IDEAS home Printed from https://ideas.repec.org/a/gam/jstats/v3y2020i1p4-39d316934.html
   My bibliography  Save this article

New Equivalence Tests for Hardy–Weinberg Equilibrium and Multiple Alleles

Author

Listed:
  • Vladimir Ostrovski

    (ERGO Group AG, ERGO-Platz 1, 40198 Düsseldorf, Germany)

Abstract

We consider testing equivalence to Hardy–Weinberg Equilibrium in case of multiple alleles. Two different test statistics are proposed for this test problem. The asymptotic distribution of the test statistics is derived. The corresponding tests can be carried out using asymptotic approximation. Alternatively, the variance of the test statistics can be estimated by the bootstrap method. The proposed tests are applied to three real data sets. The finite sample performance of the tests is studied by simulations, which are inspired by the real data sets.

Suggested Citation

  • Vladimir Ostrovski, 2020. "New Equivalence Tests for Hardy–Weinberg Equilibrium and Multiple Alleles," Stats, MDPI, vol. 3(1), pages 1-6, February.
  • Handle: RePEc:gam:jstats:v:3:y:2020:i:1:p:4-39:d:316934
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-905X/3/1/4/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2571-905X/3/1/4/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stefan Wellek, 2004. "Tests for Establishing Compatibility of an Observed Genotype Distribution with Hardy–Weinberg Equilibrium in the Case of a Biallelic Locus," Biometrics, The International Biometric Society, vol. 60(3), pages 694-703, September.
    2. Vladimir Ostrovski, 2019. "New Equivalence Tests for Approximate Independence in Contingency Tables," Stats, MDPI, vol. 2(2), pages 1-8, April.
    3. Ostrovski, Vladimir, 2018. "Testing equivalence to families of multinomial distributions with application to the independence model," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 61-66.
    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. Ostrovski, Vladimir, 2022. "Testing equivalence to power law distributions," Statistics & Probability Letters, Elsevier, vol. 181(C).
    2. Vladimir Ostrovski, 2019. "New Equivalence Tests for Approximate Independence in Contingency Tables," Stats, MDPI, vol. 2(2), pages 1-8, April.
    3. Ostrovski, Vladimir, 2022. "Testing equivalence to binary generalized linear models with application to logistic regression," Statistics & Probability Letters, Elsevier, vol. 191(C).

    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:gam:jstats:v:3:y:2020:i:1:p:4-39:d:316934. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.