A PSI Training Course on Missing Data
Presented by Mike Kenward (GlaxoSmithKline Professor of Biostatistics) and James Roger (Honorary Professor of Biostatistics) Department of Medical Statistics
London School of Hygiene and Tropical Medicine
There has been much recent activity concerning the problem of handling missing data in clinical trials. In 2010, a new set of guidelines was produced by the European regulators, and a major report was produced by the US National Research Council Panel on Handling Missing Data in Clinical Trials, at the behest of the FDA. The current course has two main threads that reflect this activity. In the first, the conceptual issues surrounding missing data in clinical trials are explored, reflecting the debate that has been taking place over the last ten years. In the second, the relevant statistical methodology is introduced and developed In particular there will be an introduction to the roles of the so-called selection and pattern-mixture frameworks, and to multiple imputation. For completeness and for purposes of comparison there will also be a brief treatment of other approaches, including ad hoc methods such as Last Observation Carried Forward (LOCF) and more principled approaches like inverse probability weighting. The two main threads will be brought together in a thorough exploration of sensitivity analyses that can be applied in this setting. Methodology will be illustrated with examples from real longitudinal clinical trials, using SAS procedures and macros. The course will consist of lectures. There will not be any computer exercises.
The following key topics will be addressed:
• The documents from US and European regulators.
• Definitions: missing value mechanisms (MCAR, MAR, MNAR), ignorability, estimands (de jure, de facto); other jargon: intention to treat, per protocol, efficacy, effectiveness.
• The distinction between missingness as a nuisance and as part of the outcome.
• Ad hoc methods: completers analyses, last observation carried forward, simple imputation, worst case analyses.
• Model based analyses under MAR for continuous and categorical data.
• Sensitivity analyses: selection and pattern-mixture models, multiple imputation, controlled imputation
Use of Computers:
There will not be any workshops where course participants do their own computing, but there will be extensive examples throughout the course, and example code will be supplied showing how to implement the preferred methods. All such code is either in the public domain or is made freely available to the participants for them to copy and use within their own organisations.
About the presenters:
Mike Kenward, GSK Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
Mike Kenward has worked in Iceland, Finland and the UK, in both research institutes and universities. He has a broad interest in modelling in biostatistics, with particular experience in longitudinal data and cross-over trials, as well as the general problem of missing data. He has co-authored three textbooks, The Design and Analysis of Cross-Over Trials (with Byron Jones), Missing Data in Clinical Studies (with Geert Molenberghs) and Multiple Imputation and its Application (with James Carpenter). He has been a consultant, principally for the pharmaceutical industry, for over 25 years, and has given many short courses throughout the world on various areas of biostatistics, especially missing data.
James Roger, Honorary Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
James Roger has a long career as university lecturer and statistician within with pharmaceutical industry including periods with J&J and GSK. Collaboration with Mike Kenward has spanned most of that career. James’ interest in missing data stemmed from shared research on linear mixed models and small sample approximations. Recent collaboration has centred on methods that address alternative estimands to those associated with classic MAR. Collaboration with GSK has allowed the development of an implementation of these approaches within SAS using multiple imputation.
Course runs from: 10:00 – 17:30 (registration from 9:30) on Day 1 and 09:00 – 16:00 on Day 2.
Registration
Please register online at www.psiweb.org and click on Events; payment now available online.
Registration costs (includes lunch and refreshments)
Registration before 15 April 2014
PSI Members: £495 plus vat
Non-members: £540 plus vat
Registration on or after 15 April 2014
PSI Members: £595 plus vat
Non-members: £640 plus vat
Accommodation can’t be guaranteed after the early bird deadline
PSI aims to be fully inclusive and endeavours to accommodate delegates with disabilities wherever possible. Please help us to help you by letting us know if you require additional facilities or have any special requirements. Please contact us on +44 (0)845 1800 349 or at PSI@mci-group.com for further information.
