IDEAS home Printed from https://ideas.repec.org/a/taf/gnstxx/v24y2012i4p977-991.html
   My bibliography  Save this article

Weighted rank tests and Hodges-Lehmann estimates for the multivariate two-sample location problem with clustered data

Author

Listed:
  • Riina Lemponen
  • Denis Larocque
  • Jaakko Nevalainen
  • Hannu Oja

Abstract

A family of weighted rank tests and corresponding Hodges-Lehmann estimates are proposed for the analysis of multivariate two-sample clustered data. These procedures are a specific case of the nonparametric multivariate methods for clustered data considered by Nevalainen, Larocque, Oja, and Pörsti [(2010), 'Nonparametric Analysis of Clustered Multivariate Data', Journal of the American Statistical Association , 105, 864-871]. This paper provides detailed proofs of their asymptotic properties that have not been previously published. Optimal weights for the procedures are derived and illustrated. The theoretical results are supplemented with simulation studies.

Suggested Citation

  • Riina Lemponen & Denis Larocque & Jaakko Nevalainen & Hannu Oja, 2012. "Weighted rank tests and Hodges-Lehmann estimates for the multivariate two-sample location problem with clustered data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 977-991, December.
    • Handle: RePEc:taf:gnstxx:v:24:y:2012:i:4:p:977-991
    DOI: 10.1080/10485252.2012.712693
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10485252.2012.712693
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10485252.2012.712693?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Gerard, Patrick D. & Schucany, William R., 2007. "An enhanced sign test for dependent binary data with small numbers of clusters," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4622-4632, May.
    2. Somnath Datta & Jaakko Nevalainen & Hannu Oja, 2012. "A general class of signed-rank tests for clustered data when the cluster size is potentially informative," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 797-808.
    3. Datta, Somnath & Satten, Glen A., 2005. "Rank-Sum Tests for Clustered Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 908-915, September.
    4. Haataja, Riina & Larocque, Denis & Nevalainen, Jaakko & Oja, Hannu, 2009. "A weighted multivariate signed-rank test for cluster-correlated data," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1107-1119, July.
    5. Denis Larocque & Riina Haataja & Jaakko Nevalainen & Hannu Oja, 2010. "Two sample tests for the nonparametric Behrens–Fisher problem with clustered data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(6), pages 755-771.
    6. Werner, Carola & Brunner, Edgar, 2007. "Rank methods for the analysis of clustered data in diagnostic trials," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 5041-5054, June.
    7. Denis Larocque & Jaakko Nevalainen & Hannu Oja, 2007. "A weighted multivariate sign test for cluster-correlated data," Biometrika, Biometrika Trust, vol. 94(2), pages 267-283.
    8. Nevalainen, Jaakko & Larocque, Denis & Oja, Hannu & Pörsti, Ilkka, 2010. "Nonparametric Analysis of Clustered Multivariate Data," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 864-872.
    9. Somnath Datta & Glen A. Satten, 2008. "A Signed-Rank Test for Clustered Data," Biometrics, The International Biometric Society, vol. 64(2), pages 501-507, June.
    10. Kloke, John D. & McKean, Joseph W. & Rashid, M. Mushfiqur, 2009. "Rank-Based Estimation and Associated Inferences for Linear Models With Cluster Correlated Errors," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 384-390.
    11. Konietschke, Frank & Brunner, Edgar, 2009. "Nonparametric analysis of clustered data in diagnostic trials: Estimation problems in small sample sizes," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 730-741, January.
    12. Fu, Liya & Wang, You-Gan & Bai, Zhidong, 2010. "Rank regression for analysis of clustered data: A natural induced smoothing approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1036-1050, April.
    13. Bernard Rosner & Robert J. Glynn & Mei-Ling Ting Lee, 2003. "Incorporation of Clustering Effects for the Wilcoxon Rank Sum Test: A Large-Sample Approach," Biometrics, The International Biometric Society, vol. 59(4), pages 1089-1098, December.
    14. Bernard Rosner & Robert J. Glynn & Mei-Ling T. Lee, 2006. "Extension of the Rank Sum Test for Clustered Data: Two-Group Comparisons with Group Membership Defined at the Subunit Level," Biometrics, The International Biometric Society, vol. 62(4), pages 1251-1259, December.
    15. Brown, Bruce M. & Hall, Peter & Young, G. Alastair, 1997. "On the Effect of Inliers on the Spatial Median," Journal of Multivariate Analysis, Elsevier, vol. 63(1), pages 88-104, October.
    Full references (including those not matched with items on IDEAS)

