IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v48y2005i4p679-684.html
   My bibliography  Save this article

Power comparisons for an improved disease clustering test

Author

Listed:
  • Ozonoff, Al
  • Bonetti, Marco
  • Forsberg, Laura
  • Pagano, Marcello

Abstract

No abstract is available for this item.

Suggested Citation

  • Ozonoff, Al & Bonetti, Marco & Forsberg, Laura & Pagano, Marcello, 2005. "Power comparisons for an improved disease clustering test," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 679-684, April.
    • Handle: RePEc:eee:csdana:v:48:y:2005:i:4:p:679-684
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(04)00099-4
    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. Kulldorff, Martin & Tango, Toshiro & Park, Peter J., 2003. "Power comparisons for disease clustering tests," Computational Statistics & Data Analysis, Elsevier, vol. 42(4), pages 665-684, April.
    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. Pei-Sheng Lin, 2014. "Generalized Scan Statistics for Disease Surveillance," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 791-808, September.
    2. 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.
    3. White, Laura Forsberg & Bonetti, Marco & Pagano, Marcello, 2009. "The choice of the number of bins for the M statistic," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3640-3649, August.

    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. HAEDO, Christian & MOUCHART , Michel & ,, 2013. "Specialized agglomerations with areal data: model and detection," LIDAM Discussion Papers CORE 2013060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. 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.
    3. Silva, Ivair R. & Duczmal, Luiz & Kulldorff, Martin, 2021. "Confidence intervals for spatial scan statistic," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    4. Rashidi, Parinaz & Wang, Tiejun & Skidmore, Andrew & Vrieling, Anton & Darvishzadeh, Roshanak & Toxopeus, Bert & Ngene, Shadrack & Omondi, Patrick, 2015. "Spatial and spatiotemporal clustering methods for detecting elephant poaching hotspots," Ecological Modelling, Elsevier, vol. 297(C), pages 180-186.
    5. Ibrahim Musa & Hyun Woo Park & Lkhagvadorj Munkhdalai & Keun Ho Ryu, 2018. "Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
    6. Fei He & Daniel R. Jeske & Elizabeth Grafton‐Cardwell, 2020. "Identifying high‐density regions of pests within an orchard," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(3), pages 417-431, May.
    7. 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.
    8. Pei-Sheng Lin, 2014. "Generalized Scan Statistics for Disease Surveillance," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 791-808, September.
    9. Costa, Marcelo Azevedo & Assunção, Renato Martins & Kulldorff, Martin, 2012. "Constrained spanning tree algorithms for irregularly-shaped spatial clustering," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1771-1783.
    10. Mohammad Meysami & Joshua P. French & Ettie M. Lipner, 2023. "Flexible-Elliptical Spatial Scan Method," Mathematics, MDPI, vol. 11(17), pages 1-22, August.
    11. William H. Woodall & J Brooke Marshall & Michael D. Joner Jr & Shannon E Fraker & Abdel‐Salam G Abdel‐Salam, 2008. "On the use and evaluation of prospective scan methods for health‐related surveillance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 223-237, January.
    12. White, Laura Forsberg & Bonetti, Marco & Pagano, Marcello, 2009. "The choice of the number of bins for the M statistic," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3640-3649, August.
    13. Zhang, Tonglin & Lin, Ge, 2009. "Spatial scan statistics in loglinear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2851-2858, June.
    14. Zhang, Tonglin & Lin, Ge, 2013. "On the limiting distribution of the spatial scan statistic," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 215-225.
    15. Porter, Michael D. & Brown, Donald E., 2007. "Detecting local regions of change in high-dimensional criminal or terrorist point processes," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2753-2768, February.
    16. Rhonda J. Rosychuk & Carolyn Huston & Narasimha G. N. Prasad, 2006. "Spatial Event Cluster Detection Using a Compound Poisson Distribution," Biometrics, The International Biometric Society, vol. 62(2), pages 465-470, June.
    17. 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.
    18. Zhanjun He & Rongqi Lai & Zhipeng Wang & Huimin Liu & Min Deng, 2022. "Comparative Study of Approaches for Detecting Crime Hotspots with Considering Concentration and Shape Characteristics," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    19. Trisalyn Nelson & Barry Boots, 2005. "Identifying insect infestation hot spots: an approach using conditional spatial randomization," Journal of Geographical Systems, Springer, vol. 7(3), pages 291-311, December.

    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:48:y:2005:i:4:p:679-684. 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.