IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v84y2022i4p1503-1525.html
   My bibliography  Save this article

Paired or partially paired two‐sample tests with unordered samples

Author

Listed:
  • Yudong Wang
  • Yanlin Tang
  • Zhi‐Sheng Ye

Abstract

In paired two‐sample tests for mean equality, it is common to encounter unordered samples in which subject identities are not observed or unobservable, and it is impossible to link the measurements before and after treatment. The absence of subject identities masks the correspondence between the two samples, rendering existing methods inapplicable. In this paper, we propose two novel testing approaches. The first splits one of the two unordered samples into blocks and approximates the population mean using the average of the other sample. The second method is a variant of the first, in which subsampling is used to construct an incomplete U‐statistic. Both methods are affine invariant and can readily be extended to partially paired two‐sample tests with unordered samples. Asymptotic null distributions of the proposed test statistics are derived and the local powers of the tests are studied. Comprehensive simulations show that the proposed testing methods are able to maintain the correct size, and their powers are comparable to those of the oracle tests with perfect pair information. Four real examples are used to illustrate the proposed methods, in which we demonstrate that naive methods can yield misleading conclusions.

Suggested Citation

  • Yudong Wang & Yanlin Tang & Zhi‐Sheng Ye, 2022. "Paired or partially paired two‐sample tests with unordered samples," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1503-1525, September.
  • Handle: RePEc:bla:jorssb:v:84:y:2022:i:4:p:1503-1525
    DOI: 10.1111/rssb.12541
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssb.12541
    Download Restriction: no

    File URL: https://libkey.io/10.1111/rssb.12541?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
    ---><---

    References listed on IDEAS

    as
    1. Akritas, Michael G. & Antoniou, Efi S. & Kuha, Jouni, 2006. "Nonparametric Analysis of Factorial Designs With Random Missingness: Bivariate Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1513-1526, December.
    2. Jing Qin & Biao Zhang, 2005. "Marginal likelihood, conditional likelihood and empirical likelihood: Connections and applications," Biometrika, Biometrika Trust, vol. 92(2), pages 251-270, June.
    3. Tomasz Antczak & Rafał Weron, 2019. "Point of Sale (POS) Data from a Supermarket: Transactions and Cashier Operations," Data, MDPI, vol. 4(2), pages 1-4, May.
    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. V. Filimonov & G. Demos & D. Sornette, 2017. "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1167-1186, August.
    2. Daniel Gaigall, 2020. "Testing marginal homogeneity of a continuous bivariate distribution with possibly incomplete paired data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(4), pages 437-465, May.
    3. Haikady N Nagaraja & Shane Sanders, 2020. "The aggregation paradox for statistical rankings and nonparametric tests," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-21, March.
    4. Yuan, Ao & He, Wenqing & Wang, Binhuan & Qin, Gengsheng, 2012. "U-statistic with side information," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 20-38.
    5. Harrar, Solomon W. & Feyasa, Merga B. & Wencheko, Eshetu, 2020. "Nonparametric procedures for partially paired data in two groups," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    6. Taku Moriyama & Masashi Kuwano, 2022. "Causal inference for contemporaneous effects and its application to tourism product sales data," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(3), pages 250-260, September.
    7. Yuan, Ao & Xu, Jinfeng & Zheng, Gang, 2014. "On empirical likelihood statistical functions," Journal of Econometrics, Elsevier, vol. 178(P3), pages 613-623.
    8. Inagaki, Kazuhisa & Komaki, Fumiyasu, 2010. "A modification of profile empirical likelihood for the exponential-tilt model," Statistics & Probability Letters, Elsevier, vol. 80(11-12), pages 997-1004, June.
    9. Paul M. Torrens, 2023. "Agent models of customer journeys on retail high streets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(1), pages 87-128, January.
    10. 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.

    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:jorssb:v:84:y:2022:i:4:p:1503-1525. 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: https://edirc.repec.org/data/rssssea.html .

    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.