Contact: Emma Lovett, Tel: +44 (0)845 1800 349
Email: PSI@mci-group.com
A PSI Training Course on Missing Data
Presented by Mike Kenward (GlaxoSmithKline Professor of Biostatistics) and James Roger (Honorary Professor of Biostatistics) Department of Medical Statistics
London School of Hygiene and Tropical Medicine
There has been much recent activity concerning the problem of handling missing data in clinical trials. In 2010, a new set of guidelines was produced by the European regulators, and a major report was produced by the US National Research Council Panel on Handling Missing Data in Clinical Trials, at the behest of the FDA. The current course has two main threads that reflect this activity. In the first, the conceptual issues surrounding missing data in clinical trials are explored, reflecting the debate that has been taking place over the last ten years. In the second, the relevant statistical methodology is introduced and developed In particular there will be an introduction to the roles of the so-called selection and pattern-mixture frameworks, and to multiple imputation. For completeness and for purposes of comparison there will also be a brief treatment of other approaches, including ad hoc methods such as Last Observation Carried Forward (LOCF) and more principled approaches like inverse probability weighting. The two main threads will be brought together in a thorough exploration of sensitivity analyses that can be applied in this setting. Methodology will be illustrated with examples from real longitudinal clinical trials, using SAS procedures and macros. The course will consist of lectures. There will not be any computer exercises.
The following key topics will be addressed:
• The documents from US and European regulators.
• Definitions: missing value mechanisms (MCAR, MAR, MNAR), ignorability, estimands (de jure, de facto); other jargon: intention to treat, per protocol, efficacy, effectiveness.
• The distinction between missingness as a nuisance and as part of the outcome.
• Ad hoc methods: completers analyses, last observation carried forward, simple imputation, worst case analyses.
• Model based analyses under MAR for continuous and categorical data.
• Sensitivity analyses: selection and pattern-mixture models, multiple imputation, controlled imputation
Use of Computers:
There will not be any workshops where course participants do their own computing, but there will be extensive examples throughout the course, and example code will be supplied showing how to implement the preferred methods. All such code is either in the public domain or is made freely available to the participants for them to copy and use within their own organisations.
About the presenters:
Mike Kenward, GSK Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
Mike Kenward has worked in Iceland, Finland and the UK, in both research institutes and universities. He has a broad interest in modelling in biostatistics, with particular experience in longitudinal data and cross-over trials, as well as the general problem of missing data. He has co-authored three textbooks, The Design and Analysis of Cross-Over Trials (with Byron Jones), Missing Data in Clinical Studies (with Geert Molenberghs) and Multiple Imputation and its Application (with James Carpenter). He has been a consultant, principally for the pharmaceutical industry, for over 25 years, and has given many short courses throughout the world on various areas of biostatistics, especially missing data.
James Roger, Honorary Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
James Roger has a long career as university lecturer and statistician within with pharmaceutical industry including periods with J&J and GSK. Collaboration with Mike Kenward has spanned most of that career. James’ interest in missing data stemmed from shared research on linear mixed models and small sample approximations. Recent collaboration has centred on methods that address alternative estimands to those associated with classic MAR. Collaboration with GSK has allowed the development of an implementation of these approaches within SAS using multiple imputation.
Course runs from: 10:00 – 17:30 (registration from 9:30) on Day 1 and 09:00 – 16:00 on Day 2.
Registration
Please register online at www.psiweb.org and click on Events; payment now available online.
Registration costs (includes lunch and refreshments)
Registration before 15 April 2014
PSI Members: £495 plus vat
Non-members: £540 plus vat
Registration on or after 15 April 2014
PSI Members: £595 plus vat
Non-members: £640 plus vat
Accommodation can’t be guaranteed after the early bird deadline
PSI aims to be fully inclusive and endeavours to accommodate delegates with disabilities wherever possible. Please help us to help you by letting us know if you require additional facilities or have any special requirements. Please contact us on +44 (0)845 1800 349 or at PSI@mci-group.com for further information.
