Dates: Mon.9th, Tues.10th, Thurs.12th & Fri.13th October 2023
Time: 09:00-12:00 BST (each day)
Location: Online
Speakers: Jonathan Bartlett and James Carpenter (LSHTM)
Who is this event intended for? This course is intended for clinical trial statisticians who are interested in learning more about statistical methods for handling missing data in clinical trial analyses.
What is the benefit of attending? By the end of the course participants will be familiar with the key concepts (e.g. missing at random) and statistical methods (e.g. multiple imputation) relevant when estimating treatment effects in trials where some data are missing.
Early Bird PSI Members = £320+VAT
Early Bird Non-Members = £430*+VAT
*Please note: Early Bird prices expire at 17:00 on Friday 8th September.
Standard PSI Members = £360+VAT
Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
To book your place, please click here.
This course will introduce participants to the key concepts and methods relevant for analysing clinical trials when some data are missing. We will describe missing data assumptions and Rubin’s framework for classifying them, based on missing completely at random, missing at random (MAR), and missing not at random, and what these imply when missingness is due to dropout or the occurrence of intercurrent events. We will describe the use of mixed models and multiple imputation to handle missingness under MAR, and finally discuss methods for conducting missing data sensitivity analyses, including reference based imputation methods.
The course will cover:
Please note: Each of the above will be presented in a one hour lecture, followed by a two hour interactive computer practical. Computer practicals will be taught using R and so having R or R Studio installed on your personal laptop/computer is required to participate in the practicals.
|
Speaker |
Biography |
|
|
Jonathan Bartlett is a Professor in Medical Statistics at the London School of Hygiene & Tropical Medicine. His research interests are focused around missing data and causal inference methods, and more recently, how these can be applied to target different estimands in clinical trials. He has held previous positions at AstraZeneca and the University of Bath, and maintains a blog thestatsgeek.com |
|
|
James Carpenter is Professor of Medical Statistics at the London School of Hygiene & Tropical Medicine, and MRC Investigator in trials methodology at the MRC CTU at UCL. His principal research interests are coping with missing data in clinical trials and complex hierarchical models, estimands, sensitivity analysis, meta-analysis and novel trial designs. |
Dates: Mon.9th, Tues.10th, Thurs.12th & Fri.13th October 2023
Time: 09:00-12:00 BST (each day)
Location: Online
Speakers: Jonathan Bartlett and James Carpenter (LSHTM)
Who is this event intended for? This course is intended for clinical trial statisticians who are interested in learning more about statistical methods for handling missing data in clinical trial analyses.
What is the benefit of attending? By the end of the course participants will be familiar with the key concepts (e.g. missing at random) and statistical methods (e.g. multiple imputation) relevant when estimating treatment effects in trials where some data are missing.
Early Bird PSI Members = £320+VAT
Early Bird Non-Members = £430*+VAT
*Please note: Early Bird prices expire at 17:00 on Friday 8th September.
Standard PSI Members = £360+VAT
Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
To book your place, please click here.
This course will introduce participants to the key concepts and methods relevant for analysing clinical trials when some data are missing. We will describe missing data assumptions and Rubin’s framework for classifying them, based on missing completely at random, missing at random (MAR), and missing not at random, and what these imply when missingness is due to dropout or the occurrence of intercurrent events. We will describe the use of mixed models and multiple imputation to handle missingness under MAR, and finally discuss methods for conducting missing data sensitivity analyses, including reference based imputation methods.
The course will cover:
Please note: Each of the above will be presented in a one hour lecture, followed by a two hour interactive computer practical. Computer practicals will be taught using R and so having R or R Studio installed on your personal laptop/computer is required to participate in the practicals.
|
Speaker |
Biography |
|
|
Jonathan Bartlett is a Professor in Medical Statistics at the London School of Hygiene & Tropical Medicine. His research interests are focused around missing data and causal inference methods, and more recently, how these can be applied to target different estimands in clinical trials. He has held previous positions at AstraZeneca and the University of Bath, and maintains a blog thestatsgeek.com |
|
|
James Carpenter is Professor of Medical Statistics at the London School of Hygiene & Tropical Medicine, and MRC Investigator in trials methodology at the MRC CTU at UCL. His principal research interests are coping with missing data in clinical trials and complex hierarchical models, estimands, sensitivity analysis, meta-analysis and novel trial designs. |
Dates: Mon.9th, Tues.10th, Thurs.12th & Fri.13th October 2023
Time: 09:00-12:00 BST (each day)
Location: Online
Speakers: Jonathan Bartlett and James Carpenter (LSHTM)
Who is this event intended for? This course is intended for clinical trial statisticians who are interested in learning more about statistical methods for handling missing data in clinical trial analyses.
