ERIC J. DAZA
I strive to advance the science of individual well-being by bridging and communicating statistical concepts with precision and empathy.
I'm a biostatistical health data scientist in digital health with 18+ years of experience in biostatistics and health research.
I created and edit Stats-of-1, a blog for innovating statistical study design and analysis methods for individual-focused digital health.
(photo by Adam Chapin Photography)
"Uncertain times call for certain measurements." (Science, Apr 2017)
"Significance of evidence is not evidence of significance." (Towards Data Science, Jun 2021)
I strive to coordinate efforts to innovate, refine, and implement statistical study design and analysis practices that strengthen the scientific, regulatory, and ethical rigor of health promotion and disease prevention using digital tools and data. To do so, I use my natural instincts to find connections across different practice areas, identify underlying concepts shared by distinct technical disciplines and philosophies, and highlight similarities among various personal histories and experiences. I communicate my findings through metaphor and wordplay punexpectedly often.
Dr. Eric J. Daza is a health data scientist at Evidation Health, a digital health company. He has worked for 18+ years in both industry and academia as a biostatistician and data scientist, in pharma clinical trials, survey sampling, nutrition, maternal/child health, global/international health, health promotion & disease prevention, healthtech, digital health, and behavioral medicine.
Daza introduced the average period treatment effect (APTE) n-of-1 counterfactual framework for understanding each person’s own health causes and effects using their own self-tracked, wearable-device, sensor, or app data. He also created and edits Stats-of-1, a health statistics blog focused on digital within-individual statistical designs or methods (WISDOM), and is an early Expert Member of the International Collaborative Network for N-of-1 Clinical Trials and Single-Case Experimental Designs.
As a privileged middle-class Brown Asian immigrant, Eric Jay earned both his BA in Neurobiology / Cognitive Studies and MPS in Applied Statistics at Cornell University, followed by his DrPH in Biostatistics at the University of North Carolina at Chapel Hill. He then trained as a postdoc at the Stanford Prevention Research Center. He is also Jesuit-trained.
(photo by Adam Chapin Photography)
(Barong Tagalog by Nostalgia Barong at Saya)
I'm a statistician.
Statistics isn't a set of tools and theories for me. It's an entire philosophy, a way of understanding the world, a fundamental framework that constantly delights and surprises me by revealing deep connections across fields and phenomena.
It is a way of life.
Please know that when I give you statistical feedback or criticism, it is from this deep place of respect for my field, for my calling. And it is also from my deep commitment to want you to succeed.
I'm trying to help: Not police you as a gatekeeper of knowledge and terminology, but help you change intuitive but bad analytic habits as a fellow player-coach.
Even I occasionally make these mistakes, despite my deep training. Human intuition and habit can be a very hard thing to recognize and change.
I don't always get it right, but I'm trying. Please tell me when I mess up, so I can change my own behavior in a way that better helps our whole team succeed. Thank you for your help and feedback.
(Thank you to Adrian Olszewski for recognizing that this missive was in essence a manifesto.)