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Pivot the RCT—one participant at a time.

Stats-of-1 is a newsletter and podcast that seeks to improve personalized health by promoting the expanded use of n-of-1 trials, single-case designs and single-subject research, switchback experiments, and other individual-focused (personalized/precision) statistical approaches in health and medicine. Building on his work at Stanford University, and inspired by his work with the International Collaborative Network for N-of-1 Trials and Single-Case Designs (ICN), Dr. Eric J. Daza founded Stats-of-1 in 2020 as a statistics-focused educational and advocacy complement to the ICN. We have since been recognized as health innovators by Forbes Magazine, Fortune Magazine, and the American Statistical Association.

We advocate for the expanded use of individual-focused, single-person or single-unit analytics in health promotion, disease prevention, epidemiology, and clinical studies. This includes the multivariate time series settings of the approaches mentioned above, along with personalized artificial intelligence (AI) approaches like person-specific fine-tuning or RAG, and patient-centered approaches in defining the outcomes and endpoints of clinical trials and studies.

Together, these quantitative idiographic approaches comprise the field of esametry (Daza, Matias, and Schneider, 2024), derived from “isa”, pronounced “ee-SA"—the Tagalog Filipino word for “one”. Visit our About page to learn more.

The pancit plot (Daza, 2019; Daza, Wac, and Oppezzo, 2020) above (pronounced “pun-SEAT") is an example of an esametric plot. It is a “longitudinal” graph of a single person’s outcome trajectories per exposure period, drawn by overlaying each per-period trajectory over all periods of measurement. It can aid within-person functional data analysis.

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