IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v6y2016i1p2158244015621115.html
   My bibliography  Save this article

Detecting Between-Groups Heteroscedasticity in Moderated Multiple Regression With a Continuous Predictor and a Categorical Moderator

Author

Listed:
  • Patrick J. Rosopa
  • Amber N. Schroeder
  • Jessica L. Doll

Abstract

Moderated multiple regression (MMR) is frequently used to test moderation hypotheses in the behavioral and social sciences. In MMR with a categorical moderator, between-groups heteroscedasticity is not uncommon and can inflate Type I error rates or reduce statistical power. Compared with research on remedial procedures that can mitigate the effects of this violated assumption, less research attention has focused on statistical procedures that can be used to detect between-groups heteroscedasticity. In the current article, we briefly review such procedures. Then, using Monte Carlo methods, we compare the performance of various procedures that can be used to detect between-groups heteroscedasticity in MMR with a categorical moderator, including a heuristic method and a variant of a procedure suggested by O’Brien. Of the various procedures, the heuristic method had the greatest statistical power at the expense of inflated Type I error rates. Otherwise, assuming that the normality assumption has not been violated, Bartlett’s test generally had the greatest statistical power when direct pairing occurs (i.e., when the group with the largest sample size has the largest error variance). In contrast, O’Brien’s procedure tended to have the greatest power when there was indirect pairing (i.e., when the group with the largest sample size has the smallest error variance). We conclude with recommendations for researchers and practitioners in the behavioral and social sciences.

Suggested Citation

  • Patrick J. Rosopa & Amber N. Schroeder & Jessica L. Doll, 2016. "Detecting Between-Groups Heteroscedasticity in Moderated Multiple Regression With a Continuous Predictor and a Categorical Moderator," SAGE Open, , vol. 6(1), pages 21582440156, January.
    • Handle: RePEc:sae:sagope:v:6:y:2016:i:1:p:2158244015621115
    DOI: 10.1177/2158244015621115
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2158244015621115
    Download Restriction: no
    File URL: https://libkey.io/10.1177/2158244015621115?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. Cribari-Neto, Francisco, 2004. "Asymptotic inference under heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 215-233, March.
    2. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    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. Magdalena Iordache Platis & Cosmin Olteanu & Anca Luiza Hotoi, 2022. "Evolution of the Online Sales of Sustainable Products in the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-16, November.

    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. Katarzyna Jabłońska, 2018. "Dealing With Heteroskedasticity Within The Modeling Of The Quality Of Life Of Older People," Statistics in Transition New Series, Polish Statistical Association, vol. 19(3), pages 423-452, September.
    2. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
    3. Nelson Areal & Maria Cortez & Florinda Silva, 2013. "The conditional performance of US mutual funds over different market regimes: do different types of ethical screens matter?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(4), pages 397-429, December.
    4. Jabłońska Katarzyna, 2018. "Dealing With Heteroskedasticity Within The Modeling Of The Quality Of Life Of Older People," Statistics in Transition New Series, Polish Statistical Association, vol. 19(3), pages 433-452, September.
    5. Benoît Le Maux & Federica Minardy & Charlotte Magalhaes, 2011. "Determinants of Electoral Outcomes: A simple Test of Meltzer and Richard's Hypothesis," Economics Working Paper from Condorcet Center for political Economy at CREM-CNRS 2011-03-ccr, Condorcet Center for political Economy.
    6. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    7. Hideki Murakami & Yukari Matsuse & Koji Mukaigawa & Yushi Tsunoda, 2013. "Product lifecycle and choice of transportation modes: Japan' s evidence of import and export," Discussion Papers 2013-28, Kobe University, Graduate School of Business Administration.
    8. Michele Fratianni & Francesco Marchionne, 2011. "The Limits to Integration," Chapters, in: Miroslav N. Jovanović (ed.), International Handbook on the Economics of Integration, Volume I, chapter 9, Edward Elgar Publishing.
    9. Tadashi Kikuchi, 2014. "Vietnamese Inter – regional labor migration: system approach to the modeling 1989, 1999, 2009," EcoMod2014 6998, EcoMod.
    10. Jean-Paul Azam & Catherine Bonjean, 1995. "La formation du prix du riz : théorie et application au cas d'Antananarivo (Madagascar) ," Revue Économique, Programme National Persée, vol. 46(4), pages 1145-1166.
    11. Nathaniel Geiger & Bryan McLaughlin & John Velez, 2021. "Not all boomers: temporal orientation explains inter- and intra-cultural variability in the link between age and climate engagement," Climatic Change, Springer, vol. 166(1), pages 1-20, May.
    12. Vittorio Nicolardi, 2009. "The effects of the new 1995 ESA methodologies of estimation on the structural analysis of Italian consumption," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(1), pages 125-149, March.
    13. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    14. Raffaella Santolini, 2017. "Electoral Rules And Public Spending Composition: The Case Of Italian Regions," Contemporary Economic Policy, Western Economic Association International, vol. 35(3), pages 551-577, July.
    15. Desbordes, Rodolphe, 2007. "The sensitivity of U.S. multinational enterprises to political and macroeconomic uncertainty: A sectoral analysis," International Business Review, Elsevier, vol. 16(6), pages 732-750, December.
    16. Zsuzsa Lábiscsák-Erdélyi & Ilona Veres-Balajti & Annamária Somhegyi & Karolina Kósa, 2022. "Self-Esteem Is Independent Factor and Moderator of School-Related Psychosocial Determinants of Life Satisfaction in Adolescents," IJERPH, MDPI, vol. 19(9), pages 1-14, May.
    17. Anjum, Zeba & Burke, Paul J. & Gerlagh, Reyer & Stern, David I., "undated". "Modeling the Emissions-Income Relationship Using Long-Run Growth Rates," Working Papers 249422, Australian National University, Centre for Climate Economics & Policy.
    18. Grzegorz Rybak & Edward Kozłowski & Krzysztof Król & Tomasz Rymarczyk & Agnieszka Sulimierska & Artur Dmowski & Piotr Bednarczuk, 2023. "Algorithms for Optimizing Energy Consumption for Fermentation Processes in Biogas Production," Energies, MDPI, vol. 16(24), pages 1-17, December.
    19. Garcia-Hiernaux, Alfredo & Gonzalez-Perez, Maria T. & Guerrero, David E., 2023. "Eurozone prices: A tale of convergence and divergence," Economic Modelling, Elsevier, vol. 126(C).
    20. Timothy Tyler Brown & Vishnu Murthy, 2020. "Do public health activities pay for themselves? The effect of county‐level public health expenditures on county‐level public assistance medical care benefits in California," Health Economics, John Wiley & Sons, Ltd., vol. 29(10), pages 1220-1230, October.

    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:sae:sagope:v:6:y:2016:i:1:p:2158244015621115. 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: SAGE Publications (email available below). General contact details of provider: .

    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.