Rushani Wijesuriya

@rush-099.bsky.social

Postdoctoral biostatistician at Murdoch Children's Research Institute and University of Melbourne★Biostatistics research : causal inference and missing data problems in child health, population allergy and social epidemiology ★she/her ★Views my own

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

Margarita Moreno-Betancur@margaritamb.bsky.social · 10mo ago

A few weeks ago I went to Canberra to receive the Moran Medal at the lovely Shine Dome of the Australian Academy of Science (@science.org.au). It was a huge honour, and wonderful to hear talks from all corners of science and to learn about the Academy's great work supporting science - pics below!

🚨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

Margarita Moreno-Betancur@margaritamb.bsky.social · last yr.

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

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

ArXiv Paperboy (Stat.ME+Econ.EM)@paperposterbot.bsky.social · last yr.

link 📈🤖 Causal machine learning for high-dimensional mediation analysis using interventional effects mapped to a target trial (Chen, Vansteelandt, Burgner et al) Causal mediation analysis examines causal pathways linking exposures to disease. The estimation of interventional effects, which are me

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

ViCBiostat@vicbiostat.bsky.social · last yr.

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!

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

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

doi.org

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/...

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....

onlinelibrary.wiley.com