Date: Monday 4th, Wednesday 6th & Friday 8th July 2022
Time: 4th 09:30-12:00, 6th&8th 10:00-12:00 BST
Location: This course will take place online.
Presenter: Andy Grieve (UCB)
Who is this event intended for? Statisticians working on the design of clinical trials.
What is the benefit of attending? Participants will learn how to use Expected Power, Average Power, Predicted Power, Probability of Success and Assurance, and Bayesian Power when planning clinical trials.
Early Bird Members = £250+VAT
Early Bird Non-Members = £375*+VAT
Regular Members = £290+VAT
Regular Non-Members = £415*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
For the most part the planning of clinical trials is based on considerations of the power of a test of a given alternative hypothesis based on ideas introduced by Neyman and Pearson in 1933. As early as 1939, Jeffreys pointed out that if the true value was unknown, so was the power. Jeffreys suggested that to understand the true power of a study the conditional power values should be averaged with respect to their prior probabilities, an unconditional power. This idea was taken up in the 1980’s by Spiegelhalter and colleagues and in the early 2000s by O’Hagan and Stevens who introduced the concept of assurance. All of this work uses unconditional as opposed to conditional probabilities.
The course is based on a book with the same title in the Chapman Hall/CRC Biostatistics Series to appear in May 2022. All participants for this course will receive a copy of the book.
Topics covered include:
• Expected Power, Average Power (AP), Predicted Power, Probability of Success and Assurance for a Simple Normal Model with Known Variance
Bounds on AP and Assurance
Sample Size for a Given AP/Assurance and Normalized Assurance.
Applying Assurance to a Series of Studies
Assurance for a Clinical Trial with a Single Interim Analysis
Non-Inferiority Trials
• AP in Non-Normal Settings – Unknown variance, Binary Data, Survival Analysis
• Bayesian Power (BP)
Bounds on BP
Sample Size for a Given BP/Normalized BP
Posterior Conditional Success Distributions
Prior Distributions for Power and sample Size
• Interim Predictions and Links to AP
• AP with Multiple Decision Criteria – Normal Model with Known Variance
Bounds on AP and Assurance
Generalized Assurance
Bayesian Approach to Multiple Decision Criteria.
Posterior Conditional GO/NOGO/Pause/Distributions
• Surety and Assurance in Estimation
An Alternative to Power in sample Size Determination
Unconditional Sample Sizing Based on CI width
Session 1:- Monday 4th July | 09:30-12:00
Session 2:- Wednesday 6th July | 10:00-12:00
Session 3:- Friday 8th July | 10:00-12:00
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
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: Monday 4th, Wednesday 6th & Friday 8th July 2022
Time: 4th 09:30-12:00, 6th&8th 10:00-12:00 BST
Location: This course will take place online.
Presenter: Andy Grieve (UCB)
Who is this event intended for? Statisticians working on the design of clinical trials.
What is the benefit of attending? Participants will learn how to use Expected Power, Average Power, Predicted Power, Probability of Success and Assurance, and Bayesian Power when planning clinical trials.
Early Bird Members = £250+VAT
Early Bird Non-Members = £375*+VAT
Regular Members = £290+VAT
Regular Non-Members = £415*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
For the most part the planning of clinical trials is based on considerations of the power of a test of a given alternative hypothesis based on ideas introduced by Neyman and Pearson in 1933. As early as 1939, Jeffreys pointed out that if the true value was unknown, so was the power. Jeffreys suggested that to understand the true power of a study the conditional power values should be averaged with respect to their prior probabilities, an unconditional power. This idea was taken up in the 1980’s by Spiegelhalter and colleagues and in the early 2000s by O’Hagan and Stevens who introduced the concept of assurance. All of this work uses unconditional as opposed to conditional probabilities.
The course is based on a book with the same title in the Chapman Hall/CRC Biostatistics Series to appear in May 2022. All participants for this course will receive a copy of the book.
