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 Mentoring 2025
Date: Ongoing 6 month cycle beginning late April/early May 2024
Are you a member of PSI looking to further your career or help develop others - why not sign up to the PSI Mentoring scheme? You can expand your network, improve your leadership skills and learn from more senior colleagues in the industry.
PSI Training Course: Mixed Models and Repeated Measures
This course is presented through lectures and practical sessions using SAS code. It is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models.
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.
This is an interactive online training workshop providing an in-depth review of the estimand framework as laid out by ICH E9(R1) addendum with inputs from estimand experts, case studies, quizzes and opportunity for discussions. You will develop an estimand in a therapeutic area of interest to your company. In an online break-out room, you will join a series of team discussions to implement the estimand framework in a case study, aligning estimands, design, conduct, analysis, (assumptions + sensitivity analyses) to the clinical objective and therapeutic setting.
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.