Intersectional Multilevel Modelling: Theory and Applications in Stata
Bridging feminist theory and cutting-edge statistics, this book introduces Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) and expands it into a contextual intersectional multilevel framework, revealing how power operates through intersecting identities and environments to generate systemic inequalities and how quantitative tools can expose, understand, and ultimately challenge them. 

It first clarifies why traditional interaction terms fail to fully capture intersectionality’s transformative aim: they overlook the simultaneous, context-specific ways that gender, race, class, sexuality and other dimensions of inequalities configure privilege and oppression. Using intersectional multilevel models, the author shows how it is possible to estimate both individual heterogeneity and group-level effects, then extends the approach to incorporate context. Worked examples in Stata guide readers through linear, binary and ordinal outcomes. A brief overview of Bayesian estimation and random slopes models is also provided. The book is accompanied by open datasets and reproducible code. Throughout, an ethical reflexive thread stresses category fluidity, disclosure risks and accountability to intersectionality’s transformative agenda, demonstrating the method’s power to reveal, and hopefully contributes to dismantling, structural inequalities. 

Designed for social scientists, policy analysts or management scholars seeking rigorous yet reflexive quantitative approaches, the book suits postgraduate students, academic researchers and practitioners working on inequalities. Those already fluent in multilevel modelling will deepen their knowledge; beginners will gain a clear, step-by-step entry into intersectional multilevel modelling in practice.

1148135079
Intersectional Multilevel Modelling: Theory and Applications in Stata
Bridging feminist theory and cutting-edge statistics, this book introduces Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) and expands it into a contextual intersectional multilevel framework, revealing how power operates through intersecting identities and environments to generate systemic inequalities and how quantitative tools can expose, understand, and ultimately challenge them. 

It first clarifies why traditional interaction terms fail to fully capture intersectionality’s transformative aim: they overlook the simultaneous, context-specific ways that gender, race, class, sexuality and other dimensions of inequalities configure privilege and oppression. Using intersectional multilevel models, the author shows how it is possible to estimate both individual heterogeneity and group-level effects, then extends the approach to incorporate context. Worked examples in Stata guide readers through linear, binary and ordinal outcomes. A brief overview of Bayesian estimation and random slopes models is also provided. The book is accompanied by open datasets and reproducible code. Throughout, an ethical reflexive thread stresses category fluidity, disclosure risks and accountability to intersectionality’s transformative agenda, demonstrating the method’s power to reveal, and hopefully contributes to dismantling, structural inequalities. 

Designed for social scientists, policy analysts or management scholars seeking rigorous yet reflexive quantitative approaches, the book suits postgraduate students, academic researchers and practitioners working on inequalities. Those already fluent in multilevel modelling will deepen their knowledge; beginners will gain a clear, step-by-step entry into intersectional multilevel modelling in practice.

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Intersectional Multilevel Modelling: Theory and Applications in Stata

Intersectional Multilevel Modelling: Theory and Applications in Stata

by Anne Laure Humbert
Intersectional Multilevel Modelling: Theory and Applications in Stata

Intersectional Multilevel Modelling: Theory and Applications in Stata

by Anne Laure Humbert

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Overview

Bridging feminist theory and cutting-edge statistics, this book introduces Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) and expands it into a contextual intersectional multilevel framework, revealing how power operates through intersecting identities and environments to generate systemic inequalities and how quantitative tools can expose, understand, and ultimately challenge them. 

It first clarifies why traditional interaction terms fail to fully capture intersectionality’s transformative aim: they overlook the simultaneous, context-specific ways that gender, race, class, sexuality and other dimensions of inequalities configure privilege and oppression. Using intersectional multilevel models, the author shows how it is possible to estimate both individual heterogeneity and group-level effects, then extends the approach to incorporate context. Worked examples in Stata guide readers through linear, binary and ordinal outcomes. A brief overview of Bayesian estimation and random slopes models is also provided. The book is accompanied by open datasets and reproducible code. Throughout, an ethical reflexive thread stresses category fluidity, disclosure risks and accountability to intersectionality’s transformative agenda, demonstrating the method’s power to reveal, and hopefully contributes to dismantling, structural inequalities. 

Designed for social scientists, policy analysts or management scholars seeking rigorous yet reflexive quantitative approaches, the book suits postgraduate students, academic researchers and practitioners working on inequalities. Those already fluent in multilevel modelling will deepen their knowledge; beginners will gain a clear, step-by-step entry into intersectional multilevel modelling in practice.


Product Details

ISBN-13: 9781032877235
Publisher: Taylor & Francis
Publication date: 02/25/2026
Pages: 196
Product dimensions: 6.88(w) x 9.69(h) x (d)

About the Author

 Anne Laure Humbert is a researcher at the University of Gothenburg, Sweden.

Table of Contents

 

            Preface

1          Introduction: intersectional multilevel modelling

 

Part 1 Quantitative multilevel approaches to intersectional analysis: theoretical and statistical considerations

 

2          Intersectionality and quantitative approaches 

3          Key concepts in (intersectional) multilevel modelling 

            Part 2 Practical applications of intersectional multi-level modelling

 

4          Data sources and pre-processing 

5          Intersectional multilevel linear modelling in practice 

6          Intersectional multilevel binary logistic modelling in practice 

7          Intersectional multilevel ordinal logistic modelling in practice 

8          Advanced extensions in applying intersectional multilevel modelling 

9          Conclusion: Towards transformative intersectional quantitative practice

 

10        References

 

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