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 Introduction to Industry Training (ITIT) Course - 2025/2026
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.
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.
PSI Book Club Webinar: Atomic Habits - The Science of Getting Your Act Together
The book club’s usual focus is to read and discuss professional development books. In this short format event you can more easily develop you career without the commitment of reading the whole book - simply listen to the 1-hour long podcast before joining the interactive session on 21 May.
PSI Webinar: Methods and tools integrating clinical trial evidence with historical or real-world data, Bayesian borrowing, and causal inference
This webinar is organised by the RWD SIG and the Historical Data SIG. We will review recent methods, applications, and tools of integrating subject-level-data from clinical trial with external data using Bayesian methods and/or causal inference methods.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
PSI Webinar: Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance
This will be a 45 minute webinar which will explain the topic presented in the published paper, ‘Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance’. There will be 15 minutes for a panel Q&A with some of the authors following the presentation.
PSI Webinar: Methodology and first results of the iRISE (improving Reproducibility In SciencE) consortium
This 1-hour webinar will be an opportunity to hear about the methodology and first results of the iRISE consortium. iRISE is working towards a better understanding of reproducibility and the interventions that work to improve it. At the end of the presentation there will also be the opportunity to ask questions.
One-day Event: Change Management for Moving to R/Open-Source
This one-day event focuses on the comprehensive management of transitioning to R/Open-Source, addressing the challenges and providing actionable insights. Attendees will participate in sessions covering essential topics such as training best practices, creating strategic plans, making the case to senior management, and managing both statistical and programming aspects of the transition.
PSI Book Club - The Art of Explanation: How to Communicate with Clarity and Confidence
Develop your non-technical skills by reading The Art of Explanation by Ros Atkins and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply skills from the book in-between sessions.
This course is aimed at biostatisticians with no or some pediatric drug development experience who are interested to further their understanding. We will give you an introduction to the pediatric drug development landscape. This will include identifying the key regulations and processes governing pediatric development, a discussion on the needs and challenges when conducting pediatric research and a focus on the ways to overcome these challenges from a statistical perspective.
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 is an exciting, new opportunity for an experienced Statistician looking to take the next step in their career. Offered as a remote or hybrid position aligned with our site in Harrogate, North Yorkshire.
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