IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v42y2003i4p665-684.html
   My bibliography  Save this article

Power comparisons for disease clustering tests

Author

Listed:
  • Kulldorff, Martin
  • Tango, Toshiro
  • Park, Peter J.

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:csdana:v:42:y:2003:i:4:p:665-684
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(02)00160-3
    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. Roger J. Marshall, 1991. "A Review of Methods for the Statistical Analysis of Spatial Patterns of Disease," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 154(3), pages 421-441, May.
    2. Julian Besag & James Newell, 1991. "The Detection of Clusters in Rare Diseases," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 154(1), pages 143-155, January.
    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. 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.
    2. 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.
    3. Zhang, Tonglin & Lin, Ge, 2009. "Spatial scan statistics in loglinear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2851-2858, June.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Silva, Ivair R. & Duczmal, Luiz & Kulldorff, Martin, 2021. "Confidence intervals for spatial scan statistic," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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.
    17. 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.
    18. Mohammad Meysami & Joshua P. French & Ettie M. Lipner, 2023. "Flexible-Elliptical Spatial Scan Method," Mathematics, MDPI, vol. 11(17), pages 1-22, August.
    19. 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.
    20. 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. Peter Congdon, 1997. "Multilevel and Clustering Analysis of Health Outcomes in Small Areas," European Journal of Population, Springer;European Association for Population Studies, vol. 13(4), pages 305-338, December.
    2. Johnston, Robert J. & Ramachandran, Mahesh & Schultz, Eric T. & Segerson, Kathleen & Besedin, Elena Y., 2011. "Characterizing Spatial Pattern in Ecosystem Service Values when Distance Decay Doesn’t Apply: Choice Experiments and Local Indicators of Spatial Association," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103374, Agricultural and Applied Economics Association.
    3. Papa Ousmane Cissé & Dominique Guégan & Abdou Kâ Diongue, 2018. "On parameters estimation of the Seasonal FISSAR Model," Documents de travail du Centre d'Economie de la Sorbonne 18018, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Bansal, Prateek & Krueger, Rico & Graham, Daniel J., 2021. "Fast Bayesian estimation of spatial count data models," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    5. repec:rri:wpaper:200506 is not listed on IDEAS
    6. Murat Yazici, 2017. "PSpatial Point Pattern Analyses and its Use in Geographical Epidemiology," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 1(5), pages 99-103, May.
    7. Tomoya Mori & Tony E. Smith, 2014. "A probabilistic modeling approach to the detection of industrial agglomerations," Journal of Economic Geography, Oxford University Press, vol. 14(3), pages 547-588.
    8. Ben Said FOUED, 2015. "Tunisian Coastal Cities Attractiveness And Amenities," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 10(3), pages 49-70, August.
    9. Tonglin Zhang & Ge Lin, 2008. "Identification of local clusters for count data: a model-based Moran's I test," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(3), pages 293-306.
    10. Tomoya Mori & Tony E. Smith, 2009. "A Reconsideration of the NAS Rule from an Industrial Agglomeration Perspective," KIER Working Papers 669, Kyoto University, Institute of Economic Research.
    11. Kristy Buzard & Gerald A. Carlino & Jake Carr & Robert M. Hunt & Tony E. Smith, 2015. "Localized Knowledge Spillovers: Evidence from the Agglomeration of American R&D Labs and Patent Data," Working Papers 15-3, Federal Reserve Bank of Philadelphia.
    12. Francesco Bartolucci & Alessio Farcomeni, 2022. "A hidden Markov space–time model for mapping the dynamics of global access to food," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 246-266, January.
    13. Youngho Kim & Morton O’Kelly, 2008. "A bootstrap based space–time surveillance model with an application to crime occurrences," Journal of Geographical Systems, Springer, vol. 10(2), pages 141-165, June.
    14. Peter Congdon & Alan Smith & Christine Dean, 1998. "Assessing Psychiatric Morbidity from Community Registers: Methods for Bayesian Adjustment," Urban Studies, Urban Studies Journal Limited, vol. 35(12), pages 2323-2352, December.
    15. Kristy Buzard & Gerald A. Carlino & Jake Carr & Robert M. Hunt & Tony E. Smith, 2017. "The Agglomeration of American Research and Development Labs," Working Papers 17-18, Federal Reserve Bank of Philadelphia.
    16. Marvin M. Smith & Tony E. Smith & John Wackes, 2007. "Alternative financial service providers and the spatial void hypothesis," Community Affairs Discussion Paper 07-01, Federal Reserve Bank of Philadelphia.
    17. Katarzyna Kopczewska, 2022. "Spatial machine learning: new opportunities for regional science," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(3), pages 713-755, June.
    18. Ronald E. Gangnon & Murray K. Clayton, 2000. "Bayesian Detection and Modeling of Spatial Disease Clustering," Biometrics, The International Biometric Society, vol. 56(3), pages 922-935, September.
    19. Papa Ousmane Cissé & Abdou Kâ Diongue & Dominique Guegan, 2016. "Note on a new Seasonal Fractionally Integrated Separable Spatial Autoregressive Model," Post-Print halshs-01278126, HAL.
    20. Peter Congdon, 1995. "Localities for Epidemiological Monitoring and Health Policy," Urban Studies, Urban Studies Journal Limited, vol. 32(7), pages 1175-1198, August.
    21. Ge Lin & Tonglin Zhang, 2005. "Loglinear Residual Tests of Moran's I Autorrelation: An Application to Kentucky Breast Cancer Data," Working Papers Working Paper 2005-06, Regional Research Institute, West Virginia University.

    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:42:y:2003:i:4:p:665-684. 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.