The Effective Statistician - in association with PSI

Do you want to be a more effective statistician? Do you have what it takes to be an effective leader in your organisation? Many people think that strong leadership skills are something that statisticians don't have. However, as a statistician, you definitely have a lot to offer an organization. Statisticians often have the skillset required for leadership positions as they can use their questioning and decision-making abilities to help solve issues within an organization. In this webinar, we will discuss how statisticians are in fact very gifted with unique leadership skills that can make them more influential and successful. We identify these skills and discuss how you can leverage them to become a more influential and effective statistician. Listen to this episode now and learn from the following points we discuss:

What are the advantages of being active on LinkedIn? How can you find the right career opportunity on this social site? How can increasing your network attract more opportunities? What kind of content should you post? In today's episode, I am talking about my favorite social media platform, LinkedIn. LinkedIn has helped a lot of professionals not only to meet new people and to broaden their network but also, in discovering new skills, learn new insights, and get motivation. Listen to this now and learn how to maximize the use of your LinkedIn account. I also discuss the following points:

Why is it important for a statistician to take the culture of the first mover advantage on a more personal level? How do the first-mover advantages help the personal and professional growth of a statistician? What does it take to be the first mover? How does being the first mover solve problems early? How do you develop the motivation to be the first mover? In this conversation, we talk about the effective impact of the first-mover advantage. To give a more visual distinction of this strategy, it is more like a chess game where the first mover often decides the direction of the game. In statistics, this attitude offers a more effective sense of understanding what the first move culture is all about. Here are some of the lessons that are presented in this conversation:

How could differences between countries affect the elements that are included in statistical research? How could studies with such a diverse sample from different countries be managed to create a more dependable reference for statistical studies? How do differences of the quality of care that the target population receives impact studies? As statisticians, we need to be able to understand the validity of the outcomes of statistical analysis for different target populations. In this podcast, you will learn ways to tackle this problem: In this podcast, you will learn how this problem could be resolved:

Leadership is one of the most important aspects of any organization, and statistics is no exception. Good leadership can help a field grow and shape the future, while bad leadership can lead to stagnation or even ruin. In this episode, we discuss what leadership means for statisticians, how we develop our own leadership style, and how it helps us continue to move forward in our careers. Join Alun Bedding and me while we answer these questions: What made Alun decide to focus on leadership? What are the advantages of practicing good leadership for statisticians? How to be an effective leader and motivator? How did Alun and I got equipped in training others to be effective leaders? We also talk about the following interesting points:

Are you struggling with your presentations? How does storytelling increase the interest of your listeners? How does audience relatability help in improving the way you are able to connect with them effectively? How does establishing rapport with your audience affect the overall value of your message and how it is going to be used by your target listeners? How can you effectively anchor a message to a visual element through storytelling? In this conversation with Helen, we discuss the importance of storytelling in creating relatable presentations that will have a more personal impact on the listeners. Rapport and connection with the audience are critical to the way a message is received. Here, Helen Packham explains more about this issue. Here are some lessons you can get from this episode:

Does Multi-tasking help or harm you? How could you handle the desire to multitask more effectively? What fallacies about multitasking does the world currently believe? Are there ways to be more productive other than multitasking? How does focus change the way we function in any form of industry? This podcast gives our listeners an idea of what multitasking is, how it has changed the way people work through time, and how it has created more problems than solving issues as expected. The information we share in this podcast will help you become more productive and understand the application of multitasking in a much better light. Here are some lessons we want to impart through this podcast:

In this last part of the leadership series with Gary Sullivan, we talk about the next steps, you can take to work on your leadership skills. We cover the following areas: - Books - Mentoring - Role of supervisors - Podcasts - Mastermind groups - Courses

Indirect comparisons and network-meta analyses play a rising role in our world. A pubmed search provides 240 hits for the term network meta-analysis in 2011. This increased to 3223 in ten years later 2021 – more than 13 times more! There are many problems you can solve using these approaches and statisticians overlook some on a regular basis. Don’t miss out on providing your colleagues with great evidence (and with the ability to learn a lot about this interesting statistical approach). Listen to my short but informative discussion with Daniel Saure as we explore five different cases with which network meta-analyses are extensively affected. Our conversation defines the problem and solutions regarding these three primary cases:

In this second part of the interview with Gary, we speak about the building blocks of leadership without authority from a statistician’s perspective. We cover questions like: Is influence the same as power? What is the role of trust, what are the different elements of trust and how can we improve trust being technical experts? How can we build relationships at work, that help us to influence change? Is influence through relationships only relevant “sideways” or also “upwards” and “downwards”? How do we know with whom we need to invest in building relationships? Is there a way of assessing how good our relationships are?

