How can we combine "MAIHDA" and intersectionality theory to help policy makers uncover heterogeneous policy effects?

Speaker(s):

Andrew Bell, University of Sheffield

Abstract:

This session will start by introducing the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) method, and the work that we have been doing to combine it with policy analysis techniques. The aim is to develop a method that allows us to uncover variation in policy effect sizes - that is, to see where policies that work on average actually only work for particular groups, and are ineffective (or even potentially cause harm) to other groups. Following an introduction, we will introduce two short presentations that show some of the work we are doing in this area relating to particular policies: national cancer screening policies, and online vs face-to-face primary care appointments. We will then introduce some of the challenges in implementing these methods, including conceptual, statistical, and data issues. This will be followed by discussion, in breakout groups, about how those challenges can be overcome.