Dates: Tues 5th, Thurs 7th, Tues 19th & Thurs 21st September 2023 Time: 13:00-17:00 BST (each day) Location: Online Speakers: Elizabeth Williamson, Clemence Leyrat, and John Tazare (all from LSHTM)
Who is this event intended for? Statisticians looking to understand how to understand and implement propensity scores for use of external data.
What is the benefit of attending? Participants will be able to come away with a practical understanding of when to use, and how to use, propensity score methods.
Course cost
Early Bird PSI Members = £320+VAT Early Bird Non-Members = £430*+VAT *Please note: Early Bird prices expire at 23:30 on Monday 7th August.
Standard PSI Members = £360+VAT Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.
Please see below an outline of the four sessions.
Session
Topic
Session 1
Introduction to propensity scores
Propensity score methods
Practical exercise using R
Session 2
Estimating the propensity score
Propensity scores for multi-valued treatments
Practical exercise using R
Session 3
Handling missing data
High dimensional propensity scores
Practical exercise using R
Session 4
Outcome regression and double robustness
Time-varying scenarios
Practical exercise using R
Speaker details
Speaker
Biography
Elizabeth Williamson LSHTM
Elizabeth Williamson is a Professor of Biostatistics and Health Data Science at the London School of Hygiene and Tropical Medicine. Her research focuses on improving statistical methods for using electronic health record data for research. Elizabeth has a long-term interest in propensity scores, beginning with her PhD in 2003-7 which explored issues around variance estimation, moving on to handling missing data within propensity scores and, more recently, exploring high-dimensional confounding within propensity score analysis.
Clemence Leyrat LSHTM
Clemence Leyrat is an Associate Professor in Medical Statistics at the London School of Hygiene and Tropical Medicine. Since completing her PhD in 2014 on the use of propensity scores in cluster randomised trials, most of her research has focused on causal inference methods for the analysis of observational studies, including trial emulation. More recently, she has been investigating the properties of propensity score weighting in longitudinal settings and in the presence of clustering by hospital.
John Tazare LSHTM
John Tazare is an Assistant Professor in Statistical Pharmacoepidemiology at the London School of Hygiene and Tropical Medicine. In 2021, John completed a PhD surrounding the use of high-dimensional propensity scores in UK electronic health records. John’s current research areas include the use of time-conditional propensity scores in prevalent new user designs and applications of causal inference methods (for example, clone-censor weighting approaches) for target trial emulation in non-randomised settings.
Scientific Meetings
PSI Training Course: Propensity Scores - practical application in non-randomised studies
Dates: Tues 5th, Thurs 7th, Tues 19th & Thurs 21st September 2023 Time: 13:00-17:00 BST (each day) Location: Online Speakers: Elizabeth Williamson, Clemence Leyrat, and John Tazare (all from LSHTM)
Who is this event intended for? Statisticians looking to understand how to understand and implement propensity scores for use of external data.
What is the benefit of attending? Participants will be able to come away with a practical understanding of when to use, and how to use, propensity score methods.
Course cost
Early Bird PSI Members = £320+VAT Early Bird Non-Members = £430*+VAT *Please note: Early Bird prices expire at 23:30 on Monday 7th August.
Standard PSI Members = £360+VAT Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.
Please see below an outline of the four sessions.
Session
Topic
Session 1
Introduction to propensity scores
Propensity score methods
Practical exercise using R
Session 2
Estimating the propensity score
Propensity scores for multi-valued treatments
Practical exercise using R
Session 3
Handling missing data
High dimensional propensity scores
Practical exercise using R
Session 4
Outcome regression and double robustness
Time-varying scenarios
Practical exercise using R
Speaker details
Speaker
Biography
Elizabeth Williamson LSHTM
Elizabeth Williamson is a Professor of Biostatistics and Health Data Science at the London School of Hygiene and Tropical Medicine. Her research focuses on improving statistical methods for using electronic health record data for research. Elizabeth has a long-term interest in propensity scores, beginning with her PhD in 2003-7 which explored issues around variance estimation, moving on to handling missing data within propensity scores and, more recently, exploring high-dimensional confounding within propensity score analysis.
Clemence Leyrat LSHTM
Clemence Leyrat is an Associate Professor in Medical Statistics at the London School of Hygiene and Tropical Medicine. Since completing her PhD in 2014 on the use of propensity scores in cluster randomised trials, most of her research has focused on causal inference methods for the analysis of observational studies, including trial emulation. More recently, she has been investigating the properties of propensity score weighting in longitudinal settings and in the presence of clustering by hospital.
John Tazare LSHTM
John Tazare is an Assistant Professor in Statistical Pharmacoepidemiology at the London School of Hygiene and Tropical Medicine. In 2021, John completed a PhD surrounding the use of high-dimensional propensity scores in UK electronic health records. John’s current research areas include the use of time-conditional propensity scores in prevalent new user designs and applications of causal inference methods (for example, clone-censor weighting approaches) for target trial emulation in non-randomised settings.