How does information technology help reduce the statistical margin of mistakes? How does leadership come into play when creating programs designed to effectively manage statistical data? How does open-source culture in informatics development in statistics help in creating innovative technology to increase research validity? Does open-source development change the way statistical validation is treated especially in developing new forms of health treatment? My interview with Coline Zeballos of Roche informatics will give you an idea on how the development of Open-Source culture in developing applications that will help validate data collected for statistical research is actually changing the way medical studies are being completed and applied by pharma companies today. Coline also shared her thoughts about internal leadership in this podcast, which will be useful not only for statisticians but for professionals in other industries as well. Some of the lessons you can get from this podcast include:

What makes persistence one of the most important factors of being a leader? How does persistence among leaders in statistics affect the results of their work? How could persistence translate into understandable and actionable results for the target population? How can a persistent leader bring high value to bringing change to the target population? How does clear vision help leaders develop persistence in reaching their goals? Even in the face of difficult barriers, a persistent leader does not give up. This short but rich conversation between Gary and me introduces the meaning of leadership and how persistence shapes its value. Looking into the examples of Martin Luther King and Earnest Hemingway, this podcast will teach you how history proves that persistence among leaders go a long way in promoting change and development across the globe. Learn from me and Gary as they talk about persistence and how it can make leadership among statisticians more effective as they translate the results of their studies to the target population. Here are some key lessons you can learn from this episode:

The Leadership program is now open and in this bonus episode, we go into some key questions about statisticians and leadership that may help you decide on your next steps. Here are the following key questions:

How do real-world data variables change the overall value of a clinical study? How does clinical study make it to the implementation stage and how is this strengthened through the use of RWEs? How does Real World Evidence validate the data and results that are presented in clinical trials? The extensive existence of Real World Evidence resources is already out there and is ready for utilization in clinical trials. In this second part of the discussion between Josephine and Alexander, we highlight how, from the point of validation to implementation, RWEs work well in strengthening the foundation of every study approved for actual real-life application. Here are some of the key learnings you can gain from this episode:

Getting things done through others is a key part or even the definition of leadership and her clients face often the same situation as statisticians. They need to convince people rather than command them. In this episode, we have our first non-statistician as a guest. Julia has built her own consulting and training company Zestfor. She and her team specialise in developing Training programmes and resources scientifically tailored for technical markets – including Pharmaceutical, IT, and Life. In this episode, we cover the following topics:

What makes a statistician more valuable to an organization? How does a statistician’s work culture differ from working in a large company to working with a smaller organization? Would statisticians be able to bring more value to their work, especially when working with smaller companies? When the term “statistician” comes to mind, it is easy to picture a person who sits for hours behind a desk working with numbers and mathematical analysis. However, there is something more to statisticians than what actually meets the eye. More than just the expectation of a person being a brilliant person who understands numbers better than the average individual. The truth is, statisticians are the ones who have the capacity to bring change to the table, especially because they know what the numbers are telling them. In this episode, Kim and I talk about how statisticians become the big fish in a small pond when they work with smaller organizations. Here are some key learnings you may be interested in as you listen through this episode:

In this podcast episode, we discuss an important part of leadership – proactive behaviour. Or simply put—drive! As a statistician, your day-to-day approach to this topic will build up to long-term success. We discuss various aspects of the drive including:

