Date: Tuesday 19th November 2024
Time: 14:00-15:30 GMT | 15:00-16:30 CET
Location: Online via Zoom
Speakers: Kaspar Rufibach, Susan Gruber, Florian Lasch
Who is this event intended for? Applied statisticians, and people genuinely interested in applying state-of-the-art statistical methodology.
What is the benefit of attending? Increased understanding and insights in causal inference principles and methodology.
This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.
In this webinar, three speakers will share their perspective on the using of causal inference methodology in the analysis of RCT data. The audience will be presented with ideas and opportunities on why and how to apply causal inference principles / techniques in their work. And more importantly how causal approaches can help evaluating evidence for answers to causal-by-nature scientific questions.
First, Kaspar Rufibach (Merck) will share his perspectives on opportunities to apply causal methods. Next, Susan Gruber (TL revolution) will discuss targeted learning as a framework to address causal questions and the importance of sensitivity analyses. Finally, Florian Lasch (EMA) will discuss both the importance of the causal inference angle in determining estimands, and will discuss a case study.
The webinar will end with a panel discussion.
|
Speaker |
Biography |
Abstract |
|
|
Kaspar Rufibach is a biostatistician who is passionate about supporting statisticians and drug developers to continuously challenge the status quo, with the aim of improving the drug development process, making it more efficient, and enabling access. More on the oncology estimand WG: http://www.oncoestimand.org More on the EFSPI statistical methodology leaders group: https://efspieurope.github.io/efspi/methods/methods_intro.html More on Kaspar: http://www.kasparrufibach.ch |
I will start with providing a few examples of very valid scientific questions in drug development that typically ask for causal answers, but which are routinely answered in ad-hoc ways that rarely allow for a causal interpretation. Further reasons why I believe a clinical biostatistician needs to know about causal inference will be given. I will conclude with a call to apply and develop statistical and causal inference methodology to fill the gap between valid causal questions and routine ad-hoc answers.
|
|
|
Susan Gruber, co-founder of TL Revolution and Founder of Putnam Data Sciences, is a biostatistician and computer scientist specializing in causal inference and predictive modeling. Her work focuses on improving methods and tools for generating robust real-world evidence to support biopharmaceutical and medical decision-making through Targeted Learning. Her tmle R package on CRAN has over 70,000 downloads worldwide. |
Targeted Learning is a framework that combines causal inference, statistics, and machine learning to address complex issues in analyzing data from randomized controlled trials and studies that incorporate real-world data. This talk provides a high-level introduction to the Targeted Learning Estimation Roadmap, statistical analysis using Targeted Maximum Likelihood Estimation (TMLE), and the role of sensitivity analysis to assess the level of support for drawing a substantive conclusion from the study findings. |
|
|
Florian is a Biostatistician with a degree in mathematics and a PhD from Hannover Medical School. Florian works as a Biostatistics Specialist at the European Medicines Agency, providing scientific support to development and evaluation throughout all stages of marketing authorisation assessments of medicinal products, and leads the ACT EU Priority Action on Clinical Trial Methodologies and the EMA Estimands Implementation Group. |
The estimands framework facilitates the application of thinking and methodology developed in the causal inference community to the design and analysis of clinical trials. This presentation will reflect on the opportunities and challenges of applying causal inference methodology to clinical trials. A case study in Alzheimer’s Disease where the intercurrent event ‘initiation of symptomatic medication’ is handled with a hypothetical strategy will illustrate the key points. |
Date: Tuesday 19th November 2024
Time: 14:00-15:30 GMT | 15:00-16:30 CET
Location: Online via Zoom
Speakers: Kaspar Rufibach, Susan Gruber, Florian Lasch
Who is this event intended for? Applied statisticians, and people genuinely interested in applying state-of-the-art statistical methodology.
What is the benefit of attending? Increased understanding and insights in causal inference principles and methodology.
This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.
