Research Fellow post at LSHTM. Come and work with Njeru Njagi, Matteo Quartagno, Wende Clarence Safari, Aurélien Belot, Bernard Rachet and myself on extending multiple imputation methods, in particular for analyses of electronic health records in cancer. jobs.lshtm.ac.uk/vacancy.aspx...

Job Opportunity at LSHTM: Research Fellow in Statistics

The London School of Hygiene & Tropical Medicine (LSHTM) is one of the world’s leading public health universities. Our mission is to improve health and health equity in the UK and worldwide; working i...

jobs.lshtm.ac.uk

Next Thursday (23rd July), joins us online or at LSHTM for a @lshtm-dash.bsky.social seminar by Mia Tackney (MRC BSU) on her work 'Capturing the curve: Functional data analysis for validated digital outcome measures'. More details here: www.lshtm.ac.uk/newsevents/e...

Capturing the curve: Functional data analysis for validated digital outcome

The use of digital health technologies to measure outcomes in clinical trials opens new opportunities as well as methodological challenges. Digital outcome measures can provide more convenient data

lshtm.ac.uk

New paper 'The role of post intercurrent event data in the estimation of hypothetical estimands in clinical trials', now available in Statistics in Biopharmaceutical Research doi.org/10.1080/1946... and open-access at researchonline.lshtm.ac.uk/id/eprint/46...

Thursday 11th June, join us at LSHTM or online to hear from Rebecca Whittle on 'How large is large enough? Sample size calculations for clinical prediction models'. Further details here: www.lshtm.ac.uk/newsevents/e... @lshtm-dash.bsky.social

How large is large enough? Sample size calculations for clinical prediction

Clinical prediction models are increasingly used to support decision-making, yet guidance on how large a dataset is needed to develop a reliable model remains limited. In practice, sample size is

lshtm.ac.uk

Perspectives on statistics in medicine: Annual joint LSHTM/RSS lecture on 16th June, by Prof. Marion Campbell. Further details here: www.lshtm.ac.uk/newsevents/e...

Perspectives on statistics in medicine: Annual joint LSHTM/RSS lecture | LSHTM

Future directions in the evaluation of innovative technologies in healthcare: Technology in healthcare is rapidly advancing. For example, a recent healthcare report suggests that 9 out of 10

lshtm.ac.uk

A few places left on our online 3 day course on multiple imputation for missing data...

Jonathan Bartlett@jonathan-bartlett.bsky.social · 7mo ago

@lshtm.bsky.social will be running a 3-day online short course on using multiple imputation to handle missing data on 23-25th June 2026. Teaching staff include James Carpenter, Ruth Keogh, Clémence Leyrat, and myself. Further details about the course at www.lshtm.ac.uk/study/course...

Come and join us this Tuesday to hear 'The test negative design: What bias is it intended to address?' @lshtm-dash.bsky.social www.lshtm.ac.uk/newsevents/e...

The test-negative design: What bias is it intended to address? | LSHTM

Test-negative studies recruit ‘cases’ who test positive for a particular disease; ‘controls’ are patients undergoing the same tests for the same medical reasons and who test negative. The design is

lshtm.ac.uk

Please join us in person or online @lshtm-dash.bsky.social on 26th February to hear about @georgiatomova.bsky.social's recent work on 'How can different modes of survey data collection introduce bias?' www.lshtm.ac.uk/newsevents/e...

How can different modes of survey data collection introduce bias? | LSHTM

Survey data are self-reported data collected directly from respondents by a questionnaire or an interview, and are commonly used in health research. Such data are traditionally collected via a single

lshtm.ac.uk

'How to interpret hazard ratios', with @dominicmagirr.bsky.social and @timpmorris.bsky.social thestatsgeek.com/2026/01/15/h...

How to interpret hazard ratios

Survival analysis of time-to-event outcomes is very commonly performed using Cox’s famous proportional hazards model. The model estimates hazard ratios for the ‘effects’ of covari…

thestatsgeek.com

@lshtm.bsky.social will be running a 3-day online short course on using multiple imputation to handle missing data on 23-25th June 2026. Teaching staff include James Carpenter, Ruth Keogh, Clémence Leyrat, and myself. Further details about the course at www.lshtm.ac.uk/study/course...

🥳 Registration for abstracts for EuroCIM 2026 (Oxford) is now OPEN and the deadline for submissions is 9 January 2026: eurocim.org/oxford-2026/... 👉 Theme? “Causal inference in health, economic and social science” 👉 When? April 14-17 👉 Where? Oxford 👉 Register? eurocim.org/oxford-2026/...

New PhD position available at @mrcctu.bsky.social to develop guidance on balancing statistical and clinical considerations when choosing an estimand in RCTs. www.findaphd.com/phds/project...

Optimising the choice of estimand in randomised trials: developing guidance on balancing statistical and clinical considerations to ensure results matter to stakeholders at University College London o...