Training Courses
PSI Training Course: Propensity Scores - practical application in non-randomised studies
Dates: Tues 5th, Thurs 7th, Tues 19th & Thurs 21st September 2023 Time: 13:00-17:00 BST (each day) Location: Online Speakers: Elizabeth Williamson, Clemence Leyrat, and John Tazare (all from LSHTM)
Who is this event intended for? Statisticians looking to understand how to understand and implement propensity scores for use of external data.
What is the benefit of attending? Participants will be able to come away with a practical understanding of when to use, and how to use, propensity score methods.
Course cost
Early Bird PSI Members = £320+VAT Early Bird Non-Members = £430*+VAT *Please note: Early Bird prices expire at 23:30 on Monday 7th August.
Standard PSI Members = £360+VAT Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.
Please see below an outline of the four sessions.
Session
Topic
Session 1
Introduction to propensity scores
Propensity score methods
Practical exercise using R
Session 2
Estimating the propensity score
Propensity scores for multi-valued treatments
Practical exercise using R
Session 3
Handling missing data
High dimensional propensity scores
Practical exercise using R
Session 4
Outcome regression and double robustness
Time-varying scenarios
Practical exercise using R
Speaker details
Speaker
Biography
Elizabeth Williamson LSHTM
Elizabeth Williamson is a Professor of Biostatistics and Health Data Science at the London School of Hygiene and Tropical Medicine. Her research focuses on improving statistical methods for using electronic health record data for research. Elizabeth has a long-term interest in propensity scores, beginning with her PhD in 2003-7 which explored issues around variance estimation, moving on to handling missing data within propensity scores and, more recently, exploring high-dimensional confounding within propensity score analysis.
Clemence Leyrat LSHTM
Clemence Leyrat is an Associate Professor in Medical Statistics at the London School of Hygiene and Tropical Medicine. Since completing her PhD in 2014 on the use of propensity scores in cluster randomised trials, most of her research has focused on causal inference methods for the analysis of observational studies, including trial emulation. More recently, she has been investigating the properties of propensity score weighting in longitudinal settings and in the presence of clustering by hospital.
John Tazare LSHTM
John Tazare is an Assistant Professor in Statistical Pharmacoepidemiology at the London School of Hygiene and Tropical Medicine. In 2021, John completed a PhD surrounding the use of high-dimensional propensity scores in UK electronic health records. John’s current research areas include the use of time-conditional propensity scores in prevalent new user designs and applications of causal inference methods (for example, clone-censor weighting approaches) for target trial emulation in non-randomised settings.
Journal Club
PSI Training Course: Propensity Scores - practical application in non-randomised studies
Dates: Tues 5th, Thurs 7th, Tues 19th & Thurs 21st September 2023 Time: 13:00-17:00 BST (each day) Location: Online Speakers: Elizabeth Williamson, Clemence Leyrat, and John Tazare (all from LSHTM)
Who is this event intended for? Statisticians looking to understand how to understand and implement propensity scores for use of external data.
What is the benefit of attending? Participants will be able to come away with a practical understanding of when to use, and how to use, propensity score methods.
Course cost
Early Bird PSI Members = £320+VAT Early Bird Non-Members = £430*+VAT *Please note: Early Bird prices expire at 23:30 on Monday 7th August.
Standard PSI Members = £360+VAT Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.
Please see below an outline of the four sessions.
Session
Topic
Session 1
Introduction to propensity scores
Propensity score methods
Practical exercise using R
Session 2
Estimating the propensity score
Propensity scores for multi-valued treatments
Practical exercise using R
Session 3
Handling missing data
High dimensional propensity scores
Practical exercise using R
Session 4
Outcome regression and double robustness
Time-varying scenarios
Practical exercise using R
Speaker details
Speaker
Biography
Elizabeth Williamson LSHTM
Elizabeth Williamson is a Professor of Biostatistics and Health Data Science at the London School of Hygiene and Tropical Medicine. Her research focuses on improving statistical methods for using electronic health record data for research. Elizabeth has a long-term interest in propensity scores, beginning with her PhD in 2003-7 which explored issues around variance estimation, moving on to handling missing data within propensity scores and, more recently, exploring high-dimensional confounding within propensity score analysis.
Clemence Leyrat LSHTM
Clemence Leyrat is an Associate Professor in Medical Statistics at the London School of Hygiene and Tropical Medicine. Since completing her PhD in 2014 on the use of propensity scores in cluster randomised trials, most of her research has focused on causal inference methods for the analysis of observational studies, including trial emulation. More recently, she has been investigating the properties of propensity score weighting in longitudinal settings and in the presence of clustering by hospital.
