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Innovative Approaches in Comparative Effectiveness Research

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Join us for an exclusive webinar tailored for quantitative scientists in the pharmaceutical industry, including RWE scientists, statisticians, data scientists, and epidemiologists. Led by renowned expert Thomas Debray, this session will offer an introduction to cutting-edge knowledge and innovative methodologies for addressing complex challenges in comparative effectiveness research.

Navigating New Teams: Building Trust and Avoiding Pitfalls

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In this episode, I tackle an important question:
How can you effectively integrate into a new team?

Drawing from my own experiences and recent discussions in the Effective Statistician Leadership Program, I explore common pitfalls and strategies for new team members.

Have you ever wondered why it’s crucial to build trust and understand team dynamics before introducing innovative ideas?

Today, I emphasize the significance of these initial steps. Through relatable anecdotes and practical advice, I aim to help statisticians and professionals transition smoothly into new roles and foster successful team collaborations.

Tune in to learn how to avoid mistakes that can hinder your integration and use the initial period to establish strong relationships and a positive team presence.

Weiterlesen …

In this episode, I tackle an important question:
How can you effectively integrate into a new team?

Drawing from my own experiences and recent discussions in the Effective Statistician Leadership Program, I explore common pitfalls and strategies for new team members.

Have you ever wondered why it’s crucial to build trust and understand team dynamics before introducing innovative ideas?

Today, I emphasize the significance of these initial steps. Through relatable anecdotes and practical advice, I aim to help statisticians and professionals transition smoothly into new roles and foster successful team collaborations.

Tune in to learn how to avoid mistakes that can hinder your integration and use the initial period to establish strong relationships and a positive team presence.

Weiterlesen …

Dr. Alexander Schacht

All Episodes

In this episode, I tackle an important question:
How can you effectively integrate into a new team?

Drawing from my own experiences and recent discussions in the Effective Statistician Leadership Program, I explore common pitfalls and strategies for new team members.

Have you ever wondered why it’s crucial to build trust and understand team dynamics before introducing innovative ideas?

Today, I emphasize the significance of these initial steps. Through relatable anecdotes and practical advice, I aim to help statisticians and professionals transition smoothly into new roles and foster successful team collaborations.

Tune in to learn how to avoid mistakes that can hinder your integration and use the initial period to establish strong relationships and a positive team presence.

Weiterlesen …

The FAIRification Of Research In Real-World Evidence: A Practical Introduction To Reproducible Analytic Workflows Using Git And R

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Picture shows: The FAIRification Of Research In Real-World Evidence: A Practical Introduction To Reproducible Analytic Workflows Using Git And R

How can you ensure your data and analytic workflows are reproducible and transparent?

What are the FAIR principles, and why are they crucial for real-world evidence research?

How did a pharmacist and epidemiologist become an expert in real-world data analytics?

In this episode, we explore the practicalities of creating reproducible analytic workflows using Git and R with our special guest, Janick Weberpals. As an instructor in medicine at Brigham and Women’s Hospital and Harvard Medical School, Janick shares his journey from pharmacist and epidemiologist to an expert in real-world data analytics and methodology.

He highlights the critical importance of reproducibility in statistical programming and explains how the FAIR principles—making data and code Findable, Accessible, Interoperable, and Reproducible—can transform research practices.

This episode is a must-listen for anyone involved in real-world evidence research, offering hands-on insights and step-by-step guidance to ensure your work is robust and transparent.

Tune in to learn how to harness the power of Git and R for your own projects, ensuring that your data and results are both reliable and reproducible.

Weiterlesen …

How can you ensure your data and analytic workflows are reproducible and transparent?

What are the FAIR principles, and why are they crucial for real-world evidence research?

How did a pharmacist and epidemiologist become an expert in real-world data analytics?

In this episode, we explore the practicalities of creating reproducible analytic workflows using Git and R with our special guest, Janick Weberpals. As an instructor in medicine at Brigham and Women’s Hospital and Harvard Medical School, Janick shares his journey from pharmacist and epidemiologist to an expert in real-world data analytics and methodology.

He highlights the critical importance of reproducibility in statistical programming and explains how the FAIR principles—making data and code Findable, Accessible, Interoperable, and Reproducible—can transform research practices.

This episode is a must-listen for anyone involved in real-world evidence research, offering hands-on insights and step-by-step guidance to ensure your work is robust and transparent.

Tune in to learn how to harness the power of Git and R for your own projects, ensuring that your data and results are both reliable and reproducible.

Weiterlesen …

How can you ensure your data and analytic workflows are reproducible and transparent?

What are the FAIR principles, and why are they crucial for real-world evidence research?

How did a pharmacist and epidemiologist become an expert in real-world data analytics?

In this episode, we explore the practicalities of creating reproducible analytic workflows using Git and R with our special guest, Janick Weberpals. As an instructor in medicine at Brigham and Women’s Hospital and Harvard Medical School, Janick shares his journey from pharmacist and epidemiologist to an expert in real-world data analytics and methodology.

He highlights the critical importance of reproducibility in statistical programming and explains how the FAIR principles—making data and code Findable, Accessible, Interoperable, and Reproducible—can transform research practices.

This episode is a must-listen for anyone involved in real-world evidence research, offering hands-on insights and step-by-step guidance to ensure your work is robust and transparent.

Tune in to learn how to harness the power of Git and R for your own projects, ensuring that your data and results are both reliable and reproducible.

Weiterlesen …

Linear mixed models – a refresher and introduction

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Together with Paolo, We kick off by revisiting the basics of linear models and why they form such a crucial foundation in data analysis. From there, we delve into the fascinating history of linear mixed effects models, tracing their development back to the early ’80s with Lerder Rubin’s influential work.

The 4+1 Phases of Learning

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I am eager to navigate the “4+1 phases of learning” with you today. This topic, central to our leadership course, particularly targets supervisors but resonates with everyone in a professional setting.