod cancer data, Environ Health, 4, 1, (2005)

[10]

Diggle P.J., Giorgi E., Model-based geostatistics for prevalence mapping in low-resource settings, J Am Stat Assoc, 111, 515, pp. 1096-1120, (2016)

← 1 2 3 →