What are RWEs or Real World Evidence about? How are Real World Evidence used in determining the value of clinical trials on how they are applied in real-life settings? How are RWEs validated and how are they used in actual medical cases as healthcare procedures are applied in hospitals? What variables tend to affect the way RWE data is managed and used as a reference to actual medical developments? How does accurate reporting affect the value of collected RWE data? Clinical trials accomplished to support the development of healthcare industries around the globe are critically defined to the references on how health conditions are diagnosed and treated. In the end, the real target end-users of the medicines and other medical procedures are the patients. Hence, creating a more patient-centered approach in handling clinical trials is an important part of defining the success of one study. One way of making sure that the clinical trials reflect real-world situations is through inculcating Real World Evidences or RWEs. Often, these evidences are garnered through observing samples that are free from the manipulation of the researchers. Through EHRs or Electronic Health Records, statisticians are able to collect data without necessarily influencing the sample population that they have chosen to observe. How does the FDA consider these factors of evidence? Listen to Josephine Wolfram, an expert in RWEs, and me, and learn more about the way the FDA sees the value of RWEs and how this factor affects the overall procedures considered when approving new medicines and medical procedures that are offered for patients to consider. Here are some key takeaways to look forward to when listening to this podcast:

In this episode, we share out ideas and experiences, which mindset sets up statisticians for success. We cover topics around:

How does patient adherence affect the results of clinical trials? Are there ways to improve patient adherence to medication and treatments not only in clinical trials but also in real-life situations? What is the future of the value of clinical trials in terms of inclusive technological innovations? Clinical trials are designed to test whether a medication would be best for the target population. While these approaches are considered critical to healthcare development strategies, their value for applicability still remains dependent on how the participants cooperate with the process of treatment which involves their attitude towards adherence to the trial. In this podcast, join me and Lina as we talk about the most effective ways to get patients to adhere to treatments they are offered in clinical trials. With her background in psychology, Lena’s insight is on point especially when it comes to determining the role of human behavior in terms of determining the applicability of the results garnered from clinical trials. While there are several problems that arise from the lack of patient adherence, this podcast highlights some of the most effective ways that are available today for researchers and statisticians to consider when handling patient-centric clinical trials-therefore ensuring a high rate of patient adherence. Here are some of the important learnings you can get from this episode:

Why would a person working under the rules and purpose of statistics for 30 years want something more than what she has been an expert with for many years? Do you want something more out of your statistician background? What could statisticians offer outside of the field of statistics in healthcare? How does leadership in statistics bring you to embrace more exciting journey outside of statistics? What does passion have to do with making statistics work for statisticians trying out new avenues of opportunities? No matter how boring it may seem to others, statistics is certainly an exciting field for those who enjoy numbers and the analysis of the data collected from samples that are worked on. From the point of collecting data to studying what they mean, statisticians are certainly considered leaders who are able to utilize data to drive change for the benefit of the patients and the general public. But there is more to statistics than simply dealing with the numbers. It gives statisticians a direct connection with the issues giving them a chance to see things more clearly. In this podcast episode on steeping outside of statistics, Alex sits down to connect with Liz Thompson who has a strong 30-year background in statistics to understand why statisticians embrace the option of stepping outside of their expertise in the hope of bringing more value to what they do. In this discussion, Liz presents some of the most distinct reasons as to why a statistician may want to embrace other options of growth in the healthcare industry as an advocate for distinct purposes. Here are the bullets of lessons you will get from this TES podcast episode:

Why should statisticians aim for becoming good leaders? How do you invest in yourself to become a good leader? How does perseverance change the path taken by a leader in the field of statistics? Gary Sullivan and I team up together to discuss the importance of leadership among statisticians. Understanding the basic factors of leadership and how it makes an effective statistician is important for every professional in the field of statistics to master. Statisticians do more than just collect data and analyze the information they have collected. In many ways, statisticians, being the first-hand handlers of the data, also find solutions to problems at a much earlier time compared to other specialists in specific fields. Hence, beyond just relaying the facts, statisticians are also expected to provide first-hand solutions that they think may be capable of resolving the issues they find critical as they go through the data they have collected. This is where leadership comes in. In our discussion, Gary and I exchange thoughts, and experiences and learned lessons through the years and how they can be applied in actual situations that statisticians face at work. Here are some of the important realizations that we gathered during our conversation:

