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 Webinar: Development of Gene Therapies: Strategic, Scientific, Regulatory and Access Considerations
This webinar will cover the history of cell/gene therapy, major regulatory advances, the role of quantitative scientists in drug development of these novel therapeutics, and discuss opportunities for innovation and product advancement.
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.
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 Introduction to Industry Training (ITIT) Course - 2024/2025
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.
PSI Training Course: Regulatory Guidelines for Statisticians
This 2-day course is designed to provide a comprehensive understanding of the regulatory guidelines affecting statisticians in the pharmaceutical industry, including the latest updates in the field. The course will cover key International Council for Harmonisation (ICH) guidelines and other key regional regulatory agency documents.
In this event, we’ll start with a general introduction to hierarchical composite endpoints and an overview of common analysis methods including win ratio, win odds, and net benefit. Then, the practical considerations will be illustrated through case studies from clinical trials in heart failure and chronic kidney disease. We conclude with a discussion and a Q&A.
Joint PSI/EFSPI Pre-Clinical SIG Webinar: Virtual Control Groups in Toxicity Studies
Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
Statisticians in the Pharmaceutical Industry Executive Office: c/o MCI UK Ltd | Unit 24/22 South | Building 4000 | Langstone Park| Langstone Road | Havant | PO9 1SA | UK