• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar

The Effective Statistician

The Effective Statistician

    Enabling Statisticians to Lead
through Innovation and Excellence

Search The Effective Statistician

  • Free webinar: 3 Actionable Ideas To Improve Your Presentations Right Now
  • NEW: The Effective Statistician Leadership Program
  • Start here!
    • Recording available: Flatten the curve – learnings from COVID-19 visualizations to better explore and communicate your data
    • Recording available: It’s not enough to be right!
  • Podcast
    • PSI CALC Podcasts
  • Free resources on visualization
  • Free resources on influencing
  • Join The Effective Statistician LinkedIn group
  • Quick tips to be more effective
  • Legal disclosure – about us
    • Datenschutzerklärung – sorry, still in German…
You are here: Home / Innovation / A deep dive into principal stratification and causal inference

A deep dive into principal stratification and causal inference

By Reine Escalona on 2020-11-17 0

A deep dive into principal stratification and causal inference
  • share 
  • tweet  
  • share  
  • share 
  • save  

Interview with Björn Bornkamp and Kaspar Rufibach

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.

In this episode, I talk with 2 experts from Novartis and Roche. We cover the following questions:

  • What is Principal Stratification?
  • How would you describe principal stratification to a non-statistician?
  • Where do you see the benefits of this estimand compared to the other typical strategies?
  • Which critique points do are usually raised against this approach?
  • How do you implement/calculate corresponding estimates for this estimand?
  • What references would you recommend for further reading?

Björn and Kaspar recommend the following very useful references:

References:

  • Books:
    • Introduction into potential outcomes and causal inference: https://www.cambridge.org/core/books/causal-inference-for-statistics-social-and-biomedical-sciences/71126BE90C58F1A431FE9B2DD07938AB
    • Hernan and Robins: https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ 
    • Pearl, the book of why: https://www.amazon.de/Book-Why-Science-Cause-Effect/dp/046509760X
  • Papers:
    • Paper draft: https://arxiv.org/abs/2008.05406 with markdown: https://oncoestimand.github.io/princ_strat_drug_dev/princ_strat_example.html and github: https://github.com/oncoestimand/princ_strat_drug_dev
    • Magnusson et al (Siponimod Beispiel): https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8333 and the corresponding EPAR: https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-evaluation-anticancer-medicinal-products-man-revision-5_en.pdf
  • Oncology estimand working group: http://www.oncoestimand.org/ 

Kaspar Rufibach

Expert Statistical Scientist at Roche Biostatistics

Kaspar Rufibach is an Expert Statistical Scientist in Roche’s Methods, Collaboration, and Outreach group and located in Basel.

He does methodological research, provides consulting to Roche statisticians and broader project teams, gives biostatistics trainings for statisticians and non-statisticians in- and externally, mentors students, and interacts with external partners in industry, regulatory agencies, and the academic community in various working groups and collaborations.

He has co-founded and co-leads the European special interest group “Estimands in oncology” (sponsored by PSI and EFSPI, which also has the status as an ASA scientific working group, a subsection of the ASA biopharmaceutical section) that currently has 39 members representing 23 companies, 3 continents, and several Health Authorities. The group works on various topics around estimands in oncology.

Kaspar’s research interests are methods to optimize study designs, advanced survival analysis, probability of success, estimands and causal inference, estimation of treatment effects in subgroups, and general nonparametric statistics. Before joining Roche, Kaspar received training and worked as a statistician at the Universities of Bern, Stanford, and Zurich.

More on the oncology estimand WG: http://www.oncoestimand.org
More on Kaspar: http://www.kasparrufibach.ch

Bjorn Bornkamp

Statistical Methodologist at Novartis

Björn Bornkamp works in the Statistical Methodology Group at Novartis in Basel, where he provides consulting to statisticians and clinical teams on topics related to dose-finding studies, subgroup analyses, Bayesian statistics as well as estimands and causal inference.

Never miss an episode of The Effective Statistician

Join hundreds of your peers and subscribe to get our latest updates by email!

Get the shownotes of our podcast episodes plus tips and tricks to increase your impact at work to boost your career!

Success! Now check your email to confirm your subscription.

There was an error submitting your subscription. Please try again.

We won't send you spam. Unsubscribe at any time. Powered by ConvertKit
  • share 
  • tweet  
  • share  
  • share 
  • save  

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Primary Sidebar

Join the PSI newsletter here!

Categories

  • Excellence
  • Innovation
  • Knowledge
  • Leadership
  • PSI Calc Podcast

Recent Posts

  • 5 steps to present successfully to upper management about complex stats (and everything else)!
  • Do you want to think and act more strategically?
  • How to best visualize uncertainty
  • What you should know about change management
  • Knowledge sharing and what it means for you

Archives

  • January 2021
  • December 2020
  • November 2020
  • October 2020
  • September 2020
  • August 2020
  • July 2020
  • June 2020
  • May 2020
  • April 2020
  • March 2020
  • February 2020
  • January 2020
  • December 2019
  • November 2019
  • October 2019
  • September 2019
  • August 2019
  • July 2019
  • June 2019
  • May 2019
  • April 2019
  • March 2019
  • February 2019
  • January 2019
  • December 2018
  • November 2018
  • October 2018
  • September 2018
  • August 2018
  • July 2018
  • June 2018
  • May 2018
  • April 2018
  • March 2018

The podcast is run in association with PSI

Copyright © 2021 · Smart Passive Income Pro on Genesis Framework · WordPress · Log in