🌟 AEA Methods seminar series 🌟

Our first seminar for 2026 is coming up at the end of this month: An overview of quasi-experimental methods for social and environmental epidemiology by Prof Tarik Benmarhnia

Date and time: Wednesday April 29th – 4:00pm AEST via Zoom

Bookings: lnkd.in/g77hRC5j

Handling Multivariable Missing Data in Causal Mediation Analysis Estimating Interventional Effects - PubMed The interventional effects approach to causal mediation analysis is increasingly common in epidemiologic research given its potential to address policy-relevant questions about hypothetical mediator interventions. Multiple imputation is widely used for handling multivariable missing data in epidemio …

Using causal mediation analysis but dealing with missing data? We provide a comprehensive overview of approaches for handling multivariable missing data in causal mediation analysis and evaluate their performance using simulation studies.

Read more: pubmed.ncbi.nlm.nih.gov/40167180/

Mark your diaries! The ViCBiostat Summer School returns from 13-20 Feb 2026, in Melbourne and online.
Courses include causal inference, cluster randomised trials, meta-analysis and the estimand framework.
Further details TBA shortly - sign up to our mailing list at www.vicbiostat.org.au
#statistics

Tracking the course of vaping and cigarette smoking across adolescence: the Child to Adult Transition Study These patterns of vaping and smoking in young Australians affirm that regulations and public health initiatives are urgently needed to prevent uptake of all nicotine and tobacco products.

Recent study in #Australia shows that 47% of adolescents reported #vaping at any frequency at age 20.

In contrast to the belief that vaping is short-lived, almost half of these adolescents were vaping across consecutive years & more than one-third reported #escalating use.

🔗 Full text below

Such a well-deserved recognition of your brilliant work!✨

Causal Machine Learning Methods and Use of Cross‐Fitting in Settings With High‐Dimensional Confounding Observational epidemiological studies commonly seek to estimate the causal effect of an exposure on an outcome. Adjustment for potential confounding bias in modern studies is challenging due to the p...

NEW PAPER!!! "Causal Machine Learning Methods and Use of Cross‐Fitting in Settings With High‐Dimensional Confounding"

led by Susie Ellul, with Stijn Vansteelandt & John Carlin
Published in Stats in Med

Check it out 👇
onlinelibrary.wiley.com/doi/10.1002/...

#EpiSky #CausalSky

The ideal trial: defining causal estimands that balance relevance and feasibility in target trial emulations and actual randomized trials Causal inference is the goal of randomized trials and many observational studies. The first step in a formal causal inference framework is to define the causal estimand, and in both types of study thi...

NEW PAPER! (in press in EPIDEMIOLOGY)

Have you wondered:
- How to specify a target trial: as an ideal trial or something else?
- What biases do target trial emulations and actual RCTs share?
- How does it all relate to potential outcomes?

Read here! 👉 arxiv.org/abs/2405.10026
#EpiSky #CausalSky

Recording of my talk @causalab.bsky.social on using m-DAGs to guide the treatment of missing data now available 👇 #EpiSky #CausalSky

Mediation effects that emulate a target randomised trial: Simulation-based evaluation of ill-defined interventions on multiple mediators - Margarita Moreno-Betancur, Paul Moran, Denise Becker, George ... Many epidemiological questions concern potential interventions to alter the pathways presumed to mediate an association. For example, we consider a study that i...

2/ The methodology uses interventional effects mapped to a “target trial” assessing the treatment strategies of interest, as proposed here tinyurl.com/yztb2hxs

🚨New method! So proud to see work led by @cttc101.bsky.social w/ @margaritamb.bsky.social @ghazalehd.bsky.social now available as an R package 📦
A powerful tool for estimating intervention effects via multiple mediators w/real examples to guide you!
Check it out ⬇️
#epitwitter #causaltwitter #rstats

1/ NEW R PACKAGE! For estimating the impact of potential interventions on multiple mediators in countering exposure effects (led by @cttc101.bsky.social)

- Paper👉 tinyurl.com/ye26jsps
- Package👉 tinyurl.com/yuh4kens

Thread shows published examples of how the method can be used! #EpiSky #CausalSky

@margaritamb.bsky.social @cebu-melbourne.bsky.social

Invited commentary: Descriptive social epidemiology: putting the question before the methods Abstract. In studies describing socioeconomic inequities in health outcomes, the choice of estimand and the planned analytic approach are central to the in

📢 New Commentary: We discuss how analytic choices impact interpretation of studies on socioeconomic health inequities. We review 1) descriptive analogues of causal estimands (à la Young et al) with competing events; 2) timescale choice; and 3) covariate adjustment.
👉 academic.oup.com/aje/advance-...