Contact: Emma Lovett, Tel: +44 (0)845 1800 349
Email: PSI@mci-group.com
A PSI Training Course on Missing Data
Presented by Mike Kenward (GlaxoSmithKline Professor of Biostatistics) and James Roger (Honorary Professor of Biostatistics) Department of Medical Statistics
London School of Hygiene and Tropical Medicine
There has been much recent activity concerning the problem of handling missing data in clinical trials. In 2010, a new set of guidelines was produced by the European regulators, and a major report was produced by the US National Research Council Panel on Handling Missing Data in Clinical Trials, at the behest of the FDA. The current course has two main threads that reflect this activity. In the first, the conceptual issues surrounding missing data in clinical trials are explored, reflecting the debate that has been taking place over the last ten years. In the second, the relevant statistical methodology is introduced and developed In particular there will be an introduction to the roles of the so-called selection and pattern-mixture frameworks, and to multiple imputation. For completeness and for purposes of comparison there will also be a brief treatment of other approaches, including ad hoc methods such as Last Observation Carried Forward (LOCF) and more principled approaches like inverse probability weighting. The two main threads will be brought together in a thorough exploration of sensitivity analyses that can be applied in this setting. Methodology will be illustrated with examples from real longitudinal clinical trials, using SAS procedures and macros. The course will consist of lectures. There will not be any computer exercises.
The following key topics will be addressed:
• The documents from US and European regulators.
• Definitions: missing value mechanisms (MCAR, MAR, MNAR), ignorability, estimands (de jure, de facto); other jargon: intention to treat, per protocol, efficacy, effectiveness.
• The distinction between missingness as a nuisance and as part of the outcome.
• Ad hoc methods: completers analyses, last observation carried forward, simple imputation, worst case analyses.
• Model based analyses under MAR for continuous and categorical data.
• Sensitivity analyses: selection and pattern-mixture models, multiple imputation, controlled imputation
Use of Computers:
There will not be any workshops where course participants do their own computing, but there will be extensive examples throughout the course, and example code will be supplied showing how to implement the preferred methods. All such code is either in the public domain or is made freely available to the participants for them to copy and use within their own organisations.
About the presenters:
Mike Kenward, GSK Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
Mike Kenward has worked in Iceland, Finland and the UK, in both research institutes and universities. He has a broad interest in modelling in biostatistics, with particular experience in longitudinal data and cross-over trials, as well as the general problem of missing data. He has co-authored three textbooks, The Design and Analysis of Cross-Over Trials (with Byron Jones), Missing Data in Clinical Studies (with Geert Molenberghs) and Multiple Imputation and its Application (with James Carpenter). He has been a consultant, principally for the pharmaceutical industry, for over 25 years, and has given many short courses throughout the world on various areas of biostatistics, especially missing data.
James Roger, Honorary Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
James Roger has a long career as university lecturer and statistician within with pharmaceutical industry including periods with J&J and GSK. Collaboration with Mike Kenward has spanned most of that career. James’ interest in missing data stemmed from shared research on linear mixed models and small sample approximations. Recent collaboration has centred on methods that address alternative estimands to those associated with classic MAR. Collaboration with GSK has allowed the development of an implementation of these approaches within SAS using multiple imputation.
Course runs from: 10:00 – 17:30 (registration from 9:30) on Day 1 and 09:00 – 16:00 on Day 2.
Registration
Please register online at www.psiweb.org and click on Events; payment now available online.
Registration costs (includes lunch and refreshments)
Registration before 15 April 2014
PSI Members: £495 plus vat
Non-members: £540 plus vat
Registration on or after 15 April 2014
PSI Members: £595 plus vat
Non-members: £640 plus vat
Accommodation can’t be guaranteed after the early bird deadline
PSI aims to be fully inclusive and endeavours to accommodate delegates with disabilities wherever possible. Please help us to help you by letting us know if you require additional facilities or have any special requirements. Please contact us on +44 (0)845 1800 349 or at PSI@mci-group.com for further information.
Contact: Emma Lovett, Tel: +44 (0)845 1800 349
Email: PSI@mci-group.com
A PSI Training Course on Missing Data
Presented by Mike Kenward (GlaxoSmithKline Professor of Biostatistics) and James Roger (Honorary Professor of Biostatistics) Department of Medical Statistics
London School of Hygiene and Tropical Medicine
There has been much recent activity concerning the problem of handling missing data in clinical trials. In 2010, a new set of guidelines was produced by the European regulators, and a major report was produced by the US National Research Council Panel on Handling Missing Data in Clinical Trials, at the behest of the FDA. The current course has two main threads that reflect this activity. In the first, the conceptual issues surrounding missing data in clinical trials are explored, reflecting the debate that has been taking place over the last ten years. In the second, the relevant statistical methodology is introduced and developed In particular there will be an introduction to the roles of the so-called selection and pattern-mixture frameworks, and to multiple imputation. For completeness and for purposes of comparison there will also be a brief treatment of other approaches, including ad hoc methods such as Last Observation Carried Forward (LOCF) and more principled approaches like inverse probability weighting. The two main threads will be brought together in a thorough exploration of sensitivity analyses that can be applied in this setting. Methodology will be illustrated with examples from real longitudinal clinical trials, using SAS procedures and macros. The course will consist of lectures. There will not be any computer exercises.
