In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
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.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
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.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
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.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
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.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
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.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
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.