In this webinar, three speakers will share their perspective on the using of causal inference methodology in the analysis of RCT data. The audience will be presented with ideas and opportunities on why and how to apply causal inference principles / techniques in their work. And more importantly how causal approaches can help evaluating evidence for answers to causal-by-nature scientific questions.
First, Kaspar Rufibach (Merck) will share his perspectives on opportunities to apply causal methods. Next, Susan Gruber (TL revolution) will discuss targeted learning as a framework to address causal questions and the importance of sensitivity analyses. Finally, Florian Lasch (EMA) will discuss both the importance of the causal inference angle in determining estimands, and will discuss a case study.
The webinar will end with a panel discussion.
|
Speaker |
Biography |
Abstract |
|
|
Kaspar Rufibach is a biostatistician who is passionate about supporting statisticians and drug developers to continuously challenge the status quo, with the aim of improving the drug development process, making it more efficient, and enabling access. More on the oncology estimand WG: http://www.oncoestimand.org More on the EFSPI statistical methodology leaders group: https://efspieurope.github.io/efspi/methods/methods_intro.html More on Kaspar: http://www.kasparrufibach.ch |
I will start with providing a few examples of very valid scientific questions in drug development that typically ask for causal answers, but which are routinely answered in ad-hoc ways that rarely allow for a causal interpretation. Further reasons why I believe a clinical biostatistician needs to know about causal inference will be given. I will conclude with a call to apply and develop statistical and causal inference methodology to fill the gap between valid causal questions and routine ad-hoc answers.
|
|
|
Susan Gruber, co-founder of TL Revolution and Founder of Putnam Data Sciences, is a biostatistician and computer scientist specializing in causal inference and predictive modeling. Her work focuses on improving methods and tools for generating robust real-world evidence to support biopharmaceutical and medical decision-making through Targeted Learning. Her tmle R package on CRAN has over 70,000 downloads worldwide. |
Targeted Learning is a framework that combines causal inference, statistics, and machine learning to address complex issues in analyzing data from randomized controlled trials and studies that incorporate real-world data. This talk provides a high-level introduction to the Targeted Learning Estimation Roadmap, statistical analysis using Targeted Maximum Likelihood Estimation (TMLE), and the role of sensitivity analysis to assess the level of support for drawing a substantive conclusion from the study findings. |
|
|
Florian is a Biostatistician with a degree in mathematics and a PhD from Hannover Medical School. Florian works as a Biostatistics Specialist at the European Medicines Agency, providing scientific support to development and evaluation throughout all stages of marketing authorisation assessments of medicinal products, and leads the ACT EU Priority Action on Clinical Trial Methodologies and the EMA Estimands Implementation Group. |
The estimands framework facilitates the application of thinking and methodology developed in the causal inference community to the design and analysis of clinical trials. This presentation will reflect on the opportunities and challenges of applying causal inference methodology to clinical trials. A case study in Alzheimer’s Disease where the intercurrent event ‘initiation of symptomatic medication’ is handled with a hypothetical strategy will illustrate the key points. |
Date: Tuesday 19th November 2024
Time: 14:00-15:30 GMT | 15:00-16:30 CET
Location: Online via Zoom
Speakers: Kaspar Rufibach, Susan Gruber, Florian Lasch
Who is this event intended for? Applied statisticians, and people genuinely interested in applying state-of-the-art statistical methodology.
What is the benefit of attending? Increased understanding and insights in causal inference principles and methodology.
This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.
In this webinar, three speakers will share their perspective on the using of causal inference methodology in the analysis of RCT data. The audience will be presented with ideas and opportunities on why and how to apply causal inference principles / techniques in their work. And more importantly how causal approaches can help evaluating evidence for answers to causal-by-nature scientific questions.
First, Kaspar Rufibach (Merck) will share his perspectives on opportunities to apply causal methods. Next, Susan Gruber (TL revolution) will discuss targeted learning as a framework to address causal questions and the importance of sensitivity analyses. Finally, Florian Lasch (EMA) will discuss both the importance of the causal inference angle in determining estimands, and will discuss a case study.