The following key topics will be addressed:
• The documents from US and European regulators.
• Definitions: missing value mechanisms (MCAR, MAR, MNAR), ignorability, estimands (de jure, de facto); other jargon: intention to treat, per protocol, efficacy, effectiveness.
• The distinction between missingness as a nuisance and as part of the outcome.
• Ad hoc methods: completers analyses, last observation carried forward, simple imputation, worst case analyses.
• Model based analyses under MAR for continuous and categorical data.
• Sensitivity analyses: selection and pattern-mixture models, multiple imputation, controlled imputation
Use of Computers:
There will not be any workshops where course participants do their own computing, but there will be extensive examples throughout the course, and example code will be supplied showing how to implement the preferred methods. All such code is either in the public domain or is made freely available to the participants for them to copy and use within their own organisations.
About the presenters:
Mike Kenward, GSK Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
Mike Kenward has worked in Iceland, Finland and the UK, in both research institutes and universities. He has a broad interest in modelling in biostatistics, with particular experience in longitudinal data and cross-over trials, as well as the general problem of missing data. He has co-authored three textbooks, The Design and Analysis of Cross-Over Trials (with Byron Jones), Missing Data in Clinical Studies (with Geert Molenberghs) and Multiple Imputation and its Application (with James Carpenter). He has been a consultant, principally for the pharmaceutical industry, for over 25 years, and has given many short courses throughout the world on various areas of biostatistics, especially missing data.
James Roger, Honorary Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
James Roger has a long career as university lecturer and statistician within with pharmaceutical industry including periods with J&J and GSK. Collaboration with Mike Kenward has spanned most of that career. James’ interest in missing data stemmed from shared research on linear mixed models and small sample approximations. Recent collaboration has centred on methods that address alternative estimands to those associated with classic MAR. Collaboration with GSK has allowed the development of an implementation of these approaches within SAS using multiple imputation.
Course runs from: 10:00 – 17:30 (registration from 9:30) on Day 1 and 09:00 – 16:00 on Day 2.
Registration
Please register online at www.psiweb.org and click on Events; payment now available online.
Registration costs (includes lunch and refreshments)
Registration before 15 April 2014
PSI Members: £495 plus vat
Non-members: £540 plus vat
Registration on or after 15 April 2014
PSI Members: £595 plus vat
Non-members: £640 plus vat
Accommodation can’t be guaranteed after the early bird deadline
PSI aims to be fully inclusive and endeavours to accommodate delegates with disabilities wherever possible. Please help us to help you by letting us know if you require additional facilities or have any special requirements. Please contact us on +44 (0)845 1800 349 or at PSI@mci-group.com for further information.
Contact: Emma Lovett, Tel: +44 (0)845 1800 349
Email: PSI@mci-group.com
A PSI Training Course on Missing Data
Presented by Mike Kenward (GlaxoSmithKline Professor of Biostatistics) and James Roger (Honorary Professor of Biostatistics) Department of Medical Statistics
London School of Hygiene and Tropical Medicine
There has been much recent activity concerning the problem of handling missing data in clinical trials. In 2010, a new set of guidelines was produced by the European regulators, and a major report was produced by the US National Research Council Panel on Handling Missing Data in Clinical Trials, at the behest of the FDA. The current course has two main threads that reflect this activity. In the first, the conceptual issues surrounding missing data in clinical trials are explored, reflecting the debate that has been taking place over the last ten years. In the second, the relevant statistical methodology is introduced and developed In particular there will be an introduction to the roles of the so-called selection and pattern-mixture frameworks, and to multiple imputation. For completeness and for purposes of comparison there will also be a brief treatment of other approaches, including ad hoc methods such as Last Observation Carried Forward (LOCF) and more principled approaches like inverse probability weighting. The two main threads will be brought together in a thorough exploration of sensitivity analyses that can be applied in this setting. Methodology will be illustrated with examples from real longitudinal clinical trials, using SAS procedures and macros. The course will consist of lectures. There will not be any computer exercises.
