Centre for Statistical Methodology

The Centre for Statistical Methodology aims to gather statistical and methodological expertise across the School in order to strengthen our research capacity in epidemiology and public health.

Welcome to the LSHTM Centre for Statistical Methodology

The LSHTM Centre for Statistical Methodology aims to gather statistical and methodological expertise across the School in order to strengthen our research capacity in epidemiology and public health, and exploit the richness and interdisciplinarity of the work carried out within the School. This is in line with the School’s strategic plans for sustaining areas of established expertise in which we have an international reputation.

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Next CSM Seminar

The Centre hosts regular seminars across the different themes. The next seminar is:

Thursday 28 Nov 2019, 12:45-2:00pm
Bradford Hill Room K/LG09, Keppel Street

Title: "Selecting causal risk factors from high-throughput experiments using multivariable Mendelian randomization"
Verena Zuber (Imperial College London)

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Joint meeting of the British and Irish Region of the International Biometric Society and the Centre for Statistical Methodology

New perspectives on studying the effects of treatment on a time to event outcome

Date: Wednesday 2nd October 2019

Venue: De Morgan House, 57-58 Russell Square, London, WC1B 4HS.

Talks from five speakers will cover new methodology for estimating treatment effects using observational data, example applications using patient registry data in the fields of cancer and cystic fibrosis, and discussion of communication of treatment risks and benefits.

To register for the meeting please find further details at:
https://biometricsociety.org.uk/events/new-perspectives

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Centre for Statistical Methodology (CSM) symposium: Quantitative approaches to personalised medicine

This symposium will consider new approaches to the challenges of personalising treatment choices. The speakers will examine how the drive to personalise medicine raises issues and opportunities for:

- The life sciences industry, regulators, and reimbursement agencies
- Conventional statistical approaches to the evaluation of new technologies
- The conduct of future studies in the age of large-scale data
- The use of machine learning and data-adaptive methods.

Confirmed speakers:
John Whittaker, Vice President, Target Sciences, Glaxo Smith Klein Pharmaceuticals.
Professor Mihaela van der Schaar, Professor of Machine Learning, Artificial Intelligence and Medicine, University of Cambridge, Keynote Speaker.
Dr Karla Diaz-Ordaz, Associate Professor of Biostatistics, London School of Hygiene and Tropical Medicine.
Dr Brian Tom, MRC Biostatistics Unit, Cambridge.
Professor Andrew Briggs, Professor of Health Economics, London School of Hygiene and Tropical Medicine.
Professor Stephen Senn, Statistical consultant, Keynote Speaker.

See here to register.

Date: Tuesday November 12th 1.30-5.30pm.

Venue: etcvenue, Holburn, London.

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Recent seminar slides & audio

Slides and audio recordings of many of our previous seminars are available. Our most recent seminars have been:

Analysis of Clinical Trials Theme
Dealing with missing binary outcomes in cluster randomized trials: weighting vs. imputation methods
Elizabeth L. Turner (Duke University)

Causal Inference Theme
Causal inference and competing events
Jessica Young (Havard Medical School)

Big Data and Machine Learning Theme
Beyond the average: Contrasting targeted learning and causal forests for inference about conditional average treatment effects of social health insurance programmes
Noemi Kreif (University of York)

Causal Inference Theme
Post-“Modern Epidemiology”: when methods meet matter
George Davey Smith (University of Bristol)

Causal Inference Theme
A new approach to generalizability of clinical trials
Anders Huitfeldt (LSE)

Causal Inference Theme
Using Quantitative Bias Analysis to Deal with Misclassification in the Results Section, not the Discussion Section.
Matt Fox (Boston University)

Statistical Computing Theme
An extended mixed-effects model for meta-analysis: statistical framework and the R package mixmeta.
Antonio Gasparrini and Francesco Sera (LSHTM)

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Centre for Statistical Methodology Mini-Symposium: Landmarking for survival analysis

Friday 18th January 2019
LSHTM, Keppel Street

The Centre held a symposium on the “landmarking” method in January 2019, welcoming Professors Hans van Houwelingen and Hein Putter from Leiden University. Landmarking was proposed by Van Houwelingen as a method for dynamic prediction of survival in a 2007 paper (Scandinavian Journal of Statistics 2007; 34: 70-85). This was followed by a number of further developments in collaboration with Putter, including as a method for multistate modelling. Their book Dynamic Prediction in Clinical Survival Analysis was published in 2012 (CRC Press). Van Houwelingen and Putter will give a joint seminar on some new developments in landmarking.

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