The webinar will end with a panel discussion.
|
Speaker |
Biography |
Abstract |
|
|
Kaspar Rufibach is a biostatistician who is passionate about supporting statisticians and drug developers to continuously challenge the status quo, with the aim of improving the drug development process, making it more efficient, and enabling access. More on the oncology estimand WG: http://www.oncoestimand.org More on the EFSPI statistical methodology leaders group: https://efspieurope.github.io/efspi/methods/methods_intro.html More on Kaspar: http://www.kasparrufibach.ch |
I will start with providing a few examples of very valid scientific questions in drug development that typically ask for causal answers, but which are routinely answered in ad-hoc ways that rarely allow for a causal interpretation. Further reasons why I believe a clinical biostatistician needs to know about causal inference will be given. I will conclude with a call to apply and develop statistical and causal inference methodology to fill the gap between valid causal questions and routine ad-hoc answers.
|
|
|
Susan Gruber, co-founder of TL Revolution and Founder of Putnam Data Sciences, is a biostatistician and computer scientist specializing in causal inference and predictive modeling. Her work focuses on improving methods and tools for generating robust real-world evidence to support biopharmaceutical and medical decision-making through Targeted Learning. Her tmle R package on CRAN has over 70,000 downloads worldwide. |
Targeted Learning is a framework that combines causal inference, statistics, and machine learning to address complex issues in analyzing data from randomized controlled trials and studies that incorporate real-world data. This talk provides a high-level introduction to the Targeted Learning Estimation Roadmap, statistical analysis using Targeted Maximum Likelihood Estimation (TMLE), and the role of sensitivity analysis to assess the level of support for drawing a substantive conclusion from the study findings. |
|
|
Florian is a Biostatistician with a degree in mathematics and a PhD from Hannover Medical School. Florian works as a Biostatistics Specialist at the European Medicines Agency, providing scientific support to development and evaluation throughout all stages of marketing authorisation assessments of medicinal products, and leads the ACT EU Priority Action on Clinical Trial Methodologies and the EMA Estimands Implementation Group. |
The estimands framework facilitates the application of thinking and methodology developed in the causal inference community to the design and analysis of clinical trials. This presentation will reflect on the opportunities and challenges of applying causal inference methodology to clinical trials. A case study in Alzheimer’s Disease where the intercurrent event ‘initiation of symptomatic medication’ is handled with a hypothetical strategy will illustrate the key points. |
Date: Tuesday 19th November 2024
Time: 14:00-15:30 GMT | 15:00-16:30 CET
Location: Online via Zoom
Speakers: Kaspar Rufibach, Susan Gruber, Florian Lasch
Who is this event intended for? Applied statisticians, and people genuinely interested in applying state-of-the-art statistical methodology.
What is the benefit of attending? Increased understanding and insights in causal inference principles and methodology.
This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.
In this webinar, three speakers will share their perspective on the using of causal inference methodology in the analysis of RCT data. The audience will be presented with ideas and opportunities on why and how to apply causal inference principles / techniques in their work. And more importantly how causal approaches can help evaluating evidence for answers to causal-by-nature scientific questions.
First, Kaspar Rufibach (Merck) will share his perspectives on opportunities to apply causal methods. Next, Susan Gruber (TL revolution) will discuss targeted learning as a framework to address causal questions and the importance of sensitivity analyses. Finally, Florian Lasch (EMA) will discuss both the importance of the causal inference angle in determining estimands, and will discuss a case study.
The webinar will end with a panel discussion.
|
Speaker |
Biography |
Abstract |
|
|
Kaspar Rufibach is a biostatistician who is passionate about supporting statisticians and drug developers to continuously challenge the status quo, with the aim of improving the drug development process, making it more efficient, and enabling access. More on the oncology estimand WG: http://www.oncoestimand.org More on the EFSPI statistical methodology leaders group: https://efspieurope.github.io/efspi/methods/methods_intro.html More on Kaspar: http://www.kasparrufibach.ch |
I will start with providing a few examples of very valid scientific questions in drug development that typically ask for causal answers, but which are routinely answered in ad-hoc ways that rarely allow for a causal interpretation. Further reasons why I believe a clinical biostatistician needs to know about causal inference will be given. I will conclude with a call to apply and develop statistical and causal inference methodology to fill the gap between valid causal questions and routine ad-hoc answers.