The following key topics will be addressed:
• The documents from US and European regulators.
• Definitions: missing value mechanisms (MCAR, MAR, MNAR), ignorability, estimands (de jure, de facto); other jargon: intention to treat, per protocol, efficacy, effectiveness.
• The distinction between missingness as a nuisance and as part of the outcome.
• Ad hoc methods: completers analyses, last observation carried forward, simple imputation, worst case analyses.
• Model based analyses under MAR for continuous and categorical data.
• Sensitivity analyses: selection and pattern-mixture models, multiple imputation, controlled imputation
Use of Computers:
There will not be any workshops where course participants do their own computing, but there will be extensive examples throughout the course, and example code will be supplied showing how to implement the preferred methods. All such code is either in the public domain or is made freely available to the participants for them to copy and use within their own organisations.
About the presenters:
Mike Kenward, GSK Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
Mike Kenward has worked in Iceland, Finland and the UK, in both research institutes and universities. He has a broad interest in modelling in biostatistics, with particular experience in longitudinal data and cross-over trials, as well as the general problem of missing data. He has co-authored three textbooks, The Design and Analysis of Cross-Over Trials (with Byron Jones), Missing Data in Clinical Studies (with Geert Molenberghs) and Multiple Imputation and its Application (with James Carpenter). He has been a consultant, principally for the pharmaceutical industry, for over 25 years, and has given many short courses throughout the world on various areas of biostatistics, especially missing data.
James Roger, Honorary Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
James Roger has a long career as university lecturer and statistician within with pharmaceutical industry including periods with J&J and GSK. Collaboration with Mike Kenward has spanned most of that career. James’ interest in missing data stemmed from shared research on linear mixed models and small sample approximations. Recent collaboration has centred on methods that address alternative estimands to those associated with classic MAR. Collaboration with GSK has allowed the development of an implementation of these approaches within SAS using multiple imputation.
Course runs from: 10:00 – 17:30 (registration from 9:30) on Day 1 and 09:00 – 16:00 on Day 2.
Registration
Please register online at www.psiweb.org and click on Events; payment now available online.
Registration costs (includes lunch and refreshments)
Registration before 15 April 2014
PSI Members: £495 plus vat
Non-members: £540 plus vat
Registration on or after 15 April 2014
PSI Members: £595 plus vat
Non-members: £640 plus vat
Accommodation can’t be guaranteed after the early bird deadline
PSI aims to be fully inclusive and endeavours to accommodate delegates with disabilities wherever possible. Please help us to help you by letting us know if you require additional facilities or have any special requirements. Please contact us on +44 (0)845 1800 349 or at PSI@mci-group.com for further information.
Contact: Emma Lovett, Tel: +44 (0)845 1800 349
Email: PSI@mci-group.com
A PSI Training Course on Missing Data
Presented by Mike Kenward (GlaxoSmithKline Professor of Biostatistics) and James Roger (Honorary Professor of Biostatistics) Department of Medical Statistics
London School of Hygiene and Tropical Medicine
There has been much recent activity concerning the problem of handling missing data in clinical trials. In 2010, a new set of guidelines was produced by the European regulators, and a major report was produced by the US National Research Council Panel on Handling Missing Data in Clinical Trials, at the behest of the FDA. The current course has two main threads that reflect this activity. In the first, the conceptual issues surrounding missing data in clinical trials are explored, reflecting the debate that has been taking place over the last ten years. In the second, the relevant statistical methodology is introduced and developed In particular there will be an introduction to the roles of the so-called selection and pattern-mixture frameworks, and to multiple imputation. For completeness and for purposes of comparison there will also be a brief treatment of other approaches, including ad hoc methods such as Last Observation Carried Forward (LOCF) and more principled approaches like inverse probability weighting. The two main threads will be brought together in a thorough exploration of sensitivity analyses that can be applied in this setting. Methodology will be illustrated with examples from real longitudinal clinical trials, using SAS procedures and macros. The course will consist of lectures. There will not be any computer exercises.
The following key topics will be addressed:
• The documents from US and European regulators.