    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. Omer Ozturk & Asuman Turkmen, 2016. "Quantile inference based on clustered data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(7), pages 867-893, October.
    2. Somnath Datta & Jaakko Nevalainen & Hannu Oja, 2012. "A general class of signed-rank tests for clustered data when the cluster size is potentially informative," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 797-808.
    3. Denis Larocque & Riina Haataja & Jaakko Nevalainen & Hannu Oja, 2010. "Two sample tests for the nonparametric Behrens–Fisher problem with clustered data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(6), pages 755-771.
    4. Liya Fu & You-Gan Wang, 2012. "Efficient Estimation for Rank-Based Regression with Clustered Data," Biometrics, The International Biometric Society, vol. 68(4), pages 1074-1082, December.
    5. Haataja, Riina & Larocque, Denis & Nevalainen, Jaakko & Oja, Hannu, 2009. "A weighted multivariate signed-rank test for cluster-correlated data," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1107-1119, July.
    6. Sandipan Dutta, 2022. "Robust Testing of Paired Outcomes Incorporating Covariate Effects in Clustered Data with Informative Cluster Size," Stats, MDPI, vol. 5(4), pages 1-13, December.
    7. Jaakko Nevalainen & Somnath Datta & Hannu Oja, 2014. "Inference on the marginal distribution of clustered data with informative cluster size," Statistical Papers, Springer, vol. 55(1), pages 71-92, February.
    8. Jaakko Nevalainen & Denis Larocque & Hannu Oja, 2007. "A weighted spatial median for clustered data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 355-379, February.
    9. Jaakko Nevalainen & Denis Larocque & Hannu Oja, 2007. "A weighted spatial median for clustered data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 355-379, February.
    10. Bernard Rosner & Robert J. Glynn, 2011. "Power and Sample Size Estimation for the Clustered Wilcoxon Test," Biometrics, The International Biometric Society, vol. 67(2), pages 646-653, June.
    11. Lea Cassar, 2014. "Job mission as a substitute for monetary incentives: experimental evidence," ECON - Working Papers 177, Department of Economics - University of Zurich.
    12. Janie McDonald & Patrick D. Gerard & Christopher S. McMahan & William R. Schucany, 2016. "Exact-Permutation-Based Sign Tests for Clustered Binary Data Via Weighted and Unweighted Test Statistics," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(4), pages 698-712, December.
    13. Philippe Aghion & Stefan Bechtold & Lea Cassar & Holger Herz, 2018. "The Causal Effects of Competition on Innovation: Experimental Evidence," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 34(2), pages 162-195.
    14. Gelder, Alan & Kovenock, Dan, 2017. "Dynamic behavior and player types in majoritarian multi-battle contests," Games and Economic Behavior, Elsevier, vol. 104(C), pages 444-455.
    15. Hasika K. Wickrama Senevirathne & Sandipan Dutta, 2024. "Testing Informativeness of Covariate-Induced Group Sizes in Clustered Data," Mathematics, MDPI, vol. 12(11), pages 1-15, May.
    16. Maul, D. & Schiereck, D., 2017. "The bond event study methodology since 1974," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 80723, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    17. Konietschke, F. & Harrar, S.W. & Lange, K. & Brunner, E., 2012. "Ranking procedures for matched pairs with missing data — Asymptotic theory and a small sample approximation," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1090-1102.
    18. Somnath Datta & Glen A. Satten, 2008. "A Signed-Rank Test for Clustered Data," Biometrics, The International Biometric Society, vol. 64(2), pages 501-507, June.
    19. You-Gan Wang & Yudong Zhao, 2008. "Weighted Rank Regression for Clustered Data Analysis," Biometrics, The International Biometric Society, vol. 64(1), pages 39-45, March.
    20. Werner, Carola & Brunner, Edgar, 2007. "Rank methods for the analysis of clustered data in diagnostic trials," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 5041-5054, June.

    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:taf:gnstxx:v:24:y:2012:i:4:p:977-991. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GNST20 .

    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.