|
|
|
Susan Gruber, co-founder of TL Revolution and Founder of Putnam Data Sciences, is a biostatistician and computer scientist specializing in causal inference and predictive modeling. Her work focuses on improving methods and tools for generating robust real-world evidence to support biopharmaceutical and medical decision-making through Targeted Learning. Her tmle R package on CRAN has over 70,000 downloads worldwide. |
Targeted Learning is a framework that combines causal inference, statistics, and machine learning to address complex issues in analyzing data from randomized controlled trials and studies that incorporate real-world data. This talk provides a high-level introduction to the Targeted Learning Estimation Roadmap, statistical analysis using Targeted Maximum Likelihood Estimation (TMLE), and the role of sensitivity analysis to assess the level of support for drawing a substantive conclusion from the study findings. |
|
|
Florian is a Biostatistician with a degree in mathematics and a PhD from Hannover Medical School. Florian works as a Biostatistics Specialist at the European Medicines Agency, providing scientific support to development and evaluation throughout all stages of marketing authorisation assessments of medicinal products, and leads the ACT EU Priority Action on Clinical Trial Methodologies and the EMA Estimands Implementation Group. |
The estimands framework facilitates the application of thinking and methodology developed in the causal inference community to the design and analysis of clinical trials. This presentation will reflect on the opportunities and challenges of applying causal inference methodology to clinical trials. A case study in Alzheimer’s Disease where the intercurrent event ‘initiation of symptomatic medication’ is handled with a hypothetical strategy will illustrate the key points. |
Date: Tuesday 19th November 2024
Time: 14:00-15:30 GMT | 15:00-16:30 CET
Location: Online via Zoom
Speakers: Kaspar Rufibach, Susan Gruber, Florian Lasch
Who is this event intended for? Applied statisticians, and people genuinely interested in applying state-of-the-art statistical methodology.
What is the benefit of attending? Increased understanding and insights in causal inference principles and methodology.
This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.
In this webinar, three speakers will share their perspective on the using of causal inference methodology in the analysis of RCT data. The audience will be presented with ideas and opportunities on why and how to apply causal inference principles / techniques in their work. And more importantly how causal approaches can help evaluating evidence for answers to causal-by-nature scientific questions.
First, Kaspar Rufibach (Merck) will share his perspectives on opportunities to apply causal methods. Next, Susan Gruber (TL revolution) will discuss targeted learning as a framework to address causal questions and the importance of sensitivity analyses. Finally, Florian Lasch (EMA) will discuss both the importance of the causal inference angle in determining estimands, and will discuss a case study.
The webinar will end with a panel discussion.
|
Speaker |
Biography |
Abstract |
|
|
Kaspar Rufibach is a biostatistician who is passionate about supporting statisticians and drug developers to continuously challenge the status quo, with the aim of improving the drug development process, making it more efficient, and enabling access. More on the oncology estimand WG: http://www.oncoestimand.org More on the EFSPI statistical methodology leaders group: https://efspieurope.github.io/efspi/methods/methods_intro.html More on Kaspar: http://www.kasparrufibach.ch |
I will start with providing a few examples of very valid scientific questions in drug development that typically ask for causal answers, but which are routinely answered in ad-hoc ways that rarely allow for a causal interpretation. Further reasons why I believe a clinical biostatistician needs to know about causal inference will be given. I will conclude with a call to apply and develop statistical and causal inference methodology to fill the gap between valid causal questions and routine ad-hoc answers.
