Rushani Wijesuriya

Flyer saying Save the date for the 2025 ViCBiostat Summer School

#ViCBiostat Summer School 13-20 Feb 2026

#Causal inference
#Estimands in trials
#Cluster randomised trials
Advanced #meta-analysis

In Melbs and online.
More details to come.
www.vicbiostat.org.au

My own TLDR for the message from this paper:

statsepi.substack.com/p/sorry-what...

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

Awarded every two years by Australian Academy of Science,
the Moran Medal honours outstanding Australian scientists in statistics & related fields. Huge congratulations to our Co-Director @margaritamb.bsky.social on this well-deserved recognition! 🎉🥳 #WomenInSTEM #ResearchExcellence

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

🚨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

🚨 A MUST-READ by John Carlin and @margaritamb.bsky.social including 6 commentaries and rejoinder

NOW PUBLISHED:
“On the Uses and Abuses of Regression Models: A Call for Reform of Statistical Practice and Teaching”

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

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...

Professor Margarita Moreno-Betancur - Moran Medal 2025 This is "Professor Margarita Moreno-Betancur - Moran Medal 2025" by Australian Academy of Science on Vimeo, the home for high quality videos and the people…

Over the moon to have received the Moran Medal from the Australian Academy of Science!🥳

Amazing recognition, hopefully highlighting the key role of biostats & causal inference in high-quality research vimeo.com/1065735362
tinyurl.com/2m3dx2ms
@cebu-melbourne.bsky.social @vicbiostat.bsky.social

Thrilled to share our new preprint on causal ML for mediation analysis! We introduce causal ML estimators for interventional effects explicitly mapped to target trials assessing hypothetical interventions inducing distinct shifts in joint mediator distributions📊 📈🧪
#CausalSky #EpiSky

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

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 VERY FIRST newsletter is here! 📬Use the link to access it and learn more about our group and the work/activities we do: shorturl.at/bzmio
@vicbiostat.bsky.social

So well deserved! Huge congratulations Margarita! 🥳🥳🥳

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

Really happy with how this went! Our first missing data workshop completely grounded on the use of missingness DAGs (m-DAGs) to specify missingness assumptions 😀 #EpiSky #CausalSky

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

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...

Moving beyond the prevalent exposure design for causal inference in dementia research As randomised trials are not always feasible or practical, observational studies remain crucial for addressing many causal questions in the dementia prevention field. Through a systematic search, we f...

New paper!! We find that prevalent exposure designs are very common in dementia research, explain why they are ill-suited for causal inference, and show how the target trial framework helps us move beyond them.

Read here👇 www.thelancet.com/journals/lan...

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

WORKSHOPS! On causal inference, missing data and SMARTs, part of the ViCBiostat Summer School (10-14 Feb, hybrid). For more details & registration visit: www.vicbiostat.org.au/short-courses

#CausalSky #EpiSky

@margaritamb.bsky.social @matteoq21.bsky.social

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/...