IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v38y2023i1d10.1007_s00180-022-01214-7.html
   My bibliography  Save this article

Controlling the familywise error rate when performing multiple comparisons in a linear latent variable model

Author

Listed:
  • Brice Ozenne

    (University of Copenhagen
    Rigshospitalet and University of Copenhagen)

  • Esben Budtz-Jørgensen

    (University of Copenhagen)

  • Sebastian Elgaard Ebert

    (Rigshospitalet and University of Copenhagen)

Abstract

In latent variable models (LVMs) it is possible to analyze multiple outcomes and to relate them to several explanatory variables. In this context many parameters are estimated and it is common to perform multiple tests, e.g. to investigate outcome-specific effects using Wald tests or to check the correct specification of the modeled mean and variance using a forward stepwise selection (FSS) procedure based on Score tests. Controlling the family-wise error rate (FWER) at its nominal level involves adjustment of the p-values for multiple testing. Because of the correlation between test statistics, the Bonferroni procedure is often too conservative. In this article, we extend the max-test procedure to the LVM framework for Wald and Score tests. Depending on the correlation between the test statistics, the max-test procedure is equivalent or more powerful than the Bonferroni procedure while also providing, asymptotically, a strong control of the FWER for non-iterative procedures. Using simulation studies, we assess the finite sample behavior of the max-test procedure for Wald and Score tests in LVMs. We apply our procedure to quantify the neuroinflammatory response to mild traumatic brain injury in nine brain regions.

