Jonathan Bartlett
@TheStatsGeek
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Biostatistician with interests in missing data, causal inference, clinical trials. Professor in Medical Statistics at @LSHTM
Bath, England
Joined May 2014
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.
journals.sagepub.com
G-formula is a popular approach for estimating the effects of time-varying treatments or exposures from longitudinal data. G-formula is typically implemented us...
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Don’t forget to join our seminar with @SofiaSVillar1 who will discuss recent developments in response-adaptive randomization 🗓️ Tuesday 10 December 🕰️ 12:50 (UK time) 📍 Online | LSHTM Details ⬇️ https://t.co/yGvukuJ8Ip
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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
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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.
academic.oup.com
Summary. Missing data in multiple variables is a common issue. We investigate the applicability of the framework of graphical models for handling missing d
Causal inference with missing data? Are missingness DAGs and graphical M(N)AR concepts, as proposed by @Carthica & @yudapearl, readily applicable to complex longitudinal studies? Check out our preprint led by @a_holovchak 👇 https://t.co/QhI9K17YlB
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Does the SE formula for a sample proportion assume equal 'success' probabilities?
thestatsgeek.com
When you estimate a proportion and want to calculate a standard error for the estimate, you would normally do so based on assuming that the number of ‘successes’ in the sample is a draw…
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Multiple imputation with flexible parametric survival models
thestatsgeek.com
Following a recent request from someone, I’ve extended the functionality of my R package smcfcs, which performs multiple imputation of missing covariates, compatible with a user-specified sub…
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The @CAUSALab Methods Series at @karolinskainst is back! @jonathanasterne @BristolUni kicks off Fall 2024 with a virtual talk on COVID-19 vaccine effectiveness & OpenSAFELY. Register to attend 👇 https://t.co/p4tKqGZSnc
#causalinference #targettrial #publichealth #causal
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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
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Estimand resources available online as highlighted by @Brennan_Kahan at #ICTMC2024 this morning:
osf.io
This page contains materials from a MRC-NIHR-TMRP funded workshop which covered the statistical methods that can be used to estimate different estimands, including estimation methods for each...
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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"
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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
lshtm.ac.uk
When estimating treatment effects in randomized clinical trials, the primary goal of covariate-adjustment is to improve precision (e.g., for linear models) and/or reduce bias (e.g., for non-linear
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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
umich.zoom.us
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Come and work with @DrPerpo, Adrian Mander, @RuthHKeogh and I on a 3 year Knowledge Transfer Partnership between @GSK and @LSHTM. More details here:
jobs.lshtm.ac.uk
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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
journals.sagepub.com
The win ratio has been increasingly used in trials with hierarchical composite endpoints. While the outcomes involved and the rule for their comparisons vary wi...
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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!
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Paul Newcombe (GSK) seminar 'Causal Machine Learning for Biomarker Subgroup Discovery in Randomised Trials' @LSHTM_datastats 16th July online and in person
lshtm.ac.uk
Decreasing costs of high-throughput ‘omics, as well as new technologies such as the Olink proteomics platform, has driven wider application in clinical trials, for example to inform precision medicine
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Multiple imputation for missing covariates in the Fine & Gray model for competing risks, by @edbonneville.
thestatsgeek.com
Competing risks and the Fine & Gray model In the setting of competing risks, one approach involves modelling the effects of covariates on the so-called cause specific hazard functions for each …
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Finally the debate is settled...., or not.
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.
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One week left to apply for a Health Data Science Post Doc with me as part of the @ai4cihub! https://t.co/y90o1Aysbe There is lots of flexibility in methodology you could pursue and an unbeatable team of collaborators!
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Join me for the 33rd Joint @LSHTM - @RoyalStatSoc Perspectives on Statistics in Medicine Annual Lecture (formerly Bradford Hill Memorial Lecture). 📅 26th June 2024 ⏲️ 1730-1830 (BST) 📍 John Snow Lecture Theatre, @LSHTM WC1E 7HT Link to join online: https://t.co/0kArcIwTHt
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