Topics covered include:
• Expected Power, Average Power (AP), Predicted Power, Probability of Success and Assurance for a Simple Normal Model with Known Variance
Bounds on AP and Assurance
Sample Size for a Given AP/Assurance and Normalized Assurance.
Applying Assurance to a Series of Studies
Assurance for a Clinical Trial with a Single Interim Analysis
Non-Inferiority Trials
• AP in Non-Normal Settings – Unknown variance, Binary Data, Survival Analysis
• Bayesian Power (BP)
Bounds on BP
Sample Size for a Given BP/Normalized BP
Posterior Conditional Success Distributions
Prior Distributions for Power and sample Size
• Interim Predictions and Links to AP
• AP with Multiple Decision Criteria – Normal Model with Known Variance
Bounds on AP and Assurance
Generalized Assurance
Bayesian Approach to Multiple Decision Criteria.
Posterior Conditional GO/NOGO/Pause/Distributions
• Surety and Assurance in Estimation
An Alternative to Power in sample Size Determination
Unconditional Sample Sizing Based on CI width
Session 1:- Monday 4th July | 09:30-12:00
Session 2:- Wednesday 6th July | 10:00-12:00
Session 3:- Friday 8th July | 10:00-12:00
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
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: Monday 4th, Wednesday 6th & Friday 8th July 2022
Time: 4th 09:30-12:00, 6th&8th 10:00-12:00 BST
Location: This course will take place online.
Presenter: Andy Grieve (UCB)
Who is this event intended for? Statisticians working on the design of clinical trials.
What is the benefit of attending? Participants will learn how to use Expected Power, Average Power, Predicted Power, Probability of Success and Assurance, and Bayesian Power when planning clinical trials.
Early Bird Members = £250+VAT
Early Bird Non-Members = £375*+VAT
Regular Members = £290+VAT
Regular Non-Members = £415*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
For the most part the planning of clinical trials is based on considerations of the power of a test of a given alternative hypothesis based on ideas introduced by Neyman and Pearson in 1933. As early as 1939, Jeffreys pointed out that if the true value was unknown, so was the power. Jeffreys suggested that to understand the true power of a study the conditional power values should be averaged with respect to their prior probabilities, an unconditional power. This idea was taken up in the 1980’s by Spiegelhalter and colleagues and in the early 2000s by O’Hagan and Stevens who introduced the concept of assurance. All of this work uses unconditional as opposed to conditional probabilities.
The course is based on a book with the same title in the Chapman Hall/CRC Biostatistics Series to appear in May 2022. All participants for this course will receive a copy of the book.
Topics covered include:
• Expected Power, Average Power (AP), Predicted Power, Probability of Success and Assurance for a Simple Normal Model with Known Variance
Bounds on AP and Assurance
Sample Size for a Given AP/Assurance and Normalized Assurance.
Applying Assurance to a Series of Studies
Assurance for a Clinical Trial with a Single Interim Analysis
Non-Inferiority Trials
• AP in Non-Normal Settings – Unknown variance, Binary Data, Survival Analysis
• Bayesian Power (BP)
Bounds on BP
Sample Size for a Given BP/Normalized BP
Posterior Conditional Success Distributions
Prior Distributions for Power and sample Size
• Interim Predictions and Links to AP
• AP with Multiple Decision Criteria – Normal Model with Known Variance
Bounds on AP and Assurance
Generalized Assurance
Bayesian Approach to Multiple Decision Criteria.
Posterior Conditional GO/NOGO/Pause/Distributions
• Surety and Assurance in Estimation
An Alternative to Power in sample Size Determination
Unconditional Sample Sizing Based on CI width
Session 1:- Monday 4th July | 09:30-12:00
Session 2:- Wednesday 6th July | 10:00-12:00
Session 3:- Friday 8th July | 10:00-12:00
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
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: Monday 4th, Wednesday 6th & Friday 8th July 2022
Time: 4th 09:30-12:00, 6th&8th 10:00-12:00 BST
Location: This course will take place online.
