I am seeking to support an applicant for a PhD scholarship from the UBEL DTP to pursue at PhD at LSHTM, starting October 2027. The topic is about developing machine learning methods for handling missi...

Dichotomisation of continuous outcomes into 'responder' and 'non-responder' categories remains widespread in clinical research, particularly where a threshold carries clinical meaning (e.g. blood

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...

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

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

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

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

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

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…

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...

Even though the advantages of randomised tria

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...

G-formula is a popular approach for estimatin

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...

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

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…

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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...

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 ...

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…

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,

Introduction: Missing data is a challenge to medical research. Accounting for missing data by imputing or weighting conditional on covariates relies on the variable with missingness being observed at ...

While well-established methods for time-to-event data are available when the proportional hazards assumption holds, there is no consensus on the best inferential approach under non-proportional hazar...

To precisely define the treatment effect of interest in a clinical trial, the ICH E9 estimand addendum describes that relevant so-called intercurrent events should be identified and strategies specifi...

ABSTRACT. The ICH E9 addendum on estimands in clinical trials provides a framework for precisely defining the treatment effect that is to be estimated, but

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

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....

Job title: Four year postdoc position at the Oslo Centre for Biostatistics and Epidemiology (OCBE) (272144), Employer: University of Oslo, Deadline: Friday, January 31, 2025

YouTube video by World Congress of Epidemiology 2024

The creation of the ICH E9 (R1) estimands framework has led to more precise specification of the treatment effects of interest in the design and statistical analysis of clinical trials. However, it is...