IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/635hx.html
   My bibliography  Save this paper

A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)

Author

Listed:
  • Evans, Clare
  • Leckie, George
  • Subramanian, SV
  • Bell, Andrew

    (University of Sheffield)

  • Merlo, Juan

Abstract

Intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA) is an innovative approach for investigating inequalities, including intersectional inequalities in health, disease, psychosocial, socioeconomic, and other outcomes. I-MAIHDA and related MAIHDA approaches have conceptual and methodological advantages over conventional single-level regression analysis. By enabling the study of inequalities produced by numerous interlocking systems of marginalization and oppression, and by addressing many of the limitations of studying interactions in conventional analyses, intersectional MAIHDA provides a valuable analytical tool in social epidemiology, health psychology, precision medicine and public health, environmental justice, and beyond. The approach allows for estimation of average differences between intersectional strata (stratum inequalities), in-depth exploration of interaction effects, as well as decomposition of the total individual variation (heterogeneity) in individual outcomes within and between strata. Specific advice for conducting and interpreting MAIHDA models has been scattered across a burgeoning literature. We consolidate this knowledge into an accessible conceptual and applied tutorial for studying both continuous and binary individual outcomes. We emphasize I-MAIHDA in our illustration, however this tutorial is also informative for understanding related approaches, such as multicategorical MAIHDA, which has been proposed for use in clinical research and beyond. The tutorial will support readers who wish to perform their own analyses and those interested in expanding their understanding of the approach. To demonstrate the methodology, we provide step-by-step analytical advice and present an illustrative health application using simulated data. We provide the data and syntax to replicate all our analyses. Please cite this paper as: Evans, C.R., G. Leckie, S.V. Subramanian, A. Bell, & J. Merlo. (2024.). A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). SSM - Population Health. https://doi.org/10.1016/j.ssmph.2024.101664

Suggested Citation

  • Evans, Clare & Leckie, George & Subramanian, SV & Bell, Andrew & Merlo, Juan, 2024. "A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)," SocArXiv 635hx, Center for Open Science.
    • Handle: RePEc:osf:socarx:635hx
    DOI: 10.31219/osf.io/635hx
    as