Presenter: Andy Grieve (UCB)
Who is this event intended for? Statisticians working on the design of clinical trials.
What is the benefit of attending? Participants will learn how to use Expected Power, Average Power, Predicted Power, Probability of Success and Assurance, and Bayesian Power when planning clinical trials.
Early Bird Members = £250+VAT
Early Bird Non-Members = £375*+VAT
Regular Members = £290+VAT
Regular Non-Members = £415*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
For the most part the planning of clinical trials is based on considerations of the power of a test of a given alternative hypothesis based on ideas introduced by Neyman and Pearson in 1933. As early as 1939, Jeffreys pointed out that if the true value was unknown, so was the power. Jeffreys suggested that to understand the true power of a study the conditional power values should be averaged with respect to their prior probabilities, an unconditional power. This idea was taken up in the 1980’s by Spiegelhalter and colleagues and in the early 2000s by O’Hagan and Stevens who introduced the concept of assurance. All of this work uses unconditional as opposed to conditional probabilities.
The course is based on a book with the same title in the Chapman Hall/CRC Biostatistics Series to appear in May 2022. All participants for this course will receive a copy of the book.
Topics covered include:
• Expected Power, Average Power (AP), Predicted Power, Probability of Success and Assurance for a Simple Normal Model with Known Variance
Bounds on AP and Assurance
Sample Size for a Given AP/Assurance and Normalized Assurance.
Applying Assurance to a Series of Studies
Assurance for a Clinical Trial with a Single Interim Analysis
Non-Inferiority Trials
• AP in Non-Normal Settings – Unknown variance, Binary Data, Survival Analysis
• Bayesian Power (BP)
Bounds on BP
Sample Size for a Given BP/Normalized BP
Posterior Conditional Success Distributions
Prior Distributions for Power and sample Size
• Interim Predictions and Links to AP
• AP with Multiple Decision Criteria – Normal Model with Known Variance
Bounds on AP and Assurance
Generalized Assurance
Bayesian Approach to Multiple Decision Criteria.
Posterior Conditional GO/NOGO/Pause/Distributions
• Surety and Assurance in Estimation
An Alternative to Power in sample Size Determination
Unconditional Sample Sizing Based on CI width
Session 1:- Monday 4th July | 09:30-12:00
Session 2:- Wednesday 6th July | 10:00-12:00
Session 3:- Friday 8th July | 10:00-12:00
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
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: Monday 4th, Wednesday 6th & Friday 8th July 2022
Time: 4th 09:30-12:00, 6th&8th 10:00-12:00 BST
Location: This course will take place online.
Presenter: Andy Grieve (UCB)
Who is this event intended for? Statisticians working on the design of clinical trials.
What is the benefit of attending? Participants will learn how to use Expected Power, Average Power, Predicted Power, Probability of Success and Assurance, and Bayesian Power when planning clinical trials.
Early Bird Members = £250+VAT
Early Bird Non-Members = £375*+VAT
Regular Members = £290+VAT
Regular Non-Members = £415*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
For the most part the planning of clinical trials is based on considerations of the power of a test of a given alternative hypothesis based on ideas introduced by Neyman and Pearson in 1933. As early as 1939, Jeffreys pointed out that if the true value was unknown, so was the power. Jeffreys suggested that to understand the true power of a study the conditional power values should be averaged with respect to their prior probabilities, an unconditional power. This idea was taken up in the 1980’s by Spiegelhalter and colleagues and in the early 2000s by O’Hagan and Stevens who introduced the concept of assurance. All of this work uses unconditional as opposed to conditional probabilities.
The course is based on a book with the same title in the Chapman Hall/CRC Biostatistics Series to appear in May 2022. All participants for this course will receive a copy of the book.