• Definitions: missing value mechanisms (MCAR, MAR, MNAR), ignorability, estimands (de jure, de facto); other jargon: intention to treat, per protocol, efficacy, effectiveness.
• The distinction between missingness as a nuisance and as part of the outcome.
• Ad hoc methods: completers analyses, last observation carried forward, simple imputation, worst case analyses.
• Model based analyses under MAR for continuous and categorical data.
• Sensitivity analyses: selection and pattern-mixture models, multiple imputation, controlled imputation
Use of Computers:
There will not be any workshops where course participants do their own computing, but there will be extensive examples throughout the course, and example code will be supplied showing how to implement the preferred methods. All such code is either in the public domain or is made freely available to the participants for them to copy and use within their own organisations.
About the presenters:
Mike Kenward, GSK Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
Mike Kenward has worked in Iceland, Finland and the UK, in both research institutes and universities. He has a broad interest in modelling in biostatistics, with particular experience in longitudinal data and cross-over trials, as well as the general problem of missing data. He has co-authored three textbooks, The Design and Analysis of Cross-Over Trials (with Byron Jones), Missing Data in Clinical Studies (with Geert Molenberghs) and Multiple Imputation and its Application (with James Carpenter). He has been a consultant, principally for the pharmaceutical industry, for over 25 years, and has given many short courses throughout the world on various areas of biostatistics, especially missing data.
James Roger, Honorary Professor of Biostatistics, Department of Medical Statistics, London School of Hygiene and Tropical Medicine
James Roger has a long career as university lecturer and statistician within with pharmaceutical industry including periods with J&J and GSK. Collaboration with Mike Kenward has spanned most of that career. James’ interest in missing data stemmed from shared research on linear mixed models and small sample approximations. Recent collaboration has centred on methods that address alternative estimands to those associated with classic MAR. Collaboration with GSK has allowed the development of an implementation of these approaches within SAS using multiple imputation.
Course runs from: 10:00 – 17:30 (registration from 9:30) on Day 1 and 09:00 – 16:00 on Day 2.
Registration
Please register online at www.psiweb.org and click on Events; payment now available online.
Registration costs (includes lunch and refreshments)
Registration before 15 April 2014
PSI Members: £495 plus vat
Non-members: £540 plus vat
Registration on or after 15 April 2014
PSI Members: £595 plus vat
Non-members: £640 plus vat
Accommodation can’t be guaranteed after the early bird deadline
PSI aims to be fully inclusive and endeavours to accommodate delegates with disabilities wherever possible. Please help us to help you by letting us know if you require additional facilities or have any special requirements. Please contact us on +44 (0)845 1800 349 or at PSI@mci-group.com for further information.
Contact: Emma Lovett, Tel: +44 (0)845 1800 349
Email: PSI@mci-group.com
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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Cookie generated by applications based on the PHP language. This is a general purpose identifier used to maintain user session variables. It is normally a random generated number, how it is used can be specific to the site, but a good example is maintaining a logged-in status for a user between pages. | |||
| History.store | Session | ||
| cookiehub | .psiweb.org | CookieHub | 365 days |
Used by CookieHub to store information about whether visitors have given or declined the use of cookie categories used on the site. | |||
Preferences
Preference cookies enables the web site to remember information to customize how the web site looks or behaves for each user. This may include storing selected currency, region, language or color theme.
| Name | Hostname | Vendor | Expiry |
|---|---|---|---|
| vuid | .vimeo.com | 400 days | |
These cookies are used by the Vimeo video player on websites. | |||
| AWSALBCORS | psi.glueup.com | 7 days | |
Amazon Web Services cookie. This cookie enables us to allocate server traffic to make the user experience as smooth as possible. A so-called load balancer is used to determine which server currently has the best availability. The information generated cannot identify you as an individual. | |||
Analytical cookies
Analytical cookies help us improve our website by collecting and reporting information on its usage.
| Name | Hostname | Vendor | Expiry |
|---|---|---|---|
| _ga_ | .psiweb.org | 400 days | |
Contains a unique identifier used by Google Analytics 4 to determine that two distinct hits belong to the same user across browsing sessions. | |||
| _ga | .psiweb.org | 400 days | |
Contains a unique identifier used by Google Analytics to determine that two distinct hits belong to the same user across browsing sessions. | |||
