Date: Thursday 14th - Friday 15th October 2021
Time: 10:00-12:30 & 14:00-16:30 BST on both days
Location: Online
Presenters: Linda Sharples and James Carpenter (LSHTM)
Who is this event intended for? This course is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models and want to further their knowledge of repeated measures and other clustered data.
What is the benefit of attending? By the end of the course attendees will know how to analyse repeated measures of patients through time or other clustered data in randomised clinical trials and associated observational studies. Attendees will develop their knowledge on conditional models for continuous hierarchical and longitudinal data, GEE and discrete models. Pre-recorded lectures will allow trainees to go through course materials when convenient for them and have some time to think over and understand the topics. Practical exercises will allow hands-on experience when working with this type of data and presenters will be available during the course to answer any questions.
Repeated measures of patients through time and other clustered data are common in randomised clinical trials and associated observational studies. Measurements taken from the same patient (or from the same cluster) are likely to be correlated, so that the assumption that all responses will be identically distributed and independent from each other will not hold. Ignoring within-cluster correlation will result in bias in the estimate of the treatment effect standard error and therefore, incorrect confidence intervals and hypothesis tests. In some situations it can also result in bias in the treatment estimate itself. Using a range of worked examples, this course will explain how to analyse repeated measures and other clustered data, with an emphasis on estimating treatment effects using the appropriate covariance structure between measurements.
This course is presented through recorded lectures and online 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.
Topics covered include:
• Conditional models for continuous hierarchical data
• Conditional models for continuous longitudinal data
• Marginal models (GEE) for continuous longitudinal data
• Discrete data
NB: This course has Early-Bird rates available. These are valid for bookings on or before 17:00 BST Wednesday 15th September only.
Early-bird Members = £300+VAT
Early-bird Non-Members = £425+VAT*
Regular Members = £340+VAT
Regular Non-Members = £465+VAT*
*Please note: Non-Member rates include membership for the rest of the 2021, and entirety of the 2022 calendar year.
This course is fully booked.
Places for this course are limited and in high-demand, so please ensure you are able to attend before booking.
Please note: PSI have moved to a new membership platform called GlueUp. When registering for this event, you will be directed to this platform to complete your registration. If you are an existing member of PSI and are prompted to enter your login credentials, this will require the email address associated with your member record and the new password you created when activating your GlueUp account.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Thursday 14th - Friday 15th October 2021
Time: 10:00-12:30 & 14:00-16:30 BST on both days
Location: Online
Presenters: Linda Sharples and James Carpenter (LSHTM)
Who is this event intended for? This course is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models and want to further their knowledge of repeated measures and other clustered data.
What is the benefit of attending? By the end of the course attendees will know how to analyse repeated measures of patients through time or other clustered data in randomised clinical trials and associated observational studies. Attendees will develop their knowledge on conditional models for continuous hierarchical and longitudinal data, GEE and discrete models. Pre-recorded lectures will allow trainees to go through course materials when convenient for them and have some time to think over and understand the topics. Practical exercises will allow hands-on experience when working with this type of data and presenters will be available during the course to answer any questions.
Repeated measures of patients through time and other clustered data are common in randomised clinical trials and associated observational studies. Measurements taken from the same patient (or from the same cluster) are likely to be correlated, so that the assumption that all responses will be identically distributed and independent from each other will not hold. Ignoring within-cluster correlation will result in bias in the estimate of the treatment effect standard error and therefore, incorrect confidence intervals and hypothesis tests. In some situations it can also result in bias in the treatment estimate itself. Using a range of worked examples, this course will explain how to analyse repeated measures and other clustered data, with an emphasis on estimating treatment effects using the appropriate covariance structure between measurements.
This course is presented through recorded lectures and online 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.
Topics covered include:
• Conditional models for continuous hierarchical data
• Conditional models for continuous longitudinal data
• Marginal models (GEE) for continuous longitudinal data
• Discrete data
NB: This course has Early-Bird rates available. These are valid for bookings on or before 17:00 BST Wednesday 15th September only.
Early-bird Members = £300+VAT
Early-bird Non-Members = £425+VAT*
Regular Members = £340+VAT
Regular Non-Members = £465+VAT*
*Please note: Non-Member rates include membership for the rest of the 2021, and entirety of the 2022 calendar year.
This course is fully booked.
Places for this course are limited and in high-demand, so please ensure you are able to attend before booking.