|
|
|
Susan Gruber, co-founder of TL Revolution and Founder of Putnam Data Sciences, is a biostatistician and computer scientist specializing in causal inference and predictive modeling. Her work focuses on improving methods and tools for generating robust real-world evidence to support biopharmaceutical and medical decision-making through Targeted Learning. Her tmle R package on CRAN has over 70,000 downloads worldwide. |
Targeted Learning is a framework that combines causal inference, statistics, and machine learning to address complex issues in analyzing data from randomized controlled trials and studies that incorporate real-world data. This talk provides a high-level introduction to the Targeted Learning Estimation Roadmap, statistical analysis using Targeted Maximum Likelihood Estimation (TMLE), and the role of sensitivity analysis to assess the level of support for drawing a substantive conclusion from the study findings. |
|
|
Florian is a Biostatistician with a degree in mathematics and a PhD from Hannover Medical School. Florian works as a Biostatistics Specialist at the European Medicines Agency, providing scientific support to development and evaluation throughout all stages of marketing authorisation assessments of medicinal products, and leads the ACT EU Priority Action on Clinical Trial Methodologies and the EMA Estimands Implementation Group. |
The estimands framework facilitates the application of thinking and methodology developed in the causal inference community to the design and analysis of clinical trials. This presentation will reflect on the opportunities and challenges of applying causal inference methodology to clinical trials. A case study in Alzheimer’s Disease where the intercurrent event ‘initiation of symptomatic medication’ is handled with a hypothetical strategy will illustrate the key points. |
Date: Tuesday 19th November 2024
Time: 14:00-15:30 GMT | 15:00-16:30 CET
Location: Online via Zoom
Speakers: Kaspar Rufibach, Susan Gruber, Florian Lasch
Who is this event intended for? Applied statisticians, and people genuinely interested in applying state-of-the-art statistical methodology.
What is the benefit of attending? Increased understanding and insights in causal inference principles and methodology.
This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.
In this webinar, three speakers will share their perspective on the using of causal inference methodology in the analysis of RCT data. The audience will be presented with ideas and opportunities on why and how to apply causal inference principles / techniques in their work. And more importantly how causal approaches can help evaluating evidence for answers to causal-by-nature scientific questions.
First, Kaspar Rufibach (Merck) will share his perspectives on opportunities to apply causal methods. Next, Susan Gruber (TL revolution) will discuss targeted learning as a framework to address causal questions and the importance of sensitivity analyses. Finally, Florian Lasch (EMA) will discuss both the importance of the causal inference angle in determining estimands, and will discuss a case study.
The webinar will end with a panel discussion.
|
Speaker |
Biography |
Abstract |
|
|
Kaspar Rufibach is a biostatistician who is passionate about supporting statisticians and drug developers to continuously challenge the status quo, with the aim of improving the drug development process, making it more efficient, and enabling access. More on the oncology estimand WG: http://www.oncoestimand.org More on the EFSPI statistical methodology leaders group: https://efspieurope.github.io/efspi/methods/methods_intro.html More on Kaspar: http://www.kasparrufibach.ch |
I will start with providing a few examples of very valid scientific questions in drug development that typically ask for causal answers, but which are routinely answered in ad-hoc ways that rarely allow for a causal interpretation. Further reasons why I believe a clinical biostatistician needs to know about causal inference will be given. I will conclude with a call to apply and develop statistical and causal inference methodology to fill the gap between valid causal questions and routine ad-hoc answers.
|
|
|
Susan Gruber, co-founder of TL Revolution and Founder of Putnam Data Sciences, is a biostatistician and computer scientist specializing in causal inference and predictive modeling. Her work focuses on improving methods and tools for generating robust real-world evidence to support biopharmaceutical and medical decision-making through Targeted Learning. Her tmle R package on CRAN has over 70,000 downloads worldwide. |
Targeted Learning is a framework that combines causal inference, statistics, and machine learning to address complex issues in analyzing data from randomized controlled trials and studies that incorporate real-world data. This talk provides a high-level introduction to the Targeted Learning Estimation Roadmap, statistical analysis using Targeted Maximum Likelihood Estimation (TMLE), and the role of sensitivity analysis to assess the level of support for drawing a substantive conclusion from the study findings. |
|
|
Florian is a Biostatistician with a degree in mathematics and a PhD from Hannover Medical School. Florian works as a Biostatistics Specialist at the European Medicines Agency, providing scientific support to development and evaluation throughout all stages of marketing authorisation assessments of medicinal products, and leads the ACT EU Priority Action on Clinical Trial Methodologies and the EMA Estimands Implementation Group. |
The estimands framework facilitates the application of thinking and methodology developed in the causal inference community to the design and analysis of clinical trials. This presentation will reflect on the opportunities and challenges of applying causal inference methodology to clinical trials. A case study in Alzheimer’s Disease where the intercurrent event ‘initiation of symptomatic medication’ is handled with a hypothetical strategy will illustrate the key points. |
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.