    Download full text from publisher

    File URL: https://osf.io/download/66015a6b4be20402a3c2f2da/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/635hx?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. Evans, Clare R. & Erickson, Natasha, 2019. "Intersectionality and depression in adolescence and early adulthood: A MAIHDA analysis of the national longitudinal study of adolescent to adult health, 1995–2008," Social Science & Medicine, Elsevier, vol. 220(C), pages 1-11.
    2. Bauer, Greta R. & Scheim, Ayden I., 2019. "Methods for analytic intercategorical intersectionality in quantitative research: Discrimination as a mediator of health inequalities," Social Science & Medicine, Elsevier, vol. 226(C), pages 236-245.
    3. Wemrell, Maria & Mulinari, Shai & Merlo, Juan, 2017. "Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches," Social Science & Medicine, Elsevier, vol. 177(C), pages 213-222.
    4. Aránzazu Hernández-Yumar & Maria Wemrell & Ignacio Abásolo Alessón & Beatriz González López-Valcárcel & George Leckie & Juan Merlo, 2018. "Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-23, December.
    5. Leckie, George & Charlton, Chris, 2013. "runmlwin: A Program to Run the MLwiN Multilevel Modeling Software from within Stata," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i11).
    6. Evans, Clare R. & Williams, David R. & Onnela, Jukka-Pekka & Subramanian, S.V., 2018. "A multilevel approach to modeling health inequalities at the intersection of multiple social identities," Social Science & Medicine, Elsevier, vol. 203(C), pages 64-73.
    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. Anna Persmark & Maria Wemrell & Sofia Zettermark & George Leckie & S V Subramanian & Juan Merlo, 2019. "Precision public health: Mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-21, August.
    2. Alvarez, Camila H. & Evans, Clare Rosenfeld, 2021. "Intersectional environmental justice and population health inequalities: A novel approach," Social Science & Medicine, Elsevier, vol. 269(C).
    3. Aránzazu Hernández-Yumar & Maria Wemrell & Ignacio Abásolo-Alessón & Beatriz González López-Valcárcel & Juan Merlo, 2023. "Impact of the Economic Crisis on Body Mass Index in Spain: An Intersectional Multilevel Analysis Using a Socioeconomic and Regional Perspective," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(4), pages 1-31, August.
    4. Fagrell Trygg, Nadja & Månsdotter, Anna & Gustafsson, Per E., 2021. "Intersectional inequalities in mental health across multiple dimensions of inequality in the Swedish adult population," Social Science & Medicine, Elsevier, vol. 283(C).
    5. Daniel Holman & Alan Walker, 2021. "Understanding unequal ageing: towards a synthesis of intersectionality and life course analyses," European Journal of Ageing, Springer, vol. 18(2), pages 239-255, June.
    6. Evans, Clare R. & Erickson, Natasha, 2019. "Intersectionality and depression in adolescence and early adulthood: A MAIHDA analysis of the national longitudinal study of adolescent to adult health, 1995–2008," Social Science & Medicine, Elsevier, vol. 220(C), pages 1-11.
    7. Evans, Clare R., 2019. "Adding interactions to models of intersectional health inequalities: Comparing multilevel and conventional methods," Social Science & Medicine, Elsevier, vol. 221(C), pages 95-105.
    8. Philipp Jaehn & Emily Mena & Sibille Merz & Robert Hoffmann & Antje Gößwald & Alexander Rommel & Christine Holmberg & on behalf of the ADVANCE GENDER study group, 2020. "Non-response in a national health survey in Germany: An intersectionality-informed multilevel analysis of individual heterogeneity and discriminatory accuracy," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-17, August.
    9. Aránzazu Hernández-Yumar & Maria Wemrell & Ignacio Abásolo Alessón & Beatriz González López-Valcárcel & George Leckie & Juan Merlo, 2018. "Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-23, December.
    10. Wilkes, Rima & Karimi, Aryan, 2024. "What does the MAIHDA method explain?," Social Science & Medicine, Elsevier, vol. 345(C).
    11. Gustafsson, Per E. & Fonseca-Rodríguez, Osvaldo & Castel Feced, Sara & San Sebastián, Miguel & Bastos, João Luiz & Mosquera, Paola A., 2024. "A novel application of interrupted time series analysis to identify the impact of a primary health care reform on intersectional inequities in avoidable hospitalizations in the adult Swedish populatio," Social Science & Medicine, Elsevier, vol. 343(C).
    12. Syeda Ammara Shaharyar & Eduardo Bernabé & Elsa Karina Delgado-Angulo, 2021. "The Intersections of Ethnicity, Nativity Status and Socioeconomic Position in Relation to Periodontal Status: A Cross-Sectional Study in London, England," IJERPH, MDPI, vol. 18(19), pages 1-10, October.
    13. Harari, Lexi & Lee, Chioun, 2021. "Intersectionality in quantitative health disparities research: A systematic review of challenges and limitations in empirical studies," Social Science & Medicine, Elsevier, vol. 277(C).
    14. Zubizarreta, Dougie & Beccia, Ariel L. & Trinh, Mai-Han & Reynolds, Colleen A. & Reisner, Sari L. & Charlton, Brittany M., 2022. "Human papillomavirus vaccination disparities among U.S. college students: An intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)," Social Science & Medicine, Elsevier, vol. 301(C).
    15. Kline, Nolan, 2022. "Syndemic statuses: Intersectionality and mobilizing for LGBTQ+ Latinx health equity after the Pulse shooting," Social Science & Medicine, Elsevier, vol. 295(C).
    16. Evans, Clare R. & Nieves, Christina I. & Erickson, Natasha & Borrell, Luisa N., 2023. "Intersectional inequities in the birthweight gap between twin and singleton births: A random effects MAIHDA analysis of 2012–2018 New York City birth data," Social Science & Medicine, Elsevier, vol. 331(C).
    17. Bell, Andrew & Evans, Clare & Holman, Daniel & Leckie, George, 2023. "Extending intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) for longitudinal data, with application to mental health trajectories in the UK," SocArXiv jq57s, Center for Open Science.
    18. Valérie Lederer & Karen Messing & Hélène Sultan-Taïeb, 2022. "How Can Quantitative Analysis Be Used to Improve Occupational Health without Reinforcing Social Inequalities? An Examination of Statistical Methods," IJERPH, MDPI, vol. 20(1), pages 1-19, December.
    19. Ivana Zilic & Helen LaVan, 2020. "Arbitration of accommodation in US workplaces: employee, stakeholder and human resources characteristics," Industrial Relations Journal, Wiley Blackwell, vol. 51(5), pages 454-473, September.
    20. T. Chatzivasileiadis & F. Estrada & M. W. Hofkes & R. S. J. Tol, 2019. "Systematic Sensitivity Analysis of the Full Economic Impacts of Sea Level Rise," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1183-1217, March.

    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:osf:socarx:635hx. 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.