PhD Project - Optimising the choice of estimand in randomised trials: developing guidance on balancing statistical and clinical considerations to ensure results matter to stakeholders at University Co...

findaphd.com

Thinking of performing a quantitative bias analysis for measurement error or misclassification? Then our recent software review, by Codie Wood, Kate Tilling, myself and Rachael Hughes, may be of interest: rdcu.be/eDRn2

Are estimands being correctly used? A new review of protocols led by Timothy Clark shows many incorrectly defined estimand attributes. See the top areas for improvement & full results here: trialsjournal.biomedcentral.com/articles/10.... #Trials

September @vicbiostat.bsky.social seminar: Camila Olarte Parra from @causalab.bsky.social Karolinska will speak on combining information from trial participants and non-participants in registry-based trials. All welcome online 25 September. More info: www.vicbiostat.org.au/event/combin...

We are recruiting a Research Fellow to develop machine learning based methods for handling missing data @lshtm.bsky.social. See jobs.lshtm.ac.uk/vacancy.aspx... for more details.

Job Opportunity at LSHTM: Research Fellow

The London School of Hygiene & Tropical Medicine (LSHTM) is one of the world’s leading public health universities. Our mission is to improve health and health equity in the UK and worldwide; working i...

jobs.lshtm.ac.uk

We are looking forward to hearing @jonathan-bartlett.bsky.social speak on the G-formula for causal inference using synthetic multiple imputation at the July @vicbiostat.bsky.social seminar! All welcome online Thursday 24th, 4:00pm Aus EST (7:00am UK time). www.vicbiostat.org.au/event/g-form...

HIRING! 2 PhD openings within the “Safe Causal Inference” consortium with experts from biostatistics, computer science, math, and epidemiology. You'll develop new methods to evaluate prediction algorithms that take the causal effect of treatments into account. 👉 www.lumc.nl/en/about-lum....

PhD Candidates Causal machine learning – Performance assessment of causal predictive algorithms | LUMC

Do you want to work on challenging problems within causal inference and contribute to algorithms that support treatment decisions for individual patients? As PhD candidate causal machine learning at t...

lumc.nl

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

📣 Calling everyone working in #datascience #biostatistics #clinicaltrials We’re bringing together experts on target-trial emulation and other frameworks, where we’ll explore the role and potential of observational data for evaluating the effects of interventions Don’t miss out 🔽 bit.ly/TTE_25

🚨 Next month, we’ll be hosting a one-day event on target-trial emulation and other frameworks, exploring the role and potential of observational data for evaluating the effects of interventions Open to everyone working in #datascience #biostatistics #clinicaltrials Get your ticket 🔽 bit.ly/TTE_25

Join us on 10th June (online or in London @lshtm-dash.bsky.social ) to hear from Matthew Sperrin talk about his work on 'Prediction under intervention: challenges and trade-offs'.More details at www.lshtm.ac.uk/newsevents/e...

Prediction under intervention: challenges and trade-offs | LSHTM

Causality and prediction are often two separate activities. In particular, prediction can be done in a way that is agnostic to underlying knowledge, mechanism or causal structure. However, it is very

lshtm.ac.uk

📆 SAVE THE DATE: 26 June 📆 for our 1-day event on “Target trial emulation and other frameworks: The role and potential of observational data for evaluating effects of interventions”, hosted by the Centre for Data & Statistical Science for Health (DASH) at LSHTM. @lshtm-dash.bsky.social

Should data observed after intercurrent events handled by the hypothetical strategy be used in estimation of treatment effects? Rhian Daniel and I investigate... thestatsgeek.com/2025/04/03/t...

The role of post intercurrent event data in the estimation of hypothetical estimands in clinical trials

Clinical trial estimands which make use of the so-called hypothetical strategy target the effect of one randomised treatment compared to another in a scenario where the corresponding intercurrent e…

thestatsgeek.com

'G-formula with multiple imputation for causal inference with incomplete data'. Open access in Statistical Methods in Medical Research. doi.org/10.1177/0962...

📣 📣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...

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...

journals.lww.com

New paper! We extend my prior work on prognostic adjustment to work with generalized linear models. This is a nice way to gain power in randomized trials (eg with binary outcomes) by leveraging historical data in a way that does not sacrifice type I error control. arxiv.org/abs/2503.22284

Powering RCTs for marginal effects with GLMs using prognostic score adjustment

In randomized clinical trials (RCTs), the accurate estimation of marginal treatment effects is crucial for determining the efficacy of interventions. Enhancing the statistical power of these analyses ...

arxiv.org

Imputation of factor variables when you have partial information about some of the missing values. See here for more details thestatsgeek.com/2025/03/27/m...

Multiple imputation for coarsened (grouped) factor covariates

Missing data are a common problem in statistical analyses. A closely related but slightly different problem is when for an individual in a dataset, although we do not know the exact value of a part…

thestatsgeek.com

3rd April, in London and online, come and hear @rlgrant.bsky.social talk about his new book with Gian Luca Di Tanna on Bayesian meta-analysis. Further details at www.lshtm.ac.uk/newsevents/e...

Demystifying Bayesian meta-analysis for researchers | LSHTM

Bayesian models offer a powerful framework for meta-analysis through their flexible and probabilistic treatment of uncertainty.There are several methodological challenges in evidence synthesis,

lshtm.ac.uk

The EuroCIM program is live! Explore the sessions, speakers, and schedule here: www.eurocim.org/program.html. Get ready for an exciting conference! 🎉