G-formula with multiple imputation for causal inference with incomplete data. Jonathan W Bartlett, Camila Olarte Parra, Emily Granger, Ruth H Keogh, Erik W van Zwet, Rhian M Daniel. Statistical Methods in Medical Research. https://t.co/oQxMEseDgx
We’re happy to be welcoming @SofiaSVillar1 for our next seminar to discuss recent developments in response-adaptive randomization
🗓️ Tuesday 10 December
🕰️ 12:50 (UK time)
📍 Online | LSHTM
Details ⬇️
https://t.co/yGvukuJ8Ip
Our paper on applying missingness DAGs to longitudinal trial data has just been published in Biostatistics: https://t.co/SoR67wiYRP
A challenging but rewarding experience.
We give ideas on useful rules of thumbs & how to explore deviations from the assumed missingness process.
When selecting a causal estimand, it’s crucial to balance asking the right question with the feasibility of answering it under realistic assumptions. Ignoring this in clinical trials risks chasing shadows. https://t.co/X7N63g2WFb 1/2 #CausalInference#PharmaStats#Estimands
check out the latest article from ASA BIOP Covariate Adjustment SWG here https://t.co/YDWh6ZFCCm
"Covariate Adjustment for Linear Models: Understanding FDA Advice on Standard Errors"
24th September - please join us online for Devan Mehrotra's seminar on 'Covariate adjustment using treatment-blinded covariate selection within randomized clinical trials', hosted by @LSHTM_datastats.
https://t.co/Wgg1LBTvPN
Our next journal club is scheduled on Sep 13 at 11am EST.
Speaker: Kelly Van Lancker, Ghent University
Zoom link: https://t.co/K4EreJhGkp
Title: Automated, efficient and model-free inference for randomized clinical trials via data-driven covariate adjustment
Come and work with @DrPerpo, Adrian Mander, @RuthHKeogh and I on a 3 year Knowledge Transfer Partnership between @GSK and @LSHTM. More details here: https://t.co/kwOpbK9i2G
Win ratio has been widely used, but so far with little attention to its estimand. I argue for articulating the estimand as a first step to analysis, and explain how👇
https://t.co/UtCu2RdvZe
@CatchTwentyToo My guess is that you shouldn't view them as independent events-a patch of rain is moving across an area, and the uncertainty is mostly when will it rain and not if? And to calculate the prob of a dry day you'd need to assume/know something about the dependence of hourly outcomes.
Exciting job opportunity for a talented statistician to join us at the Early Phase & Adaptive Trials Group @ICR_CTSU as a Trials Methodologist! If you enjoy developing and implementing efficient trial methods to impact patients’ lives, come and join us! https://t.co/KKZvR1le7Q
Paul Newcombe (GSK) seminar 'Causal Machine Learning for Biomarker Subgroup Discovery in Randomised Trials' @LSHTM_datastats 16th July online and in person https://t.co/MjTosdG1VJ
Our (with @Frank_Bretz and Oliver Dukes) review article on covariate adjustment for marginal treatment effects is now published in Clinical Trials: https://t.co/uDZkbdx1bu; along with a commentary by @f2harrell : https://t.co/dR3VdL2uPH and our rejoinder: https://t.co/0BzG0ZD5Cf.