Please note: PSI have moved to a new membership platform called GlueUp. When registering for this event, you will be directed to this platform to complete your registration. If you are an existing member of PSI and are prompted to enter your login credentials, this will require the email address associated with your member record and the new password you created when activating your GlueUp account.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Thursday 14th - Friday 15th October 2021
Time: 10:00-12:30 & 14:00-16:30 BST on both days
Location: Online
Presenters: Linda Sharples and James Carpenter (LSHTM)
Who is this event intended for? This course is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models and want to further their knowledge of repeated measures and other clustered data.
What is the benefit of attending? By the end of the course attendees will know how to analyse repeated measures of patients through time or other clustered data in randomised clinical trials and associated observational studies. Attendees will develop their knowledge on conditional models for continuous hierarchical and longitudinal data, GEE and discrete models. Pre-recorded lectures will allow trainees to go through course materials when convenient for them and have some time to think over and understand the topics. Practical exercises will allow hands-on experience when working with this type of data and presenters will be available during the course to answer any questions.
Repeated measures of patients through time and other clustered data are common in randomised clinical trials and associated observational studies. Measurements taken from the same patient (or from the same cluster) are likely to be correlated, so that the assumption that all responses will be identically distributed and independent from each other will not hold. Ignoring within-cluster correlation will result in bias in the estimate of the treatment effect standard error and therefore, incorrect confidence intervals and hypothesis tests. In some situations it can also result in bias in the treatment estimate itself. Using a range of worked examples, this course will explain how to analyse repeated measures and other clustered data, with an emphasis on estimating treatment effects using the appropriate covariance structure between measurements.
This course is presented through recorded lectures and online 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.
Topics covered include:
• Conditional models for continuous hierarchical data
• Conditional models for continuous longitudinal data
• Marginal models (GEE) for continuous longitudinal data
• Discrete data
NB: This course has Early-Bird rates available. These are valid for bookings on or before 17:00 BST Wednesday 15th September only.
Early-bird Members = £300+VAT
Early-bird Non-Members = £425+VAT*
Regular Members = £340+VAT
Regular Non-Members = £465+VAT*
*Please note: Non-Member rates include membership for the rest of the 2021, and entirety of the 2022 calendar year.
This course is fully booked.
Places for this course are limited and in high-demand, so please ensure you are able to attend before booking.
Please note: PSI have moved to a new membership platform called GlueUp. When registering for this event, you will be directed to this platform to complete your registration. If you are an existing member of PSI and are prompted to enter your login credentials, this will require the email address associated with your member record and the new password you created when activating your GlueUp account.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Thursday 14th - Friday 15th October 2021
Time: 10:00-12:30 & 14:00-16:30 BST on both days
Location: Online
Presenters: Linda Sharples and James Carpenter (LSHTM)
Who is this event intended for? This course is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models and want to further their knowledge of repeated measures and other clustered data.
What is the benefit of attending? By the end of the course attendees will know how to analyse repeated measures of patients through time or other clustered data in randomised clinical trials and associated observational studies. Attendees will develop their knowledge on conditional models for continuous hierarchical and longitudinal data, GEE and discrete models. Pre-recorded lectures will allow trainees to go through course materials when convenient for them and have some time to think over and understand the topics. Practical exercises will allow hands-on experience when working with this type of data and presenters will be available during the course to answer any questions.
Repeated measures of patients through time and other clustered data are common in randomised clinical trials and associated observational studies. Measurements taken from the same patient (or from the same cluster) are likely to be correlated, so that the assumption that all responses will be identically distributed and independent from each other will not hold. Ignoring within-cluster correlation will result in bias in the estimate of the treatment effect standard error and therefore, incorrect confidence intervals and hypothesis tests. In some situations it can also result in bias in the treatment estimate itself. Using a range of worked examples, this course will explain how to analyse repeated measures and other clustered data, with an emphasis on estimating treatment effects using the appropriate covariance structure between measurements.
This course is presented through recorded lectures and online 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.
Topics covered include:
• Conditional models for continuous hierarchical data
• Conditional models for continuous longitudinal data
• Marginal models (GEE) for continuous longitudinal data
• Discrete data
NB: This course has Early-Bird rates available. These are valid for bookings on or before 17:00 BST Wednesday 15th September only.
Early-bird Members = £300+VAT
Early-bird Non-Members = £425+VAT*
Regular Members = £340+VAT
Regular Non-Members = £465+VAT*
*Please note: Non-Member rates include membership for the rest of the 2021, and entirety of the 2022 calendar year.
This course is fully booked.
Places for this course are limited and in high-demand, so please ensure you are able to attend before booking.
