IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v66y2010i2p355-364.html
   My bibliography  Save this article

Hierarchical and Joint Site-Edge Methods for Medicare Hospice Service Region Boundary Analysis

Author

Listed:
  • Haijun Ma
  • Bradley P. Carlin
  • Sudipto Banerjee

Abstract

No abstract is available for this item.

Suggested Citation

  • Haijun Ma & Bradley P. Carlin & Sudipto Banerjee, 2010. "Hierarchical and Joint Site-Edge Methods for Medicare Hospice Service Region Boundary Analysis," Biometrics, The International Biometric Society, vol. 66(2), pages 355-364, June.
  • Handle: RePEc:bla:biomet:v:66:y:2010:i:2:p:355-364
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01291.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. G. M. Jacquez & S. Maruca & M.-J. Fortin, 2000. "From fields to objects: A review of geographic boundary analysis," Journal of Geographical Systems, Springer, vol. 2(3), pages 221-241, September.
    2. Hoff P.D. & Raftery A.E. & Handcock M.S., 2002. "Latent Space Approaches to Social Network Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1090-1098, December.
    3. Banerjee, Sudipto & Gelfand, Alan E., 2006. "Bayesian Wombling: Curvilinear Gradient Assessment Under Spatial Process Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1487-1501, December.
    4. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    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. Duncan Lee & Richard Mitchell, 2013. "Locally adaptive spatial smoothing using conditional auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(4), pages 593-608, August.
    2. Duncan Lee & Alastair Rushworth & Sujit K. Sahu, 2014. "A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution," Biometrics, The International Biometric Society, vol. 70(2), pages 419-429, June.
    3. Alastair Rushworth & Duncan Lee & Christophe Sarran, 2017. "An adaptive spatiotemporal smoothing model for estimating trends and step changes in disease risk," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 141-157, January.
    4. Joshua L. Warren & Jiachen Cai & Nicholaus P. Johnson & Nicole C. Deziel, 2022. "A discrete kernel stick‐breaking model for detecting spatial boundaries in hydraulic fracturing wastewater disposal well placement across Ohio," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(1), pages 175-193, January.

    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. Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.
    2. Linardi, Fernando & Diks, Cees & van der Leij, Marco & Lazier, Iuri, 2020. "Dynamic interbank network analysis using latent space models," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    3. Hatfield, Laura A. & Hoffbeck, Richard W. & Alexander, Bruce H. & Carlin, Bradley P., 2009. "Spatiotemporal and spatial threshold models for relating UV exposures and skin cancer in the central United States," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3001-3015, June.
    4. Hannah M. Director & Adrian E. Raftery, 2022. "Contour models for physical boundaries enclosing star‐shaped and approximately star‐shaped polygons," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1688-1720, November.
    5. Duncan Lee & Richard Mitchell, 2013. "Locally adaptive spatial smoothing using conditional auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(4), pages 593-608, August.
    6. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
    7. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    8. Jesse Elliott & Zemin Bai & Shu-Ching Hsieh & Shannon E Kelly & Li Chen & Becky Skidmore & Said Yousef & Carine Zheng & David J Stewart & George A Wells, 2020. "ALK inhibitors for non-small cell lung cancer: A systematic review and network meta-analysis," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-18, February.
    9. Christina Leuker & Thorsten Pachur & Ralph Hertwig & Timothy J. Pleskac, 2019. "Do people exploit risk–reward structures to simplify information processing in risky choice?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 76-94, August.
    10. Francois Olivier & Laval Guillaume, 2011. "Deviance Information Criteria for Model Selection in Approximate Bayesian Computation," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-25, July.
    11. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
    12. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    13. Rubio, F.J. & Steel, M.F.J., 2011. "Inference for grouped data with a truncated skew-Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3218-3231, December.
    14. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    15. Padilla, Juan L. & Azevedo, Caio L.N. & Lachos, Victor H., 2018. "Multidimensional multiple group IRT models with skew normal latent trait distributions," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 250-268.
    16. Svetlana V. Tishkovskaya & Paul G. Blackwell, 2021. "Bayesian estimation of heterogeneous environments from animal movement data," Environmetrics, John Wiley & Sons, Ltd., vol. 32(6), September.
    17. David Macro & Jeroen Weesie, 2016. "Inequalities between Others Do Matter: Evidence from Multiplayer Dictator Games," Games, MDPI, vol. 7(2), pages 1-23, April.
    18. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    19. Tautenhahn, Susanne & Heilmeier, Hermann & Jung, Martin & Kahl, Anja & Kattge, Jens & Moffat, Antje & Wirth, Christian, 2012. "Beyond distance-invariant survival in inverse recruitment modeling: A case study in Siberian Pinus sylvestris forests," Ecological Modelling, Elsevier, vol. 233(C), pages 90-103.
    20. Julian P. T. Higgins & Simon G. Thompson & David J. Spiegelhalter, 2009. "A re‐evaluation of random‐effects meta‐analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 137-159, January.

    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:bla:biomet:v:66:y:2010:i:2:p:355-364. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.