Publications are part of the bigger communication plan which also covers PR, scientific dialog, promotion, training, and internal communications. Writing publications should follow an overall strategy for the compound or therapeutic area. They are necessary for further steps like having promotional material, HTA submissions, scientific/medical dialog, etc. They should not be an afterthought or seen as a pure incentive. In this episode, Jenny Devenport and I talk about these publications as critical part of the scientific process We also cover how creating these helps establishing credibility with various stakeholders. We also discuss the following points:

What is a secondary paper? What is its typical content? Where is the content coming from? A secondary paper is a paper you do once you are done with your primary paper. I've been working on this for a long time and always have fun doing it. Together with Benjamin, we discuss the following points:

Feeling comfortable does not lead to growth. But why do most people stay in their comfort zone? Are your own expectations holding you back? In this episode, I am talking about the reasons why people stay in their comfort zones and always choose the “safe side”. And why choosing this hinders you from your personal and career growth.

I am really passionate about leadership and Claude Petit is also passionate about building leaders and being an effective leader. Together, we will share with you how to become a statistical leader and how to build such an organization. So stay tuned!

What is a pharmacometrician? What does the training of a pharmacometrician look like? In my career, my experience of working with pharmacometricians was very limited because I spent most of my time working more on the later phases; and the contact with people in that space of the industry is not that big, that's why I found this episode really helpful. If you don't have a clue what they do then stay tuned for this episode.

What can go wrong with network meta-analyses? You often have multiple endpoints but these are not collected consistently across all the studies included in the NMA. How do you deal with this? Even with the same variables assessed over studies, they might be collected at different time points. This often has an effect on both efficacy and safety results. What do you do? Your placebo treatment might change over time and consequently your placebo response. Often placebo plays a crucial part in your network, but can you really pool all your placebo arms? The patient population differs between studies and hence between treatments. How do you control this bias? The pool of relevant treatments differs across countries when using network meta-analyses for HTA submissions. Should you adapt your NMA for each country's submission? You’re not submitting all your HTA dossiers at once and thus the literature search needs to be updated repeatedly hence you input data into the NMA. How big are the differences and how long will it take to update everything (and what will it cost?)?

In today's episode, I am the interviewee, and Jenny is the one asking the questions. We are talking about how training in launch and commercialization can be a super weapon, what its role is, and how can this be developed and administered for non-statisticians. We also talk about the following interesting points:

The world has changed, and it will not turn back to what is used to be before the pandemic. This comes on top of other trends, like the increased use of data across all aspects of data. The hunger for talent in the data science space has dramatically increased, and it is not only coming from the Apples, Googles, and Amazons. Other trends are the increase in prices, the shifts in motivations of employees, and the debate about what really makes people join and stay at companies.

I first became aware of these sources for real-world evidence some years ago, and I tried to get an expert on this topic so often, but unfortunately no one would speak with me. Then finally someone agreed when they found out what country my research was being conducted in-the Scandinavian Union! You might be wondering why we need data from such a unique place as Scandinavia? Stay tuned because you'll find out soon enough… This region provides us statisticians everything we could hope: perfect measurements plus high-quality counts.

Is a board of directors essential for everyone? Is it necessary for it to come from within your company? This episode is all about career advise. Together with Heather, we talk about having your personal board of directors and how could this concept help you have a career advancement overtime.

We all need to present frequently and the more you progress with your career the more important the presentations become. Messing these presentations up - especially in front of those responsible for your next promotion - will lead to bad career outcomes.

What are biomarkers, and why is this essential?

Today’s episode is an extract from my interview with Jenn Fenwick, who's also a podcaster like me and we talk about my career and leadership. This is a fun chat where we talk about navigating fear, opening ourselves up to vulnerability and making courageous decisions… oh and Beyonce gets a mention too!

What is extrapolation? How can we use extrapolation in paedriatics? What are the main challenges? Paedriatic research always comes with challenges and understanding paedriatic submission is very important. There's always a lack of treatment in this area. In this episode, you'll understand what you can do to get evidence through extrapolation for the children population.

What are the benefits of including external data in the design and analysis of clinical studies? How does the meta-analytic predictive model (MAP) work? I know you've had this dilemma of either having had the difficulty in collecting data or having too much available and yet irrelevant data while trying to conduct a clinical trial. When is it appropriate to use historical data and when is it appropriate to enroll new patients to collect new data? Today, Gaëlle and I talked about the main objective of using historical data in clinical trials.