John Tazare LSHTM
John Tazare is an Assistant Professor in Statistical Pharmacoepidemiology at the London School of Hygiene and Tropical Medicine. In 2021, John completed a PhD surrounding the use of high-dimensional propensity scores in UK electronic health records. John’s current research areas include the use of time-conditional propensity scores in prevalent new user designs and applications of causal inference methods (for example, clone-censor weighting approaches) for target trial emulation in non-randomised settings.
Webinars
PSI Training Course: Propensity Scores - practical application in non-randomised studies
Dates: Tues 5th, Thurs 7th, Tues 19th & Thurs 21st September 2023 Time: 13:00-17:00 BST (each day) Location: Online Speakers: Elizabeth Williamson, Clemence Leyrat, and John Tazare (all from LSHTM)
Who is this event intended for? Statisticians looking to understand how to understand and implement propensity scores for use of external data.
What is the benefit of attending? Participants will be able to come away with a practical understanding of when to use, and how to use, propensity score methods.
Course cost
Early Bird PSI Members = £320+VAT Early Bird Non-Members = £430*+VAT *Please note: Early Bird prices expire at 23:30 on Monday 7th August.
Standard PSI Members = £360+VAT Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.
Please see below an outline of the four sessions.
Session
Topic
Session 1
Introduction to propensity scores
Propensity score methods
Practical exercise using R
Session 2
Estimating the propensity score
Propensity scores for multi-valued treatments
Practical exercise using R
Session 3
Handling missing data
High dimensional propensity scores
Practical exercise using R
Session 4
Outcome regression and double robustness
Time-varying scenarios
Practical exercise using R
Speaker details
Speaker
Biography
Elizabeth Williamson LSHTM
Elizabeth Williamson is a Professor of Biostatistics and Health Data Science at the London School of Hygiene and Tropical Medicine. Her research focuses on improving statistical methods for using electronic health record data for research. Elizabeth has a long-term interest in propensity scores, beginning with her PhD in 2003-7 which explored issues around variance estimation, moving on to handling missing data within propensity scores and, more recently, exploring high-dimensional confounding within propensity score analysis.
Clemence Leyrat LSHTM
Clemence Leyrat is an Associate Professor in Medical Statistics at the London School of Hygiene and Tropical Medicine. Since completing her PhD in 2014 on the use of propensity scores in cluster randomised trials, most of her research has focused on causal inference methods for the analysis of observational studies, including trial emulation. More recently, she has been investigating the properties of propensity score weighting in longitudinal settings and in the presence of clustering by hospital.
John Tazare LSHTM
John Tazare is an Assistant Professor in Statistical Pharmacoepidemiology at the London School of Hygiene and Tropical Medicine. In 2021, John completed a PhD surrounding the use of high-dimensional propensity scores in UK electronic health records. John’s current research areas include the use of time-conditional propensity scores in prevalent new user designs and applications of causal inference methods (for example, clone-censor weighting approaches) for target trial emulation in non-randomised settings.
Careers Meetings
PSI Training Course: Propensity Scores - practical application in non-randomised studies
Dates: Tues 5th, Thurs 7th, Tues 19th & Thurs 21st September 2023 Time: 13:00-17:00 BST (each day) Location: Online Speakers: Elizabeth Williamson, Clemence Leyrat, and John Tazare (all from LSHTM)
Who is this event intended for? Statisticians looking to understand how to understand and implement propensity scores for use of external data.
What is the benefit of attending? Participants will be able to come away with a practical understanding of when to use, and how to use, propensity score methods.
Course cost
Early Bird PSI Members = £320+VAT Early Bird Non-Members = £430*+VAT *Please note: Early Bird prices expire at 23:30 on Monday 7th August.
Standard PSI Members = £360+VAT Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.
Please see below an outline of the four sessions.
Session
Topic
Session 1
Introduction to propensity scores
Propensity score methods
Practical exercise using R
Session 2
Estimating the propensity score
Propensity scores for multi-valued treatments
Practical exercise using R
Session 3
Handling missing data
High dimensional propensity scores
Practical exercise using R
Session 4
Outcome regression and double robustness
Time-varying scenarios
Practical exercise using R
Speaker details
Speaker
Biography
Elizabeth Williamson LSHTM
Elizabeth Williamson is a Professor of Biostatistics and Health Data Science at the London School of Hygiene and Tropical Medicine. Her research focuses on improving statistical methods for using electronic health record data for research. Elizabeth has a long-term interest in propensity scores, beginning with her PhD in 2003-7 which explored issues around variance estimation, moving on to handling missing data within propensity scores and, more recently, exploring high-dimensional confounding within propensity score analysis.