Please note: PSI have moved to a new membership platform called GlueUp. When registering for this event, you will be directed to this platform to complete your registration. If you are an existing member of PSI and are prompted to enter your login credentials, this will require the email address associated with your member record and the new password you created when activating your GlueUp account.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Thursday 14th - Friday 15th October 2021
Time: 10:00-12:30 & 14:00-16:30 BST on both days
Location: Online
Presenters: Linda Sharples and James Carpenter (LSHTM)
Who is this event intended for? This course is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models and want to further their knowledge of repeated measures and other clustered data.
What is the benefit of attending? By the end of the course attendees will know how to analyse repeated measures of patients through time or other clustered data in randomised clinical trials and associated observational studies. Attendees will develop their knowledge on conditional models for continuous hierarchical and longitudinal data, GEE and discrete models. Pre-recorded lectures will allow trainees to go through course materials when convenient for them and have some time to think over and understand the topics. Practical exercises will allow hands-on experience when working with this type of data and presenters will be available during the course to answer any questions.
Repeated measures of patients through time and other clustered data are common in randomised clinical trials and associated observational studies. Measurements taken from the same patient (or from the same cluster) are likely to be correlated, so that the assumption that all responses will be identically distributed and independent from each other will not hold. Ignoring within-cluster correlation will result in bias in the estimate of the treatment effect standard error and therefore, incorrect confidence intervals and hypothesis tests. In some situations it can also result in bias in the treatment estimate itself. Using a range of worked examples, this course will explain how to analyse repeated measures and other clustered data, with an emphasis on estimating treatment effects using the appropriate covariance structure between measurements.
This course is presented through recorded lectures and online 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.
Topics covered include:
• Conditional models for continuous hierarchical data
• Conditional models for continuous longitudinal data
• Marginal models (GEE) for continuous longitudinal data
• Discrete data
NB: This course has Early-Bird rates available. These are valid for bookings on or before 17:00 BST Wednesday 15th September only.
Early-bird Members = £300+VAT
Early-bird Non-Members = £425+VAT*
Regular Members = £340+VAT
Regular Non-Members = £465+VAT*
*Please note: Non-Member rates include membership for the rest of the 2021, and entirety of the 2022 calendar year.
This course is fully booked.
Places for this course are limited and in high-demand, so please ensure you are able to attend before booking.
Please note: PSI have moved to a new membership platform called GlueUp. When registering for this event, you will be directed to this platform to complete your registration. If you are an existing member of PSI and are prompted to enter your login credentials, this will require the email address associated with your member record and the new password you created when activating your GlueUp account.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Thursday 14th - Friday 15th October 2021
Time: 10:00-12:30 & 14:00-16:30 BST on both days
Location: Online
Presenters: Linda Sharples and James Carpenter (LSHTM)
Who is this event intended for? This course is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models and want to further their knowledge of repeated measures and other clustered data.
What is the benefit of attending? By the end of the course attendees will know how to analyse repeated measures of patients through time or other clustered data in randomised clinical trials and associated observational studies. Attendees will develop their knowledge on conditional models for continuous hierarchical and longitudinal data, GEE and discrete models. Pre-recorded lectures will allow trainees to go through course materials when convenient for them and have some time to think over and understand the topics. Practical exercises will allow hands-on experience when working with this type of data and presenters will be available during the course to answer any questions.
Repeated measures of patients through time and other clustered data are common in randomised clinical trials and associated observational studies. Measurements taken from the same patient (or from the same cluster) are likely to be correlated, so that the assumption that all responses will be identically distributed and independent from each other will not hold. Ignoring within-cluster correlation will result in bias in the estimate of the treatment effect standard error and therefore, incorrect confidence intervals and hypothesis tests. In some situations it can also result in bias in the treatment estimate itself. Using a range of worked examples, this course will explain how to analyse repeated measures and other clustered data, with an emphasis on estimating treatment effects using the appropriate covariance structure between measurements.
This course is presented through recorded lectures and online 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.
Topics covered include:
• Conditional models for continuous hierarchical data
• Conditional models for continuous longitudinal data
• Marginal models (GEE) for continuous longitudinal data
• Discrete data
NB: This course has Early-Bird rates available. These are valid for bookings on or before 17:00 BST Wednesday 15th September only.
Early-bird Members = £300+VAT
Early-bird Non-Members = £425+VAT*
Regular Members = £340+VAT
Regular Non-Members = £465+VAT*
*Please note: Non-Member rates include membership for the rest of the 2021, and entirety of the 2022 calendar year.
This course is fully booked.
Places for this course are limited and in high-demand, so please ensure you are able to attend before booking.
Please note: PSI have moved to a new membership platform called GlueUp. When registering for this event, you will be directed to this platform to complete your registration. If you are an existing member of PSI and are prompted to enter your login credentials, this will require the email address associated with your member record and the new password you created when activating your GlueUp account.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
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.
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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