Evidence map›Paper›PMID 38690117›Full record

ArticleSSM - population health2024

A tutorial for conducting intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).

Clare R Evans, George Leckie, S V Subramanian, Andrew Bell, Juan Merlo

Abstract read
In one paragraph

Article in SSM - population health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

51 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Resilience at the Intersection of Race/Ethnicity, Sex, and Sexual Orientation among U.S. Adults.Journal of urban health : bulletin of the New York Academy of Medicine · 2026
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  8. From Averages to Heterogeneity: A Plain-Language Guide to MAIHDA in Epidemiology.International journal of social determinants of health and health services · 2026
    Review
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  11. Sociodemographic disparities and reasons for delayed healthcare among U.S. cancer survivors: an All of Us study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Clare R EvansDepartment of Sociology, University of Oregon, Eugene, OR, USA.
George LeckieCentre for Multilevel Modelling and School of Education, University of Bristol, UK.
S V SubramanianDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Andrew BellSheffield Methods Institute, University of Sheffield, Sheffield, UK.
Juan MerloResearch Unit of Social Epidemiology, Faculty of Medicine, University of Lund, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Indexed as

Health inequalityIntersectionalityLinear regressionLogistic regressionMAIHDAMultilevel modelsQuantitative methodsSocial determinants

Identifiers

PMID38690117
PMCPMC11059336

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.