Clemence Leyrat LSHTM
Clemence Leyrat is an Associate Professor in Medical Statistics at the London School of Hygiene and Tropical Medicine. Since completing her PhD in 2014 on the use of propensity scores in cluster randomised trials, most of her research has focused on causal inference methods for the analysis of observational studies, including trial emulation. More recently, she has been investigating the properties of propensity score weighting in longitudinal settings and in the presence of clustering by hospital.
John Tazare LSHTM
John Tazare is an Assistant Professor in Statistical Pharmacoepidemiology at the London School of Hygiene and Tropical Medicine. In 2021, John completed a PhD surrounding the use of high-dimensional propensity scores in UK electronic health records. John’s current research areas include the use of time-conditional propensity scores in prevalent new user designs and applications of causal inference methods (for example, clone-censor weighting approaches) for target trial emulation in non-randomised settings.
Upcoming Events
PSI Training Course: Effective Leadership – the keys to growing your leadership capabilities
This course will consist of three online half-day workshops. The first will be aimed at building trust, the backbone of leadership and a key to becoming effective. This is key to building a solid foundation.
The second will be on improving communication as a technical leader. This workshop will focus on communication strategies for different stakeholders and will involve tips on effective communication and how to develop the skills of active listening, coaching and what improv can teach us about good communication.
The final workshop will bring these two components together to help leaders become more influential. This will also focus on how to use Steven Covey’s 7-Habits, in particular Habits 4, 5 and 6, which are called the habits of communication.
The workshops will be interactive, allowing you to practice the concepts discussed. There will be plenty of time for questions and discussion. There will also be reflective time where you can think about what you are learning and how you might experiment with it.
PSI Introduction to Industry Training (ITIT) Course - 2026/2027
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This webinar brings together three bitesize complementary sessions to help PSI contributors create conference presentations and posters that communicate clearly and inclusively. Participants will explore how to refine their message, prepare materials effectively, and adopt practical habits that support confident, accessible delivery. A focused, supportive session designed to elevate every contribution.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “Graphics Basics,” will introduce the fundamentals of producing graphics using the ggplot2 package.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
Join our Health Technology Assessment (HTA) European Special Interest Group (ESIG) for a webinar on the strategic role of statisticians in the Joint Clinical Assessment (JCA). The introduction of the JCA marks a new era for evidence generation and market access in Europe. As HTA requirements become more harmonized and methodologically demanding, the role of statisticians has evolved far beyond data analysis. Today, statistical expertise is central to shaping clinical development strategies, designing robust comparative evidence, and ensuring that submissions withstand the scrutiny of EU-level assessors. In this webinar, we explore how statisticians contribute strategically to successful JCA outcomes.
Statisticians in the Age of AI: On Route to Strategic Partnership
A 90-minute webinar featuring two case studies from Bayer and Roche demonstrating how statisticians successfully integrated into AI programs, followed by interactive discussion on strategies for elevating statistical expertise in the AI era.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
GSK - Statistics Director - Vaccines and Infectious Disease
We are seeking an experienced and visionary Statistics Director to join our Team and lead strategic statistical innovation across GSK’s Vaccines and Infectious Disease portfolio.
As a Senior Biostatistician I at ICON, you will play a pivotal role in designing and analyzing clinical trials, interpreting complex medical data, and contributing to the advancement of innovative treatments and therapies.
As a Statistical Scientist at ICON, you will play a pivotal role in designing and analyzing clinical trials, interpreting complex medical data, and contributing to the advancement of innovative treatments and therapies.
We have an exciting opportunity for an Associate Director, Biostatistics to join a passionate team within Advanced Quantitative Sciences – Full Development.
: We have an exciting opportunity for an Associate Director (AD), Statistical Programming, to join a passionate team within Advanced Quantitative Sciences- Development.
Novartis - Senior Principal Statistical Programmer
We have an exciting opportunity for a Senior Principal Statistical Programmer, to join a passionate team within Advanced Quantitative Sciences – Development.
Pierre Fabre - Clinical Development Safety Statistics Expert M/F
We are seeking a highly skilled and proactive Clinical Development Safety Statistics Expert to join our Biometry Department and the Biometry Leadership Team based in Toulouse (31, Oncopole) or Boulogne (92).
Pierre Fabre - Lead Statistician – Real World Evidence -CDI- M/F
Pierre Fabre Laboratories are hiring a highly skilled and experienced Lead Statistician – Real World Evidence (RWE) to join the Biometry Department, part of the Data Science & Biometry Department, based in Toulouse (Oncopôle) or Boulogne.
Pierre Fabre - Lead Statistician- Clinical Trials M/F
We are seeking a highly skilled and experienced Lead Statistician in Clinical Trials to join our Biometry Department based in Toulouse (31, Oncopole) or Boulogne (92).
We are looking for Senior Statistical Programmers in the UK to join Veramed, where you'll deliver high-impact programming solutions in an FSP-style capacity, while advancing your career in a supportive, growth-driven environment.
