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Dr Matthew Smith

Statistician Knowledge Transfer Partnership KTP Associate

United Kingdom

I am a statistician and Knowledge Transfer Partnership (KTP) Associate jointly based at the London School of Hygiene & Tropical Medicine and GSK. My current work focuses on integrating target trial emulation methods across multiple therapeutic areas within GSK, using real-world data to inform clinical development, regulatory strategy, and trial design. This involves the application of advanced causal inference methods and the translation of methodological research into industry practice.

 

I completed my PhD at LSHTM in 2020, where I examined socioeconomic inequalities in survival among patients with non-Hodgkin lymphoma. I also hold an MSc in Medical Statistics from LSHTM and a BSc in Mathematics from the University of Nottingham.

 

Before my current role, I was a postdoctoral research fellow in statistics within the Inequalities in Cancer Outcomes Network at LSHTM and co-investigator for the MRC-funded ROBEST project (Better Methods, Better Research award), which aimed to develop and promote double-robust causal inference methodology for applied researchers in public health, epidemiology, and clinical sciences.

 

I also hold an honorary research fellow position at the Institute of Health Informatics at University College London.

Affiliations

Department of Medical Statistics
Faculty of Epidemiology and Population Health

Teaching

I have previously contributed to postgraduate teaching on the MSc Medical Statistics course at LSHTM. This included co-organising the Causal Inference and Missing Data module and facilitating practical sessions for modules such as Generalised Linear Models and Analysis of Hierarchical and Other Dependent Data. I have also supervised MSc summer projects and served as a personal tutor to MSc students.

 

I currently supervise a PhD student conducting research into the relationship between mechanical ventilation and health outcomes in intensive care settings.

Research

My research focuses on the development, evaluation, and application of causal inference methods for observational data, with a particular emphasis on target trial emulation. I am especially interested in using real-world data to answer clinical questions that inform treatment decisions, trial design, and regulatory strategy.

 

I have contributed to the methodological advancement and applied implementation of target trial emulation, and in my current role as a Knowledge Transfer Partnership Associate between LSHTM and GSK, I am leading efforts to embed this framework across multiple therapeutic areas within the pharmaceutical setting.

 

My broader research includes evaluating the performance of double-robust estimators—particularly targeted maximum likelihood estimation (TMLE)—and exploring their use in longitudinal and survival data. I have published accessible introductions to causal inference for applied researchers and contributed to practical guidance for implementing TMLE and target trial emulation using real-world data.

Research Area
Health inequalities
Health outcomes
Modelling
Statistical methods
Epidemiology
Disease and Health Conditions
Cancer
Dementia, incl. Alzheimer's
Country
United Kingdom
Finland
United States of America
China
Region
Euro area

Selected Publications

Characteristics of interventions aimed at reducing inequalities along the cancer continuum: A scoping review
SAFARI, WC; GRAVENHORST, K; LEYRAT, C; SHIMIZU, K; SMITH, MJ; AGGARWAL, A; MARINGE, C;
2025
International journal of cancer
Performance of Cross-Validated Targeted Maximum Likelihood Estimation
SMITH, MJ; Phillips, RV; MARINGE, C; LUQUE-FERNANDEZ, MA;
2024
On Causal Inference for the Relative Survival Setting
SMITH, M;
2024
Pacific Causal Inference Conference
Performance of Cross-Validated Targeted Maximum Likelihood Estimation
SMITH, M;
2024
American Causal Inference Conference (ACIC)
Comparison of common multiple imputation approaches: An application of logistic regression with an interaction
SMITH, MJ; Quartagno, M; BELOT, A; RACHET, B; Njeru Njagi, E;
2024
Research methods in medicine & health sciences
Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review.
SMITH, MJ; Phillips, RV; LUQUE-FERNANDEZ, MA; MARINGE, C;
2023
Annals of epidemiology
On Causal Inference for the Relative Survival Setting
SMITH, M;
2023
European Causal Inference Meeting
Application of targeted maximum likelihood estimation in public health
and epidemiological studies: a systematic review
SMITH, MJ; Phillips, RV; LUQUE-FERNANDEZ, MA; Maringe, C;
2023
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