Topics covered include:
• Expected Power, Average Power (AP), Predicted Power, Probability of Success and Assurance for a Simple Normal Model with Known Variance
Bounds on AP and Assurance
Sample Size for a Given AP/Assurance and Normalized Assurance.
Applying Assurance to a Series of Studies
Assurance for a Clinical Trial with a Single Interim Analysis
Non-Inferiority Trials
• AP in Non-Normal Settings – Unknown variance, Binary Data, Survival Analysis
• Bayesian Power (BP)
Bounds on BP
Sample Size for a Given BP/Normalized BP
Posterior Conditional Success Distributions
Prior Distributions for Power and sample Size
• Interim Predictions and Links to AP
• AP with Multiple Decision Criteria – Normal Model with Known Variance
Bounds on AP and Assurance
Generalized Assurance
Bayesian Approach to Multiple Decision Criteria.
Posterior Conditional GO/NOGO/Pause/Distributions
• Surety and Assurance in Estimation
An Alternative to Power in sample Size Determination
Unconditional Sample Sizing Based on CI width
Session 1:- Monday 4th July | 09:30-12:00
Session 2:- Wednesday 6th July | 10:00-12:00
Session 3:- Friday 8th July | 10:00-12:00
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
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: Monday 4th, Wednesday 6th & Friday 8th July 2022
Time: 4th 09:30-12:00, 6th&8th 10:00-12:00 BST
Location: This course will take place online.
Presenter: Andy Grieve (UCB)
Who is this event intended for? Statisticians working on the design of clinical trials.
What is the benefit of attending? Participants will learn how to use Expected Power, Average Power, Predicted Power, Probability of Success and Assurance, and Bayesian Power when planning clinical trials.
Early Bird Members = £250+VAT
Early Bird Non-Members = £375*+VAT
Regular Members = £290+VAT
Regular Non-Members = £415*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
For the most part the planning of clinical trials is based on considerations of the power of a test of a given alternative hypothesis based on ideas introduced by Neyman and Pearson in 1933. As early as 1939, Jeffreys pointed out that if the true value was unknown, so was the power. Jeffreys suggested that to understand the true power of a study the conditional power values should be averaged with respect to their prior probabilities, an unconditional power. This idea was taken up in the 1980’s by Spiegelhalter and colleagues and in the early 2000s by O’Hagan and Stevens who introduced the concept of assurance. All of this work uses unconditional as opposed to conditional probabilities.
The course is based on a book with the same title in the Chapman Hall/CRC Biostatistics Series to appear in May 2022. All participants for this course will receive a copy of the book.
Topics covered include:
• Expected Power, Average Power (AP), Predicted Power, Probability of Success and Assurance for a Simple Normal Model with Known Variance
Bounds on AP and Assurance
Sample Size for a Given AP/Assurance and Normalized Assurance.
Applying Assurance to a Series of Studies
Assurance for a Clinical Trial with a Single Interim Analysis
Non-Inferiority Trials
• AP in Non-Normal Settings – Unknown variance, Binary Data, Survival Analysis
• Bayesian Power (BP)
Bounds on BP
Sample Size for a Given BP/Normalized BP
Posterior Conditional Success Distributions
Prior Distributions for Power and sample Size
• Interim Predictions and Links to AP
• AP with Multiple Decision Criteria – Normal Model with Known Variance
Bounds on AP and Assurance
Generalized Assurance
Bayesian Approach to Multiple Decision Criteria.
Posterior Conditional GO/NOGO/Pause/Distributions
• Surety and Assurance in Estimation
An Alternative to Power in sample Size Determination
Unconditional Sample Sizing Based on CI width
Session 1:- Monday 4th July | 09:30-12:00
Session 2:- Wednesday 6th July | 10:00-12:00
Session 3:- Friday 8th July | 10:00-12:00
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
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.
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 webinar is targeted at statisticians working in the pharmaceutical industry, and the objective is to 1) provide a basic understanding of IV methodology including how it relates to causal inference, and 2) present two inspirational pharma-relevant applications.
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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