Multilevel models allow researchers to use data that has a clustered structure – such as pupils nested within schools, or individuals within neighbourhoods. Recently, a version of multilevel models has been developed for the study of intersectional inequalities in individual outcomes. With the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), individuals are nested within their intersectional strata – that is their combination of various sociodemographic identity categories –for instance gender, age, ethnicity and social class.

This method has great potential for uncovering and understanding intersectional inequalities, where a combination of social identities combine in complex ways to produce societal (dis)advantage.

This training course will provide a short introduction to the intersectional MAIHDA approach. We will briefly cover multilevel models more generally, before focusing on MAIHDA. We will then consider extensions of MAIHDA, for instance when considering varying slopes, or when using longitudinal data. Throughout, we will show how to use  the MAIHDA approach, some key statistics that can be produced from that approach, give advice on how to visualize the results that are produced, and how to interpret the results robustly.

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