Pleased to see this out in print - detailing MAIHDA's desirable statistical properties. "MAIHDA is especially valuable when inequalities are subtle or data for marginalised intersections are sparse - conditions common in practice" journals.sagepub.com/doi/10.1177/... @clarerevans.bsky.social

Want to know how to use MAIHDA to examine heterogeniety in policy outcomes? Here's a nice worked-through example! How does intersectional identity impact preference for in-person vs online GP appoinments? Has been great working with @healthfoundation.bsky.social colleagues on this :)

Now officially out with nice formatting and all 🥳 "Thinking clearly about age, period, and cohort effects" -- a gentle introduction to the age-period-cohort problem and how to "solve" it through various types of assumptions. journals.sagepub.com/doi/10.1177/...

NCRM has opened applications to participate in the Research Methods Rendezvous! This free event will explore the process of turning early-stage ideas into #research projects. #RMR2025 takes place online on 10 September and 29 October 2025. Apply: www.ncrm.ac.uk/training/RMR...

Thanks to everybody who chimed in! I arrived at the conclusion that (1) there's a lot of interesting stuff about interactions and (2) the figure I was looking for does not exist. So, I made it myself! Here's a simple illustration of how to control for confounding in interactions:>

Our research on the effects that PIP changes could have on local economies, written by authors @nataliecbennett.bsky.social @profbambra.bsky.social & @lukemunford.bsky.social, was featured on the @itvpeston.bsky.social programme last night - you can watch the episode on catch up

Another q for the stats people! People worry about collinearity (cf blog post below). Consider a scenario in which the collinear predictors are just controls to account for confounding. Including both of them doesn't impair the precision with which the effect of interest is estimated, does it?

Multilevel Models: Practical Applications Curious about multilevel modelling but not sure where to start? Learn to recognise, build & interpret multilevel models using MLwiN or R, through real-world examples & hands-on practice. Find out more: bit.ly/3Yj5I4f #ESS2025

Still time to apply for this RA post- developing and applying the intersectional MAIHDA approach with @clarerevans.bsky.social and others. If you're a quantitative social scientist with an interest in quantitative methods and methods development, please apply! DMs open www.jobs.ac.uk/job/DMR190/r...

Come join George and I in Bristol, to learn about intersectional MAIHDA! bristol.ac.uk/cmm/software... @ncrm.ac.uk

It’s my first project too! In fact, it’s also my first in epidemiology since I come from philosophy. :) I find stratified graphs based on social categories (like Hernández-Yumar, 2018) really interesting.

A little story about this article & how teachers make a difference: In 2013, I was a student in a social epidemiology class taught by the esteemed David Williams. He observed, with some frustration while we looked at a series of graphs, that we often lump people into the “Hispanic” category — 1/

George Leckie and I have created a new short MAIHDA tutorial, with videos and practical exercises: www.ncrm.ac.uk/resources/on... It's based on our tutorial paper in SSM Pop Health, but shorter and more interactive. Hope it's helpful! @ncrm.ac.uk

Starting out using #intersectional MAIHDA analyses, so need to dig into this great tutorial paper by @clarerevans.bsky.social , Leckie, Subramanian, @andrewjdbell.bsky.social Juan Merlo 👏 www.sciencedirect.com/science/arti...

New paper published in Social Science and Medicine 'An analysis of intersectional disparities in alcohol consumption in the US'. Led by @sophiebright.bsky.social, this study identifies several understudied groups who may have higher alcohol consumption than traditional methods would suggest.

New preprint! osf.io/preprints/ps... The age-period-cohort problem is something that many researchers are vaguely aware of. There have been very cool advances in how to reason about it which don't seem to be well-known in psych. So, I've written a primer!

Rereading @andrewjdbell.bsky.social's 2020 paper on APC analysis & this is such a great example of how plots imply certain interpretations of the data. Same underlying data but depending on how you connect the lines, the implied age effect looks completely different.