Looking forward to speaking at the CAUSALab methods seminar series next week! 👇

@margaritamb.bsky.social @julieasimpson50.bsky.social

@cebu-melbourne.bsky.social

Handling multivariable missing data in causal mediation... : Epidemiology miologic studies. However, guidance is lacking on best practice for using multiple imputation when estimating interventional mediation effects, specifically regarding the role of missingness mechanism...

📣 📣NEW PAPER providing guidance on best practice for using multiple imputation when estimating interventional mediation effects, considering missingness mechanism, multiple imputation model specification, & variance estimation
#CausalSky #EpiSky

Read more 👇🏽
journals.lww.com/epidem/abstr...

Advert for next Causal Inference Interest Group seminar. "Using missingness directed acyclic graphs (m-DAGs) to guide the treatment of multivariable missing data in epidemiological studies" with Margarita Moreno Betancur on 7th April 2025 at 9am BST.

"Using missingness directed acyclic graphs (m-DAGs) to guide the treatment of multivariable missing data in epidemiological studies"

Don't miss the next #CIIG seminar with @margaritamb.bsky.social on 7th April 2025 at *9am* BST!

Register at: turing-uk.zoom.us/meeting/regi...

#EpiSky #CausalSky

Our next Introduction to Biostatistics course will take place over 5 half days 9am -12.30pm on 24-28 March 2025 at @MCRI_for_kids. Read more and register here: www.mcri.edu.au/research/res... Reduced rates available for internal and LMIC participants, reach out: cebu.admin@mcri.edu.au

Seminar announcement🗣️

Prof Kelley Kidwell (Uni of Michigan): SMARTer Trials: Integrating Patient Treatment Preferences for Pragmatic Multi-Stage Trial Design & Analyses

27 Mar, 9:30am AEDT
Online + in person @ Monash SPHPM, Melbourne

Details - www.vicbiostat.org.au/seminars

Huge congratulations to our co-director @margaritamb.bsky.social for receiving an #NHMRC investigator grant to further her research work in #causalinference research !! 🥂🎉

Exciting Monday news with two of our brilliant researchers awarded NHMRC Investigator Grants 🎊

Congratulations Margarita Moreno-Betancur @margaritamb.bsky.social and Julie Simpson @julieasimpson50.bsky.social

More:
www.vicbiostat.org.au/news

@mischhub.bsky.social @cebu-melbourne.bsky.social

Massive congratulations! Incredibly well-deserved!!! 🤸🏽‍♂️🎉🥳

Thrilled to have received this funding for my causal inference research program - with my amazing team we shall continue to advance methods and provide expertise in this key area for another 5 years!!! 🥳☺️ #CausalSky #EpiSky

Another successful workshop from our missing data methods research group ✔️Led by Margarita Moreno-Betancur @margaritamb.bsky.social, with presenters Kate Lee, Ghazaleh Dashti @ghazalehd.bsky.social, Jiaxin Zhang, Cattram Nguyen, Melissa Middleton and Jessica Xu.

Thank you to all who came along!

Our research methods and software training course timetable for 2025 is out! check it out here 👇 www.mcri.edu.au/research/res...

We're off and away with Summer School 2025!

Jonathan Sterne @jonathanasterne.bsky.social is leading our Advanced causal inference course, ably assisted by tutors Ghazaleh Dashti @ghazalehd.bsky.social, Marnie Downes, Daisy Shepherd and Jiaxin Zhang from CEBU.

@margaritamb.bsky.social

Pre-diagnostic exposures and cancer survival: Can a... : Epidemiology An abstract is unavailable. This article is available as a PDF only.

NEW COMMENTARY in Epidemiology on causal estimands in studies of pre-diagnostic exposures and cancer survival

#EpiSkye #CausalSky

journals.lww.com/epidem/citat...

Multiple Imputation for Longitudinal Data: A Tutorial Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably correlated and thu....

Hot off the press! 📣📣In this tutorial we illustrate available multiple imputation approaches for handling longitudinal data including when they are clustered within higher level clusters. A reproducible example with R and Stata code provided! #OpenAccess

onlinelibrary.wiley.com/doi/10.1002/...

Correction to: “Canonical causal diagrams to guide the treatment of missing data in epidemiologic studies” Moreno-Betancur et al.1 report and correct here errors in their article “Canonical causal diagrams to guide the treatment of missing data in epidemiologic

NOW PUBLISHED! Correction to: “Canonical causal diagrams to guide the treatment of missing data in epidemiologic studies" doi.org/10.1093/aje/...

Grateful to have had the opportunity to correct our paper translating missingness DAGs (m-DAGs) into epidemiological practice #CausalSky #EpiSky