Why are we raving about this conference? Why is this the best conference I have been attending to? What are the other activities beside the conference itself? This is a special episode while Benjamin and I talk about the upcoming PSI conference and what you can expect from it. This will be a face to face conference in Gothenburg, Sweden!

The FDA is developing a series of four methodological patient-focused drug development (PFDD) guidance documents to address, in a stepwise manner, how stakeholders can collect and submit patient experience data and other relevant information from patients and caregivers for medical product development and regulatory decision making. In today's episode, we discuss the process with the FDA publishing a timeline of planned public workshops, draft guidance documents and final guidance documents for 4 documents, originally planned to finish in end 2021 and its objective to explore the factors that need to be considered when developing COA-based endpoints.

What is a DIGA? Why is Germany so important for DIGAs? Nowadays, there are a couple of available apps being used in several countries that collect user information, such as heart rate combined with algorithms that calculate certain health risks that the user may be vulnerable to. What differentiates these apps from the apps listed in the DIGA registry? In today's episode, Dr. Stefan Walzer and I discussed the goal of the Digital Health Application.

Why do companies want to develop new patient-reported outcomes? How does the process start when we want to develop a new questionnaire? What are the key areas to look into for understanding the quality of a PRO? What guidelines exist for developing new PROs? In today's episode, Antoine and I answer these questions and more. E.g. we talk about the importance of calibrating the relevance of the existing items in the questionnaire and developing new ones in order to reach more accurate measurements resulting in good PROs.

What is medical affairs? Launch and Lifecycle? How has this area evolved over the last 2 decades? What is the current state across the industry in terms of the role of statistics in this space?

When there is one topic, which is really hot, it's causal inference. I've got in contact with it about 20 years ago when analysing observational studies and when nobody working on clinical trials would consider it. But now - after the introduction of the estimands framework - this becomes part of every statisticians toolkit. Today, we have one of the world leading experts in this field as a guest - Miguel Hernan. I'm talking with him about: How can this help generate and analyze data to identify better strategies for the treatment and prevention of both infectious and noninfectious diseases?

The guest in this episode represents the sponsor of this show – Nigel Howitt – current chair of PSI.

In the modern workplace, conflict has become a difficult topic. After all, conflict is antithetical to teamwork, employee engagement, and a positive company culture. Or is it? "No" is a sign of conflict and many avoid saying it by all means. But... Why is saying no so hard? How do we say no in the right way? When should we say no?

Subgroup analyses in combination with data visualisation is one of the hottest topics I can think about. And it hits us as statisticians during our careers again and again. We need to understand subgroups for efficacy reasons and safety reasons and it's a common question in terms of how consistent your drug works across the different subgroups. It gets even more complicated if you want to review it across multiple studies.

Publishing data is great, but we also want to measure the impact our work has beyond the additional entry in our CVs. During this episode, Mike and I discuss the tools Altmetric and Dimensions. These can help us to understand the reach and influence of clinical and scientific research beyond citations. Based on these, we can track the full journey, from idea to impact. We touch on a number of interesting topics during the interview, including how Altmetric and Dimensions work together in uncovering this journey, but also the insights that can be gleaned from the kind of data the tools provide. ‘I get to sit in the middle of this wonderful web with both Dimensions data and altmetric and I pull the two things together. And together, I can create these translational maps of where research is going from the laboratory through to the hospital and into the broader population.’ - Mike Taylor

We leverage Real World Evidence in many different areas and there's are many different things that can go wrong with this. In today's episode, Rachel and I will discuss the things that we would like to have known before we started working with RWE so stay tuned to avoid mistakes we made in the past.

How do you start your week? Do you just rely on yourself or do you use some tools to organise yourself? learned a lot of productivity hacks from Michael Hyatt. I've listened a lot to his podcasts and I used some of his recommended tools to make my plans work such as the Full Focus Planner which is kind of a calendar and a to-do list together with goal setting tips and more.

There's a lot of community charity works we can all do but there is not a lot of work where we can maximise our impact by using our specific skills as programmers, as statisticians, and as data scientists.