IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v7y2008i1n31.html

A Unification of Multivariate Methods for Meta-Analysis of Genetic Association Studies

Author

Listed:
  • Bagos Pantelis G

    (University of Central Greece)

Abstract

Methods for multivariate meta-analysis of genetic association studies are reviewed, summarized and presented in a unified framework. Modifications of standard models are described in detail in order to be applied in genetic association studies. The model based on summary data is uniformly defined for both discrete and continuous outcomes and analytical expressions for the covariance of the two jointly modeled outcomes are derived for both cases. The models based on the binary nature of the data are fitted using both prospective and retrospective likelihood. Furthermore, formal tests for assessing the genetic model of inheritance are developed based on standard normal theory. The general model is compared to the recently proposed genetic model-free bivariate approach (either using summary or binary data), and it is clearly shown that the estimates provided by this approach are nearly identical to the estimates derived by the general bivariate model using the aforementioned tests for the genetic model. The methods developed here as well as the tests, are easily implemented in all major statistical packages, escaping the need of self written software. The methods are applied in several already published meta-analyses of genetic association studies (with both discrete and continuous outcomes) and the results are compared against the widely used univariate approach as well as against the genetic model free approaches. Illustrative examples of code in Stata are given in the appendix. It is anticipated that the methods developed in this work will be widely applied in the meta-analysis of genetic association studies.

Suggested Citation

  • Bagos Pantelis G, 2008. "A Unification of Multivariate Methods for Meta-Analysis of Genetic Association Studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-35, October.
  • Handle: RePEc:bpj:sagmbi:v:7:y:2008:i:1:n:31
    DOI: 10.2202/1544-6115.1408
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1544-6115.1408
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.2202/1544-6115.1408?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Hoang Pham, 2006. "Theory of Estimation," Springer Series in Reliability Engineering, in: System Software Reliability, chapter 3, pages 77-120, Springer.
    2. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    3. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    4. Marsaglia, George, 2006. "Ratios of Normal Variables," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 16(i04).
    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. Xianxian Yang & Bin Tan & Xipeng Zhou & Jian Xue & Xian Zhang & Peng Wang & Chuang Shao & Yingli Li & Chaorui Li & Huiming Xia & Jingfu Qiu, 2015. "Interferon-Inducible Transmembrane Protein 3 Genetic Variant rs12252 and Influenza Susceptibility and Severity: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-14, May.

    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. Mueller-Langer, Frank & Fecher, Benedikt & Harhoff, Dietmar & Wagner, Gert G., 2019. "Replication studies in economics—How many and which papers are chosen for replication, and why?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 48(1), pages 62-83.
    2. Simon Gächter & Chris Starmer & Fabio Tufano, 2025. "Measuring Group Cohesion to Reveal the Power of Social Relationships in Team Production," The Review of Economics and Statistics, MIT Press, vol. 107(2), pages 539-554, March.
    3. repec:ebl:ecbull:v:3:y:2008:i:42:p:1-13 is not listed on IDEAS
    4. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    5. Ellen Poel & Owen O'donnell & Eddy Doorslaer, 2009. "What explains the rural-urban gap in infant mortality: Household or community characteristics?," Demography, Springer;Population Association of America (PAA), vol. 46(4), pages 827-850, November.
    6. Thierry Poynard & Dominique Thabut & Mona Munteanu & Vlad Ratziu & Yves Benhamou & Olivier Deckmyn, 2010. "Hirsch Index and Truth Survival in Clinical Research," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-10, August.
    7. Alexander Frankel & Maximilian Kasy, 2022. "Which Findings Should Be Published?," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 1-38, February.
    8. Jyotirmoy Sarkar, 2018. "Will P†Value Triumph over Abuses and Attacks?," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 7(4), pages 66-71, July.
    9. Andrew Gelman & Daniel Lee & Jiqiang Guo, 2015. "Stan," Journal of Educational and Behavioral Statistics, , vol. 40(5), pages 530-543, October.
    10. Cyrenne, Philippe & Grant, Hugh, 2009. "University decision making and prestige: An empirical study," Economics of Education Review, Elsevier, vol. 28(2), pages 237-248, April.
    11. Stephen Fox, 2016. "Dismantling The Box — Applying Principles For Reducing Preconceptions During Ideation," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-27, August.
    12. Amanda Fitzgerald & Naoise Mac Giollabhui & Louise Dolphin & Robert Whelan & Barbara Dooley, 2018. "Dissociable psychosocial profiles of adolescent substance users," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-16, August.
    13. Yeojin Chung & Sophia Rabe-Hesketh & Vincent Dorie & Andrew Gelman & Jingchen Liu, 2013. "A Nondegenerate Penalized Likelihood Estimator for Variance Parameters in Multilevel Models," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 685-709, October.
    14. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2019. "The Impact of Bullying Victimisation on Mental Wellbeing," IZA Discussion Papers 12206, IZA Network @ LISER.
    15. Hsin-Neng Hsieh & Hung-Yi Lu, 2020. "The generalized inference on the ratio of mean differences for fraction retention noninferiority hypothesis," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-12, June.
    16. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, IZA Network @ LISER.
    17. Saul Estrin & Julia Korosteleva & Tomasz Mickiewicz, 2022. "Schumpeterian Entry: Innovation, Exporting, and Growth Aspirations of Entrepreneurs," Entrepreneurship Theory and Practice, , vol. 46(2), pages 269-296, March.
    18. Godager, Geir & Iversen, Tor & Ma, Ching-to Albert, 2015. "Competition, gatekeeping, and health care access," Journal of Health Economics, Elsevier, vol. 39(C), pages 159-170.
    19. Matteo M. Galizzi & Daniel Navarro-Martinez, 2019. "On the External Validity of Social Preference Games: A Systematic Lab-Field Study," Management Science, INFORMS, vol. 65(3), pages 976-1002, March.
    20. Jens GroЯer & Ernesto Reuben & Agnieszka Tymula, 2010. "Tacit Lobbying Agreements: An Experimental Study," Working Paper Series in Economics 50, University of Cologne, Department of Economics.
    21. Namin, Aidin & Soysal, Gonca P. & Ratchford, Brian T., 2022. "Alleviating demand uncertainty for seasonal goods: An analysis of attribute-based markdown policy for fashion retailers," Journal of Business Research, Elsevier, vol. 145(C), pages 671-681.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:bpj:sagmbi:v:7:y:2008:i:1:n:31. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.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.