PSI VisSIG Wonderful Wednesday Webinar Series
This is a good opportunity to develop your knowledge by thinking through a practical example, practicing how to apply graphics principles, and developing your coding skills.
The Quantitative Decision-making Special Interest Group (QDM SIG) was formed in October 2017. It is a group of statisticians from industry and academia, with experience and interests in statistical methods for quantitative decision-making in drug development. The objectives of the SIG are:
Gianluca Baio (UCL) |
Nicolas Bonnet (Sanofi) |
Sarah Bray (Amgen) |
Alex Carlton (GSK) |
Jacquie Christie (GSK) |
Pierre Colin (Debiopharm) |
Paul Frewer (AstraZeneca) |
Heiko Goette (Merck) |
Martin Johnson (UCB Pharma) |
Kevin Kunzmann (Cambridge University) |
John-Philip Lawo (CSL Behring) |
Jesper Madsen (Novo Nordisk) |
Pavel Mozgunov (Lancaster University) |
Emmanuel Pham (Ipsen) |
Veronique Robert (Servier) |
Oliver Sailer (Boehringer Ingelheim ) |
Gaëlle Saint-Hilary (Saryga) (Chair) |
Guido Thömmes (Grunenthal) |
For further information, or to join the QDM SIG, please contact the chair:
Gaelle Saint-Hilary (Saryga)
gsainthilary@gmail.com
This is a good opportunity to develop your knowledge by thinking through a practical example, practicing how to apply graphics principles, and developing your coding skills.
Dr Francq will discuss the need for analytical methods to deliver unbiased and precise results and talk in detail on confidence, prediction and tolerance intervals work in linear mixed models and the interpretation of statistical results. This will be followed by Q&A.
During this session you will explore how we best execute change within our roles, build your practical understanding of agile tools and techniques, and inspire you to experiment with the new ways of working to deliver your goals.
To understand how the estimand framework changed the development of clinical trials.
Aimed at Statisticians working on the design of Clinical Trials, participants will learn how to use Expected Power, Average Power, Predicted Power, Probability of Success and Assurance, and Bayesian Power when planning clinical trials.
The Apprentice Biostatistician splits their time between working for Parexel and performing studies with a university to obtain a MSc in Statistics over a period of three years.
We are actively looking to expand our team in Wokingham with a permanent position for a Biostatistician / Statistical Programmer.
Are you interested in prevention, diagnosis and treatment of infectious diseases and the application of modern and innovative statistical methods?