Overview
Join us for our next COPSS-NISS Leadership Webinar: Leadership in Esametry: Within-Individual Statistics of N-of-1 Trials and Single-Case Designs. Over many decades, various aspects of quantitative idiography have been developed in a variety of fields—with different areas of application, and in different academic, scientific, and clinical traditions. Modern digital health technology has widened this set of disparate fields even more. We, the quantitative specialists all interested in developing statistical methods for a single individual, are scattered far and wide across these many areas. For these reasons, I felt that having one name would help unify our disjointed community. This is how I decided to coin the term “esametry” (pronounced “ee-sa-met-ree”). It was inspired by “idiography” and “biometry”, and derived from “isa” (pronounced “ee-SA”), the Tagalog Filipino word for “one”. From my newsletter, Stats-of-1:
Esametry is the application of statistics to a single person, individual, or unit (Daza, Matias, and Schneider, 2025). Think of how econometrics, psychometrics, and biostatistics are the respective applications of statistics to economics, psychological measurement, and clinical trials and population health. Esametry is the collective set of quantitative idiography (i.e., individualized/personalized) approaches—the latter being a term coined in 2013 by Dr. Yuichi Shoda and others—particularly for digital health. The goal of esametry is to infer true average relationships across time for a “population-of-one” (Daza, 2018).
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Speakers
Christopher H. Schmid, PhD, Professor of Biostatistics and founding member of the Center for Evidence Synthesis in Health, School of Public Health, Brown University
Mariola Moeyaert, PhD, Associate Professor, Department of Educational & Counseling Psychology, School of Education, University at Albany State University of New York
Moderator
Eric J. Daza, DrPH, MPS (he/him/
siya),
Associate Director, Principal Clinical Data Scientist; and Founder and Chief Editor of Stats-of-1
About the Speakers
Christopher H. Schmid, PhD is Professor of Biostatistics and founding member of the Center for Evidence Synthesis in Health in the Brown School of Public Health. He is Fellow of the American Statistical Association (ASA), elected member of the Society for Research Synthesis Methodology, Founding Editor of the journal Research Synthesis Methods, statistical editor for the American Journal of Kidney Diseases and former Chair of the Section on Health Policy Statistics at ASA. He directs the Biostatistics, Epidemiology and Research Design (BERD), Core of Advance-RI Clinical and Translational Research and the Evidence Synthesis Academy, an AHRQ-funded training program in evidence synthesis focusing on comparative effectiveness and patient-centered research directed at mid-career professionals and users of healthcare evidence. His research focuses on methods and applications for meta-analysis, particularly Bayesian methods and software, on predictive models derived from combining data from different sources and on clinical trials, particularly N-of-1 trials, single person multiple crossover studies. He has published extensively on meta-regression and multivariate methods, including network meta-analysis and combining N-of-1 studies. Dr. Schmid also has coauthored a large number of applications in collaboration with medical and public health scientists. He has published in all the leading general medical journals and in many top subspecialty journals as well. Dr. Schmid helped develop Institute of Medicine national standards for systematic reviews. Before moving to Brown, Dr. Schmid was on the faculty of Tufts University School of Medicine from 1992-2012. He served as Director of the Biostatistics Research Center at Tufts Medical Center and as Associate Director of the Clinical and Translational Science program. He directed the Brown Biostatistics Masters Program from 2012-2016. Dr. Schmid holds a PhD in Statistics from Harvard University (1991) and a BA in Mathematics from Haverford College (1983). He consults extensively with government, academia and industry and has served on many data safety monitoring and grant review committees including most recently the AHRQ Health Care Research Training Study Section, the FDA Drug Safety and Risk Management Advisory Committee and the Scientific Advisory Committee of the Cochrane Collaboration. See full profile here: Schmid, Christopher
Dr. Mariola Moeyaert obtained her PhD in Educational Statistics in 2014 from the University of Leuven (Belgium) and worked as a Postdoctoral fellow at the Center of Advanced Study in Education at the City University of New York. She joined the faculty of Educational Psychology and Methodology in the Fall of 2015. Her major research interests and publications are in the field of multilevel analysis, meta-analysis, large-scale data analysis, and interrupted time series. She has (co)authored approximately 82 international publications, for instance in Psychological Methods, Multivariate Behavior Research, Behavior Research Methods, Journal of School Psychology, and School Psychology Quarterly, reporting about developments in Educational research methodology (including several extensive simulation studies) and about applications of statistical models to educational data. Dr. Moeyaert obtained the 2016 Anastasi Dissertation Award Division 5 of the American Psychological Association (innovative quantitative research methods). She is currently conducting research as co-PI on a grant awarded by the Institute of Education Sciences (Grant # R305D240044: “Methods for Investigating Causal Mechanisms in Single-Case Experimental Designs”) and she completed two other IES funded grants as PI (Grant # R305D190022: “Assessing Generalizability and Variability of Single-Case Design Effect Sizes Using Multilevel Modeling Including Moderators”) and co-PI (Grant # R305D15000703: ‘Multilevel modeling of single-subject experimental data: Handling data and design complexities’). See full profile here: Mariola Moeyaert | University at Albany
About the Moderator
Eric J. Daza, DrPH, MPS, (pronouns: he/him/siya) created Stats-of-1, a digital health newsletter for promoting the expanded use of n-of-1 trials, single-case designs, switchback experiments, and other individual-focused (personalized/precision) statistical approaches—for health and medicine in particular. These approaches can truly personalize health insights, diagnosis, and treatment in a way traditional clinical and biomedical statistics—and even many precision medicine, machine learning, and AI approaches—fundamentally cannot. For this innovative work, Dr. Daza was recognized by Forbes Magazine and Fortune Magazine, and by the American Statistical Association. He also won a 2025 COPSS Emerging Leader Award. Daza is also a General Member of the International Collaborative Network for N-of-1 Clinical Trials and Single-Case Experimental Designs (ICN). Daza is a biostatistician and health data scientist. He has worked for 22+ years in industry and academia, in pharma clinical trials, survey sampling, nutrition, maternal/child health, global/international health, health promotion and disease prevention, healthtech, digital health, and behavioral medicine. He works as an Associate Director, Principal Clinical Data Scientist at Boehringer Ingelheim. Daza is the 2025 Chairperson of the Justice, Equity, Diversity, and Inclusion (JEDI) Outreach Group (OG) at the American Statistical Association. In 2022 and 2023, he served as the Professional Development Committee (PDC) Chairperson. He has been an ASA JEDI PDC Member since 2021. Daza earned both his BA in Neurobiology and 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. See full profile here: Eric J. Daza, DrPH, MPS
COPSS (Committee of the Presidents of Statistical Societies) and NISS have come together to organize and host a new webinar series focusing on leadership in statistics and data science. Plan to attend these webinars every month during the academic year! Visit the COPSS-NISS Leadership Series Page for previous webinars.
The COPSS-NISS Leadership Webinar Series is co-organized by the Committee of the Presidents of Statistical Societies (COPSS) Emerging Leaders in Statistics and the National Institute of Statistical Sciences (NISS). The purpose of the webinar series is to promote leadership skills for members of the statistical societies at any stage in their careers. The series features conversations with leaders throughout the discipline, including leaders from major academic and government institutions, and companies. Invited speakers share their leadership stories and answer questions about their experiences. Each webinar is moderated by a member of the COPSS Emerging Leaders in Statistics program.
Access the Full COPSS-NISS Leadership Webinar Series YouTube Playlist | COPSS-NISS Leadership Webinar Series: https://www.youtube.com/playlist?list=PLoRtupvDJTjvFukMcO6NfDr0GvxDsIj81