Suggested Citation

  • Brice Ozenne & Esben Budtz-Jørgensen & Sebastian Elgaard Ebert, 2023. "Controlling the familywise error rate when performing multiple comparisons in a linear latent variable model," Computational Statistics, Springer, vol. 38(1), pages 1-23, March.
    • Handle: RePEc:spr:compst:v:38:y:2023:i:1:d:10.1007_s00180-022-01214-7
    DOI: 10.1007/s00180-022-01214-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-022-01214-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-022-01214-7?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. Brice Ozenne & Patrick M. Fisher & Esben Budtz‐J⊘rgensen, 2020. "Small sample corrections for Wald tests in latent variable models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 841-861, August.
    2. Christian Bressen Pipper & Christian Ritz & Hans Bisgaard, 2012. "A versatile method for confirmatory evaluation of the effects of a covariate in multiple models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 61(2), pages 315-326, March.
    3. Armengol Gasull & José López-Salcedo & Frederic Utzet, 2015. "Maxima of Gamma random variables and other Weibull-like distributions and the Lambert $$\varvec{W}$$ W function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 714-733, December.
    4. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors," Papers 1212.6906, arXiv.org, revised Jan 2018.
    5. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    6. Klaus Holst & Esben Budtz-Jørgensen, 2013. "Linear latent variable models: the lava-package," Computational Statistics, Springer, vol. 28(4), pages 1385-1452, August.
    7. DiCiccio, Cyrus J. & DiCiccio, Thomas J. & Romano, Joseph P., 2020. "Exact tests via multiple data splitting," Statistics & Probability Letters, Elsevier, vol. 166(C).
    8. Westfall, Peter H. & Tobias, Randall D., 2007. "Multiple Testing of General Contrasts: Truncated Closure and the Extended ShafferRoyen Method," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 487-494, June.
    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. Paul Blanche & Jean‐François Dartigues & Jérémie Riou, 2022. "A closed max‐t test for multiple comparisons of areas under the ROC curve," Biometrics, The International Biometric Society, vol. 78(1), pages 352-363, March.
    2. Brice Ozenne & Patrick M. Fisher & Esben Budtz‐J⊘rgensen, 2020. "Small sample corrections for Wald tests in latent variable models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 841-861, August.
    3. Soriano, José Luis & Mejía-Trejo, Juan, 2022. "Modelado de Ecuaciones Estructurales en el campo de las Ciencias de la Administración [Structural Equations Modeling in the Management Sciences]," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 33(1), pages 242-263, June.
    4. Sonia Nawrocka & Hans De Witte & Margherita Pasini & Margherita Brondino, 2023. "A Person-Centered Approach to Job Insecurity: Is There a Reciprocal Relationship between the Quantitative and Qualitative Dimensions of Job Insecurity?," IJERPH, MDPI, vol. 20(7), pages 1-27, March.
    5. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "Testing Many Moment Inequalities," CeMMAP working papers 65/13, Institute for Fiscal Studies.
    6. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-dimensional econometrics and regularized GMM," CeMMAP working papers CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Md. Mominur Rahman & Bilkis Akhter, 2021. "The impact of investment in human capital on bank performance: evidence from Bangladesh," Future Business Journal, Springer, vol. 7(1), pages 1-13, December.
    8. Masashi Soga & Kevin J. Gaston & Yuichi Yamaura & Kiyo Kurisu & Keisuke Hanaki, 2016. "Both Direct and Vicarious Experiences of Nature Affect Children’s Willingness to Conserve Biodiversity," IJERPH, MDPI, vol. 13(6), pages 1-12, May.
    9. César Merino-Soto & Gina Chávez-Ventura & Verónica López-Fernández & Guillermo M. Chans & Filiberto Toledano-Toledano, 2022. "Learning Self-Regulation Questionnaire (SRQ-L): Psychometric and Measurement Invariance Evidence in Peruvian Undergraduate Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    10. Mayya Zhilova, 2015. "Simultaneous likelihood-based bootstrap confidence sets for a large number of models," SFB 649 Discussion Papers SFB649DP2015-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Vladimir Spokoiny & Mayya Zhilova, 2014. "Bootstrap confidence sets under model misspecification," SFB 649 Discussion Papers SFB649DP2014-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Nathaniel Oliver Iotti & Damiano Menin & Tomas Jungert, 2022. "Early Adolescents’ Motivations to Defend Victims of Cyberbullying," IJERPH, MDPI, vol. 19(14), pages 1-9, July.
    13. Peter Tavel & Bibiana Jozefiakova & Peter Telicak & Jana Furstova & Michal Puza & Natalia Kascakova, 2022. "Psychometric Analysis of the Shortened Version of the Spiritual Well-Being Scale on the Slovak Population (SWBS-Sk)," IJERPH, MDPI, vol. 19(1), pages 1-12, January.
    14. Allen, Jaime & Eboli, Laura & Forciniti, Carmen & Mazzulla, Gabriella & Ortúzar, Juan de Dios, 2019. "The role of critical incidents and involvement in transit satisfaction and loyalty," Transport Policy, Elsevier, vol. 75(C), pages 57-69.
    15. Andreea-Ionela Puiu & Anca Monica Ardeleanu & Camelia Cojocaru & Anca Bratu, 2021. "Exploring the Effect of Status Quo, Innovativeness, and Involvement Tendencies on Luxury Fashion Innovations: The Mediation Role of Status Consumption," Mathematics, MDPI, vol. 9(9), pages 1-18, May.
    16. Andres Trujillo-Barrera & Joost M. E. Pennings & Dianne Hofenk, 2016. "Understanding producers' motives for adopting sustainable practices: the role of expected rewards, risk perception and risk tolerance," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(3), pages 359-382.
    17. Daria J. Kuss & Lydia Harkin & Eiman Kanjo & Joel Billieux, 2018. "Problematic Smartphone Use: Investigating Contemporary Experiences Using a Convergent Design," IJERPH, MDPI, vol. 15(1), pages 1-16, January.
    18. Allen, Jaime & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2019. "On evasion behaviour in public transport: Dissatisfaction or contagion?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 626-651.
    19. Cloarec, Julien, 2022. "Privacy controls as an information source to reduce data poisoning in artificial intelligence-powered personalization," Journal of Business Research, Elsevier, vol. 152(C), pages 144-153.
    20. Merkle, Edgar C. & Steyvers, Mark & Mellers, Barbara & Tetlock, Philip E., 2017. "A neglected dimension of good forecasting judgment: The questions we choose also matter," International Journal of Forecasting, Elsevier, vol. 33(4), pages 817-832.

    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:spr:compst:v:38:y:2023:i:1:d:10.1007_s00180-022-01214-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.