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Activity Number: 85 - Challenging Collaborations and Lessons Learned
Type: Topic-Contributed
Date/Time: Monday, August 9, 2021 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistical Consulting
Abstract #317516
Title: Challenging Collaborations and Lessons Learned
Author(s): Manisha Desai* and Elaine Eisenbeisz* and Kim Love* and Clark Kogan* and NAYAK L POLISSAR*
Companies: Departments of Medicine and Biomedical Data Science Stanford University and OMEGA STATISTICS and K. R. Love QCC and Washington State University and The Mountain-Whisper-Ligtht: Statistics & Data Science
Keywords: Consulting, complex problems, statistical challenges, solutions

Over the course of their careers, statistical consultants invariably encounter a few projects that will always live in their memory due to the great challenges that had to be overcome to complete the projects. These challenges can come in different forms: an analysis with once-in-a-lifetime complexity; an analysis that is next to impossible to explain to a lay audience; a dataset that is intractably large or that needs extraordinary cleaning prior to analysis; an analysis—on a sensitive topic—where confounding and potential bias are very prominent. Lastly, there could be an ethical dilemma with the client or the public. This session presents real examples of these challenges and the important lessons that were learned. The session will be of benefit to anyone who carries out statistical projects with clients or collaborators.

Authors who are presenting talks have a * after their name.

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