About cookies on this site
We use cookies to collect and analyse information on site performance and usage, to provide social media features and to enhance and customise content and advertisements.
About cookies on this site
Cookies used on the site are categorized and below you can read about each category and allow or deny some or all of them. When categories than have been previously allowed are disabled, all cookies assigned to that category will be removed from your browser. Additionally you can see a list of cookies assigned to each category and detailed information in the cookie declaration.
Necessary cookies
Some cookies are required to provide core functionality. The website won't function properly without these cookies and they are enabled by default and cannot be disabled.
CookieHub is a Consent Management Platform (CMP) which allows users to control storage and processing of personal information.
Cloudflare is a global network designed to make everything you connect to the Internet secure, private, fast, and reliable.
Amazon Web Services offers a broad set of global cloud-based products including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security, and enterprise applications.
Microsoft Azure is a cloud computing platform offering a wide range of services, including virtual machines, databases, and AI tools.
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.
Analytical cookies
Analytical cookies help us improve our website by collecting and reporting information on its usage.
Google Analytics is a web analytics service offered by Google that tracks and reports website traffic.
Vimeo, Inc. is an American video hosting, sharing, services provider, and broadcaster. Vimeo focuses on the delivery of high-definition video across a range of devices.
Cookies used on the site are categorized and below you can read about each category and allow or deny some or all of them. When categories than have been previously allowed are disabled, all cookies assigned to that category will be removed from your browser. Additionally you can see a list of cookies assigned to each category and detailed information in the cookie declaration.
Necessary cookies
Some cookies are required to provide core functionality. The website won't function properly without these cookies and they are enabled by default and cannot be disabled.
| Name | Hostname | Vendor | Expiry |
|---|---|---|---|
| ARRAffinity | .psiweb.org | Session | |
This cookie is set by websites run on the Windows Azure cloud platform. It is used for load balancing to make sure the visitor page requests are routed to the same server in any browsing session. | |||
| ARRAffinitySameSite | .psiweb.org | Session | |
Used to distribute traffic to the website on several servers in order to optimize response times. | |||
| __cf_bm | .vimeo.com | Cloudflare, Inc. | 1 hour |
The __cf_bm cookie supports Cloudflare Bot Management by managing incoming traffic that matches criteria associated with bots. The cookie does not collect any personal data, and any information collected is subject to one-way encryption. | |||
| _cfuvid | .vimeo.com | Session | |
Used by Cloudflare WAF to distinguish individual users who share the same IP address and apply rate limits | |||
| __cf_bm | .glueup.com | Cloudflare, Inc. | 1 hour |
The __cf_bm cookie supports Cloudflare Bot Management by managing incoming traffic that matches criteria associated with bots. The cookie does not collect any personal data, and any information collected is subject to one-way encryption. | |||
| AWSALBTGCORS | psi.glueup.com | 7 days | |
AWS Classic Load Balancer Cookie: Load Balancing Cookie: Used to map the session to the instance. Same value as AWSELB. | |||
| PHPSESSID | psi.glueup.com | Session | |
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. | |||
.png?sfvrsn=e7ecafdb_0&MaxWidth=200&MaxHeight=200&ScaleUp=false&Quality=High&Method=ResizeFitToAreaArguments&Signature=0A8FE0E627EB292A3E804E12BFD8E6DF "kaspar1 (002)")