What is the benefit of attending? By the end of the course participants will be familiar with the key concepts (e.g. missing at random) and statistical methods (e.g. multiple imputation) relevant when estimating treatment effects in trials where some data are missing.
Early Bird PSI Members = £320+VAT
Early Bird Non-Members = £430*+VAT
*Please note: Early Bird prices expire at 17:00 on Friday 8th September.
Standard PSI Members = £360+VAT
Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
To book your place, please click here.
This course will introduce participants to the key concepts and methods relevant for analysing clinical trials when some data are missing. We will describe missing data assumptions and Rubin’s framework for classifying them, based on missing completely at random, missing at random (MAR), and missing not at random, and what these imply when missingness is due to dropout or the occurrence of intercurrent events. We will describe the use of mixed models and multiple imputation to handle missingness under MAR, and finally discuss methods for conducting missing data sensitivity analyses, including reference based imputation methods.
The course will cover:
Please note: Each of the above will be presented in a one hour lecture, followed by a two hour interactive computer practical. Computer practicals will be taught using R and so having R or R Studio installed on your personal laptop/computer is required to participate in the practicals.
|
Speaker |
Biography |
|
|
Jonathan Bartlett is a Professor in Medical Statistics at the London School of Hygiene & Tropical Medicine. His research interests are focused around missing data and causal inference methods, and more recently, how these can be applied to target different estimands in clinical trials. He has held previous positions at AstraZeneca and the University of Bath, and maintains a blog thestatsgeek.com |
|
|
James Carpenter is Professor of Medical Statistics at the London School of Hygiene & Tropical Medicine, and MRC Investigator in trials methodology at the MRC CTU at UCL. His principal research interests are coping with missing data in clinical trials and complex hierarchical models, estimands, sensitivity analysis, meta-analysis and novel trial designs. |
Dates: Mon.9th, Tues.10th, Thurs.12th & Fri.13th October 2023
Time: 09:00-12:00 BST (each day)
Location: Online
Speakers: Jonathan Bartlett and James Carpenter (LSHTM)
Who is this event intended for? This course is intended for clinical trial statisticians who are interested in learning more about statistical methods for handling missing data in clinical trial analyses.
What is the benefit of attending? By the end of the course participants will be familiar with the key concepts (e.g. missing at random) and statistical methods (e.g. multiple imputation) relevant when estimating treatment effects in trials where some data are missing.
Early Bird PSI Members = £320+VAT
Early Bird Non-Members = £430*+VAT
*Please note: Early Bird prices expire at 17:00 on Friday 8th September.
Standard PSI Members = £360+VAT
Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
To book your place, please click here.
This course will introduce participants to the key concepts and methods relevant for analysing clinical trials when some data are missing. We will describe missing data assumptions and Rubin’s framework for classifying them, based on missing completely at random, missing at random (MAR), and missing not at random, and what these imply when missingness is due to dropout or the occurrence of intercurrent events. We will describe the use of mixed models and multiple imputation to handle missingness under MAR, and finally discuss methods for conducting missing data sensitivity analyses, including reference based imputation methods.
The course will cover:
Please note: Each of the above will be presented in a one hour lecture, followed by a two hour interactive computer practical. Computer practicals will be taught using R and so having R or R Studio installed on your personal laptop/computer is required to participate in the practicals.
|
Speaker |
Biography |
|
|
Jonathan Bartlett is a Professor in Medical Statistics at the London School of Hygiene & Tropical Medicine. His research interests are focused around missing data and causal inference methods, and more recently, how these can be applied to target different estimands in clinical trials. He has held previous positions at AstraZeneca and the University of Bath, and maintains a blog thestatsgeek.com |
|
|
James Carpenter is Professor of Medical Statistics at the London School of Hygiene & Tropical Medicine, and MRC Investigator in trials methodology at the MRC CTU at UCL. His principal research interests are coping with missing data in clinical trials and complex hierarchical models, estimands, sensitivity analysis, meta-analysis and novel trial designs. |
Dates: Mon.9th, Tues.10th, Thurs.12th & Fri.13th October 2023
Time: 09:00-12:00 BST (each day)
Location: Online
Speakers: Jonathan Bartlett and James Carpenter (LSHTM)
Who is this event intended for? This course is intended for clinical trial statisticians who are interested in learning more about statistical methods for handling missing data in clinical trial analyses.
