The Effective Statistician - in association with PSI

Everybody talks about AI, but where are the actual use cases? In the episode today, I'm talking with Dooti Roy about AiCure. AiCure uses an easy-to-use, proprietary AI platform to directly engage and provide support to patients via smartphones to deliver meaningful, high-quality data around patient behavior.

As the pandemic continues to affect the community’s ability to meet in-person, virtual conferences adapt and develop to create space for companies. Now, there is much more emphasis on virtual settings, and there are many new tools available to improve the virtual conference experience.

Are you a master's student or just graduated from a university? What is the Graduate Training Programme? How is the training conducted? What happens after the programme? Veramed's graduate training programme aims to smooth the transition from graduate to effective member of a clinical biostatistics team. The comprehensive 12 week syllabus equips you with relevant skills and knowledge so that by the end of the training programme you will feel prepared for your new role as a Statistician or Programmer. As well as in depth technical training, you will get an overview of the industry and a range of soft skills to help you manage projects, communicate with clients and follow specific processes. Even if you have some technical experience, our comprehensive programme ensures that any potential knowledge gaps are addressed. As the programme progresses you will take on more project work and client-specific training, and by the end of the 12 weeks you will have sufficient skills to work on client projects.

For today's episode, Qiqi and I talk about BI-UConn Summer Academy, an initiative we started 3 years ago to help students understand and learn the world of clinical development better and bring them networking opportunities. This hybrid academy is open to both UCOnn students and students outside of UConn. It's sponsored by Boehringer Ingelheim.

Do you have a great idea you want to move forward and you need others to buy in? Maybe you want to improve a process or implement a new analysis approach. Your business partner might be your study team or your supervisor. Whenever, we want to change something, we usually need others to agree into the next steps.

Aiden has first worked on simulations during studying statistics to understand which sample sizes lead to sufficient performance of statistics, which are only asymptotically normal. It helped him in many situations, in which it was difficult to tackle a problem analytically. Simulations help us understand very complex situations, and the development of new treatments is surely a very complex topic.

We designed this program for statisticians and data scientist to strengthen your leadership skills so you can maximize your impact at work even if you don’t have direct reports. The Effective Statistician Leadership Program, a modular program of self-learning parts and moderated small group discussions, helps all statisticians and data scientists. It especially takes into account the needs of pharmaceutical statisticians, but the concepts will apply to any data scientist. It aims at all levels of statisticians and helps both junior statisticians without management responsibilities and experienced statisticians leading teams. We believe all data scientists and statisticians can be leaders. Check out and learn more about the leadership program here: https://theeffectivestatistician.com/the-effective-statistician-leadership-program/

Clubhouse is a new social media platform that is audio only and only works on iOS or iPhones for now, but it will be available for Android phones in 5 months. Just like in any other social media platform, you can also grow your network here and speak with each other. You can only join a Clubhouse room if you receive an invitation. So, head over to LinkedIn and follow me to get the notification posts and create a LinkedIn post telling that you want to take part in the Clubhouse event and tag me. The room will be open on a weekly basis at 3pm CET to talk about the latest podcast episodes and how to be an effective statistician and data scientist. See you there!

Do you sometimes feel that you disrupt your own happiness and success? Are you overworked to make sense of yourself? Do your emotions often control you? Stuart and I got a recommendation to read a book entitled "The Chimp Paradox: The Acclaimed Mind Management". This book is an incredibly powerful mind management model that can help you become a happy, confident, healthier, and more successful person.

In today's episode, we're talking with a niche part of clinical research many statisticians never get actively involved in: DMCs. David Kerr comes with a deep knowledge and long experience in this setting. We'll speak about: What is a DMC? What is the role of a DMC statistician? What are the best skills and traits of the DMC statistician

The knowledge about the bias variance trade off is very important for you as a statistician as it comes across your work - especially exploratory work - all the time. Taking care about it will help you avoid problems of over- or underfitting your models.

Jenny has encountered several highly competent people throughout her career who have admitted that they entered one path or another based on certain assumptions that were not entirely correct. Further, she has talked with interns about their future career interests and she sees them teetering on the edges of some same fallacies. It’s all fun and science until you have to get a job. As you will make this decision at some point, Jenny wants to give you a few key points to consider when evaluating potential statistics / data science careers in drug development and healthcare.

