IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i8p2843-2850.html
   My bibliography  Save this article

A flexible spatial scan test for case event data

Author

Listed:
  • Cucala, Lionel

Abstract

A new method is proposed for identifying clusters in spatial point processes. It relies on a specific ordering of events and the definition of area spacings which have the same distribution as one-dimensional spacings. Then the spatial clusters are detected using a scan statistic adapted to the analysis of one-dimensional point processes. This flexible spatial scan test seems to be very powerful against any arbitrarily-shaped cluster alternative. These results have applications in epidemiological studies of rare diseases.

Suggested Citation

  • Cucala, Lionel, 2009. "A flexible spatial scan test for case event data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2843-2850, June.
  • Handle: RePEc:eee:csdana:v:53:y:2009:i:8:p:2843-2850
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00471-4
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter J. Diggle & Barry S. Rowlingson, 1994. "A Conditional Approach to Point Process Modelling of Elevated Risk," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 157(3), pages 433-440, May.
    2. Peter J. Diggle, 1990. "A Point Process Modelling Approach to Raised Incidence of a Rare Phenomenon in the Vicinity of a Prespecified Point," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 153(3), pages 349-362, May.
    3. Duczmal, Luiz & Cancado, Andre L.F. & Takahashi, Ricardo H.C. & Bessegato, Lupercio F., 2007. "A genetic algorithm for irregularly shaped spatial scan statistics," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 43-52, September.
    4. Demattei[diaeresis], Christophe & Molinari, Nicolas & Daures, Jean-Pierre, 2007. "Arbitrarily shaped multiple spatial cluster detection for case event data," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3931-3945, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wan, You & Pei, Tao & Zhou, Chenghu & Jiang, Yong & Qu, Chenxu & Qiao, Youlin, 2012. "ACOMCD: A multiple cluster detection algorithm based on the spatial scan statistic and ant colony optimization," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 283-296.
    2. LeSage, James & Banerjee, Sudipto & Fischer, Manfred M. & Congdon, Peter, 2009. "Spatial statistics: Methods, models & computation," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2781-2785, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wan, You & Pei, Tao & Zhou, Chenghu & Jiang, Yong & Qu, Chenxu & Qiao, Youlin, 2012. "ACOMCD: A multiple cluster detection algorithm based on the spatial scan statistic and ant colony optimization," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 283-296.
    2. S P Kingham & A C Gatrell & B Rowlingson, 1995. "Testing for Clustering of Health Events within a Geographical Information System Framework," Environment and Planning A, , vol. 27(5), pages 809-821, May.
    3. Hossain, Md. Monir & Lawson, Andrew B., 2009. "Approximate methods in Bayesian point process spatial models," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2831-2842, June.
    4. Alexandre Rodrigues & Peter Diggle & Renato Assuncao, 2010. "Semiparametric approach to point source modelling in epidemiology and criminology," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(3), pages 533-542, May.
    5. Martin L. Hazelton & Tilman M. Davies, 2022. "Pointwise comparison of two multivariate density functions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1791-1810, December.
    6. Davies, Tilman M. & Jones, Khair & Hazelton, Martin L., 2016. "Symmetric adaptive smoothing regimens for estimation of the spatial relative risk function," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 12-28.
    7. Lawson, Andrew B. & Simeon, Silvia & Kulldorff, Martin & Biggeri, Annibale & Magnani, Corrado, 2007. "Line and point cluster models for spatial health data," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6027-6043, August.
    8. Inkyung Jung, 2019. "Spatial scan statistics for matched case-control data," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-10, August.
    9. Silva, Ivair R. & Duczmal, Luiz & Kulldorff, Martin, 2021. "Confidence intervals for spatial scan statistic," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    10. Peter J. Diggle & Barry S. Rowlingson, 1994. "A Conditional Approach to Point Process Modelling of Elevated Risk," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 157(3), pages 433-440, May.
    11. LeSage, James & Banerjee, Sudipto & Fischer, Manfred M. & Congdon, Peter, 2009. "Spatial statistics: Methods, models & computation," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2781-2785, June.
    12. Carl Schmertmann & Renato Assunção & Joseph Potter, 2010. "Knox meets Cox: Adapting epidemiological space-time statistics to demographic studies," Demography, Springer;Population Association of America (PAA), vol. 47(3), pages 629-650, August.
    13. Davidson, Marty, 2024. "Strategic Point Processes," OSF Preprints g5r9t, Center for Open Science.
    14. Xiaolan Wu & Tony Grubesic, 2010. "Identifying irregularly shaped crime hot-spots using a multiobjective evolutionary algorithm," Journal of Geographical Systems, Springer, vol. 12(4), pages 409-433, December.
    15. Wei Wang & Sheng Li & Tao Zhang & Fei Yin & Yue Ma, 2023. "Detecting the spatial clustering of exposure–response relationships with estimation error: a novel spatial scan statistic," Biometrics, The International Biometric Society, vol. 79(4), pages 3522-3532, December.
    16. Dale L. Zimmerman, 2008. "Estimating the Intensity of a Spatial Point Process from Locations Coarsened by Incomplete Geocoding," Biometrics, The International Biometric Society, vol. 64(1), pages 262-270, March.
    17. Xiaojian Yi & Peng Hou & Haiping Dong, 2020. "A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks," Energies, MDPI, vol. 13(6), pages 1-15, March.
    18. de Lima, Max Sousa & Duczmal, Luiz Henrique, 2014. "Adaptive likelihood ratio approaches for the detection of space–time disease clusters," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 352-370.
    19. Paciorek, Christopher J., 2007. "Computational techniques for spatial logistic regression with large data sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3631-3653, May.
    20. A C Gatrell & C E Dunn & P J Boyle, 1991. "The Relative Utility of the Central Postcode Directory and Pinpoint Address Code in Applications of Geographical Information Systems," Environment and Planning A, , vol. 23(10), pages 1447-1458, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:53:y:2009:i:8:p:2843-2850. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.