The Effective Statistician - in association with PSI

Interview with Tim Rolfe Click here to get to the homepage of the episode! Risk-based monitoring plays an increasingly important role for clinical trials. Of course, the assessment of the risk is based on statistics. This presents now only interesting career options for statisticians, but also has an impact on the role of statisticians in study teams. 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.

Experiences from many trainings summarized Click here to get to the homepage of the episode! Start with a relevant example Collect questions upfront and track progress of answering them during the training Create regular meetings to engage people Interrupt your presentations with asking questions Use contrasts to show the impact Have a physician first introduce the example study Don’t shy away from speaking to very basic things like p-values Prefer white board over slides Use technology for your advantage in virtual settings Make pre-read easy Collect feedback

Interview with Brett Hauber Click here to get to the homepage of this episode! Ultimately, we work to improve patients lives but traditionally the voice of the patient was not important. However, over the last decades many stakeholders shift to include the patient more in the decision-making process and patients voice their needs and preferences more. Still capturing and evaluating patient preferences does not belong to the core capabilities of most biostatisticians. This episode will help you to understand patient preferences.

What aspects to consider? Click here to get to the homepage of the episode! Are you early in your career and you could still go for a PhD in statistics? Do you wonder, if this pays out short and long-term? Is it worth the money? What are the long-term benefits or are there actually short term benefits as well?

Interview with Oliver Schoenborn-Kellenberger Click here to get to the homepage of the episode! Do you want to change your job? Are you just looking for you first job? Do you consider to work for your own company or as a free-lancer? Then this episode will help you!

Interview with Maria Costa and Shahrul Mt-Isa Click here to access the homepage of the episode! Benefit-risk assessments are made by various stakeholders including sponsors, regulators, payers, physicians, and patients throughout the life-cycle of a treatment. The understanding of data plays a vital role in weighting positive and negative effects of medications. In this episode, we give you an introduction to what benefit-risk (BR) assessment is in order for you to understand your role.

Interview with Kate Taylor – chair of the PSI conference in 2019 Click here to get to the homepage of the episode! In this episode, we talk about how to network how to prepare for the conference how to follow up after the conference As well as some specific topics around the PSI conference itself.

Not all patients are created equal, but are there subgroups that are more homogenous? Click here to get to the homepage of the episode! 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.

Interview with Stephen Ruberg Click here to get to the homepage of the episode! There’s a long tradition of statisticians working on clinical studies as well as other related data, e.g. pre-clinical data and observational data. In the advent of big data and data sciences, there’s a considerable pull from the business side of pharma to employ statistical approaches as well. What does this mean for medical statisticians?

Interview with Ursula Garczarek Click here to get to the homepage of the episode! Do you want to learn where the health sector might be heading in terms of data science? Do you understand the opportunities and barriers in terms of the application of data science? Are you prepared to learn the individual skills needed for these changes? Then this interview with Ursula from Cytel provides you with the relevant answers.