What is the benefit of attending? By the end of the course participants will be familiar with the key concepts (e.g. missing at random) and statistical methods (e.g. multiple imputation) relevant when estimating treatment effects in trials where some data are missing.
Early Bird PSI Members = £320+VAT
Early Bird Non-Members = £430*+VAT
*Please note: Early Bird prices expire at 17:00 on Friday 8th September.
Standard PSI Members = £360+VAT
Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
To book your place, please click here.
This course will introduce participants to the key concepts and methods relevant for analysing clinical trials when some data are missing. We will describe missing data assumptions and Rubin’s framework for classifying them, based on missing completely at random, missing at random (MAR), and missing not at random, and what these imply when missingness is due to dropout or the occurrence of intercurrent events. We will describe the use of mixed models and multiple imputation to handle missingness under MAR, and finally discuss methods for conducting missing data sensitivity analyses, including reference based imputation methods.
The course will cover:
Please note: Each of the above will be presented in a one hour lecture, followed by a two hour interactive computer practical. Computer practicals will be taught using R and so having R or R Studio installed on your personal laptop/computer is required to participate in the practicals.
|
Speaker |
Biography |
|
|
Jonathan Bartlett is a Professor in Medical Statistics at the London School of Hygiene & Tropical Medicine. His research interests are focused around missing data and causal inference methods, and more recently, how these can be applied to target different estimands in clinical trials. He has held previous positions at AstraZeneca and the University of Bath, and maintains a blog thestatsgeek.com |
|
|
James Carpenter is Professor of Medical Statistics at the London School of Hygiene & Tropical Medicine, and MRC Investigator in trials methodology at the MRC CTU at UCL. His principal research interests are coping with missing data in clinical trials and complex hierarchical models, estimands, sensitivity analysis, meta-analysis and novel trial designs. |
Dates: Mon.9th, Tues.10th, Thurs.12th & Fri.13th October 2023
Time: 09:00-12:00 BST (each day)
Location: Online
Speakers: Jonathan Bartlett and James Carpenter (LSHTM)
Who is this event intended for? This course is intended for clinical trial statisticians who are interested in learning more about statistical methods for handling missing data in clinical trial analyses.
What is the benefit of attending? By the end of the course participants will be familiar with the key concepts (e.g. missing at random) and statistical methods (e.g. multiple imputation) relevant when estimating treatment effects in trials where some data are missing.
Early Bird PSI Members = £320+VAT
Early Bird Non-Members = £430*+VAT
*Please note: Early Bird prices expire at 17:00 on Friday 8th September.
Standard PSI Members = £360+VAT
Standard Non-Members = £470*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2024.
To book your place, please click here.
This course will introduce participants to the key concepts and methods relevant for analysing clinical trials when some data are missing. We will describe missing data assumptions and Rubin’s framework for classifying them, based on missing completely at random, missing at random (MAR), and missing not at random, and what these imply when missingness is due to dropout or the occurrence of intercurrent events. We will describe the use of mixed models and multiple imputation to handle missingness under MAR, and finally discuss methods for conducting missing data sensitivity analyses, including reference based imputation methods.
The course will cover:
Please note: Each of the above will be presented in a one hour lecture, followed by a two hour interactive computer practical. Computer practicals will be taught using R and so having R or R Studio installed on your personal laptop/computer is required to participate in the practicals.
|
Speaker |
Biography |
|
|
Jonathan Bartlett is a Professor in Medical Statistics at the London School of Hygiene & Tropical Medicine. His research interests are focused around missing data and causal inference methods, and more recently, how these can be applied to target different estimands in clinical trials. He has held previous positions at AstraZeneca and the University of Bath, and maintains a blog thestatsgeek.com |
|
|
James Carpenter is Professor of Medical Statistics at the London School of Hygiene & Tropical Medicine, and MRC Investigator in trials methodology at the MRC CTU at UCL. His principal research interests are coping with missing data in clinical trials and complex hierarchical models, estimands, sensitivity analysis, meta-analysis and novel trial designs. |
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.
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.
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.
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.
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.
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.
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.
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.
The program will feature insightful sessions led by distinguished invited speakers, alongside a poster session showcasing the latest advancements in the field. Further details will be provided.
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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