Podcast

In this episode, we’ll give you an introduction to risk-based monitoring (RBM) as well as speak about the role of statisticians in this area. Further, we provide you as a study statistician insights into what you need to know about RBM. Finally, we also give some recommendations in terms of further resources to learn from.

This episode helps you to make your training engaging, interesting, and useful. Such training will help you to build your reputation as an expert as well as a great person to work with. It’s an awesome experience for non-statisticians if they have a light-bulb moment while being trained in statistics.

Still capturing and evaluating patient preferences does not belong to the core capabilities of most biostatisticians.

In this episode, we dig into the different aspects of this highly personal decision. Given, that Benjamin went directly into a job, whereas I first finalized my PhD, we also offer our experiences.

Oliver has accrued lots of experience working in different setups over his career and thus can tell about the different strengths and limitations of the set-ups.

Benefit-risk assessments are made by various stakeholders including sponsors, regulators, payers, physicians, and patients throughout the life-cycle of a treatment.

We’ll explore where leadership powers originate, how they shape decision-making, and most importantly, how you can harness them to amplify your influence and effectiveness within your statistical domain.

This episode follows the outline of a webinar, that I presented in 2018 during a PSI webinar. I’m introducing cluster analysis and why you as a statistician need to know about it.

Stephen Ruberg answers these and related questions in today’s episode. Coming from the medical side, he built a business analytics team at Lilly and gave a related keynote presentation at the 2018 PSI conference.

Then this interview with Ursula from Cytel provides you with the relevant answers.