The COVID-19 pandemic has put pharmaceutical research firmly into the spotlight, with the urgent need to develop new therapies, tests, and vaccines. For those outside the industry, hearing announcements in the mainstream media, it is not always easy to understand the intensity of the work and collaboration that fuels game-changing new developments. However, we know that there are thousands of ‘unsung heroes’ around the world, working in different capacities on different clinical trials to make the breakthrough. It has been a herculean collective effort.

Should we oversimplify statistics, or should managers learn more about statistics? If you've been working as a statistician for a while, you know that you have to keep it simple if you want managers to understand you. Of course, I speak about those managers not being statisticians themselves. There are a lot of ways to explain statistical concepts to them, but this adds time to the presentation. Sometimes there won't even be a presentation, and all you have is sending the report via email. From reading, from my experience, and from talking to other experienced statisticians, I have distilled the knowledge about this challenge into 5 steps.

Outside of statistics departments, we are often seen as tactical and operational implementers. This branding makes it hard for statisticians to be included in strategic discussions. This limits our ability to influence the organizations and projects. It can even lead to entire departments being outsourced or not appropriately funded because of this terrible reputation. I'm long on a journey to fight against this branding. This journey also requires us statisticians to learn about thinking and acting strategically.

Our job as statisticians focuses primarily on the analysis and communication of uncertainty in its many aspects. For this episode, I think of uncertainty as the variability in the population we are studying, the uncertainty around estimates, or the model uncertainty, which we might capture via looking into various models.

What is change management? Is it only something for big corporate initiatives or does it also apply to smaller changes? Why does it require so much consideration? What's hard about change? Change management is something I never thought about being interesting for statisticians, but recently, I needed to dive in to this frequently. I learned that this helps me when creating new designs or processes as it answers lots of questions about getting from an idea to an implementation.

Knowledge sharing is close to my heart and Nelson, who is a very knowledgeable statistician, has shared a lot of articles in LinkedIn and on his website. Nelson has always been keen to learn from others and share that knowledge broadly, so we'll be exploring similarities and differences in how he's seen that be achieved in different circumstances.

Do you want to review a data visualization effectively? Do you want to provide your organization with a simple tool to improve your data visualizations? Do you need a checklist for yourself to make sure you covered everything for your data visualization? This episode is for you!

Do you want to review a data visualization effectively? Do you want to provide your organization with a simple tool to improve your data visualizations? Do you need a checklist for yourself to make sure you covered everything for your data visualization? This episode is for you!

Principal stratification used to play a role only in observational research but at least since the addendum of the ICH E9 guideline, this approach to causal inference became a hot topic.

Yves and I have worked together in various roles. Over time, he became more interested in becoming a statistician and I helped him to change his career path in this direction.

Today, we are talking about Taylor Swift and visualizations. Does it seem like a very unreasonable thing? I thought so as well but then I read this interesting LinkedIn post where I laughed hard but it really made sense!

What's in it for statisticians and data scientists? Design thinking is an interesting topic and is becoming more popular these days. I found out about it on LinkedIn and it's where I met Victoria.

What do you do if you need something from someone at work, but - You have never talked to this person ever before - This person doesn’t know you - The person is very protective about the thing you need - You have only 15 minutes to convince her

Stephen is a really interesting person. He is the author of The Art of Action and has a background in consulting and history. Based on this knowledge, he wrote a couple of books about history and leadership. In terms of leadership, there's an area that overlooked usually from the business. However, business can learn a lot from this area. I'm talking about the military space as armies were the biggest organizations needing strong leadership for thousands of years.

How does understanding the bigger picture helps you to be more productive and to be more influential at work? How can this help you sell your work to your supervisors? How can you fit your work with others work? How can you easily understand where others are coming from? Throughout the leadership program, this topic comes up again and again. We spend quite a lot of time talking about how you can better understand the bigger picture.

If you enjoyed the last book review, you'll surely enjoy this one as well. This is much more practical than the last one. Getting to Yes is a very fundamental book that everybody should read. It was fundamental for me early in my career as it helped me through many negotiations throughout my career.

Do you feel overwhelmed by all the tasks? Do you think you are missing to get the big things done as you are drowning in day-to-day work? Are you frustrated about going home in the evenings feeling like you have not accomplished what you wanted?

Why do we need to innovate? What are the drivers for innovation? How much time would you invest in something if it made an awful task more bearable? I really enjoyed this interview with Mike as we talked about his award-winning presentation.

Napoleon Hill is an interesting author and quite controversial but still good content to reflect upon. In this episode, I want to reflect on: Why people fail in their careers? What hinders us from getting to the career goal set we have? How can we avoid doing the same thing in our own life?

Do you currently run an initiative? Do you want to get support or budget for an initiative? Do you want to change the design or analyses of a study? Do you need to run it past a committee or a senior person? In this episode, I talk about the 4 important advice if you want to engage with key people in your organization

Today, I am talking about a topic that is very close to my heart. I want us, statisticians, to have an impact. I truly believe that if we make better decisions in our day-to-day jobs in our companies and organizations, then we can truly have a much bigger impact on the overall success of these organizations.

Why do you need personal leadership principles? How can you refine and reflect them? What kind of leader do you want to be? Is it possible to be a leader even without a title? I will talk about personal leadership today and this is not being a leader by position, but by principle.

To give you an update, I'll be sharing with you what I have learned from the past year about visualization as I worked a lot of these - the exploratory and explanatory visualization.

What are typical meetings you would be invited to as a statistician? - Study meeting - Project meetings - Team meetings

What can we do about indirect comparisons to make it better and more efficient rather than using the usual technique? What are the indirect comparisons in terms of the efficacy of different drugs? What experiences have you had when the type of one-to-one approach is better?

How are safety analyses different from efficacy analyses? What does validation and quality control mean for interactive visualization? Over recent years, a lot of interesting things happened around safety analyses and visualization. They help us to better understand our safety data and detect safety signals. Wei and colleagues have recently published an article about these topics.

Have you ever thought of having an additional or changing career? What are the things you must prepare for when considering this? Today, we interview Lucy on how can statisticians create an impact beyond statistics. Lucy has a very inspiring career, and she has started as a statistician and got further responsibilities.

For your career, have you ever thought about what mindset you should adapt to? What do you think marks a “successful” career? What will help you understand in which direction your career should go? Diana Stuart, who is a Senior Manager in programming, shares with us her thoughts, lessons, and her vast experience in this field and what we can do to create a robust career with all the surrounding changes.

Given the pandemic, this episode comes timely as it's a challenge to manage time while working at home. But even after the pandemic, this challenge of getting most out of your time will not end.

Were there times you think about creating something bigger than what you currently have? Are you equipped and confident enough to start implementing strategies and plans for future service enhancement?

Imagine you need to choose a comparator for a head-to-head study. How do we usually approach it? - Debate - Meetings - More meetings with other stakeholders - Creating a slide deck - Revising the slide deck - Getting into time pressure - Getting conflicting feedback - Let’s just make a recommendation and find the data that supports this

Have you been sitting through boring presentations? Have you felt that the presenter lost the audience in seconds? Have you found yourself after a presentation thinking - so what? When you are presenting, you don't want the audience to feel this way. But how can you deliver a knock-out presentation and wow the audience?

As statisticians, we often need to bring terrible news to the team. We’re the first to know, that a study didn’t reach the primary endpoint, or that safety analyses showed some new signals, or that some analyses contained mistakes, that need to be corrected. How do you deal with such situations?

What are win-win situations for you? How to create such win-win situations? Upon observing on our daily business, however, we have the tendency to view situations not as win-win but rather as win-lose. Is it really possible to have such kind of situation?

Are you working long hours? How do you manage your time? Do you know how to say no? How do you manage expectations? We want to achieve our goals and be productive at the same time, i.e. we want to accomplish a lot of things during the day. But is it really effective to work long hours?

How do you create effective data visualization? How do you effectively understand and communicate your data? This episode helps you to explore different perspectives and approaches to create more effective visualizations. Andy and Eva from MakeoverMonday offer inspiration and a dose of perspective for those who communicate data.