How can you generalize an n-of-1 trial's results to another person? Read our newest post to find out! *** ? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
Stats-of-1 | Inference for the Individual
研究服务
San Francisco Bay Area，CA 760 位关注者
Pivot the RCT—one participant at a time.
关于我们
Stats-of-1 is a newsletter and podcast that seeks to improve personalized health by discovering true insights about you—a statistical "population-of-one" (Daza, 2018)—and which of your habits are worth changing. Building on his work at Stanford University, Dr. Eric J. Daza founded Stats-of-1 in 2020. We have since been recognized as health innovators by Forbes Magazine, Fortune Magazine, and the American Statistical Association. We promote the expanded use of individual-focused, single-person or single-unit analytics in health and medicine. This includes the multivariate time series settings of n-of-1 trials, single-case designs and single-subject research, switchback experiments, and personalized artificial intelligence (AI) approaches like person-specific fine-tuning or RAG. 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: statsof1.org/about *** ? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (podcasters.spotify.com/pod/show/n-of-5-minutes). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: statsof1.org/resources/#how-to-cite-this-stats-of-1-resources-webpage)
- 网站
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https://statsof1.org/
Stats-of-1 | Inference for the Individual的外部链接
- 所属行业
- 研究服务
- 规模
- 2-10 人
- 总部
- San Francisco Bay Area，CA
- 类型
- 个体经营
- 创立
- 2020
- 领域
- n-of-1、single case experimental design、statistics、psychology、wearables、causal inference、digital health、behavioral health、clinical psychology、digital medicine、patient generated health data和healthtech
地点
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主要
获取路线
US，CA，San Francisco Bay Area
Stats-of-1 | Inference for the Individual员工
动态
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? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
Data from PubMed show an impressive upward trajectory in the number of articles published on N of 1 trials and single case designs, particularly in the last decade. This surge indicates growing recognition of the value of using these methodologies to identify evidence-based treatments for individual patients. These designs have been applied in several fields, including medicine, pharmacology, complementary medicines, MedTech, medicinal cannabis and much more. Aggregated N of 1 trials and single case experimental designs offer the advantage of being time and cost effective, as well as providing personalised results for each and every participant. If you're conducting clinical research, whether in an academic or industry context, now is the time to explore how this methodology can reduce costs and save time. Book a free consultation call with our world-class experts at N-of-1 Hub to learn how you can incorporate these trial designs into your work!? Link to book for free: https://lnkd.in/gdX3BExZ #personalisedmedicine #nof1 #nof1trials #clinicalresearch #personalisedmedicine #singlecasedesign #medicalinnovation #clinicaltrials #sced
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Congratulations to our founder Dr. Eric J. Daza for winning a 2025 COPSS Emerging Leader Award! ?? *** ? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
Data Science + Biostatistics ◆ Digital Health + Causal Inference + N-of-1 @ Stats-of-1 ◆ Inventor ◆ JEDI @ ASA ◆ FilAm ????????
?? I'm delighted to share that I've won a 2025 COPSS Emerging Leader Award for my work at Stats-of-1 | Inference for the Individual (statsof1.org) and the JEDI Outreach Group (datascijedi.org)! ?? And congratulations to all my fellow winners! ???? ? Ana M. Ortega-Villa | https://lnkd.in/gxVNf5iR — National Institute of Allergy and Infectious Diseases (NIAID) ? Bei Jiang | sites.ualberta.ca/~bei1 — University of Alberta ? Eric J. Daza | ericjdaza.com — Stats-of-1 | Inference for the Individual ? Irina Gaynanova | irinagain.github.io — University of Michigan ? Lucas Janson | https://lnkd.in/gTJRT9XJ — Harvard University ? Lucy D'Agostino McGowan | lucymcgowan.com — Wake Forest University ? Nadja Klein | kiez.ai/nadja-klein — Karlsruhe Institute of Technology (KIT) ? Yize Zhao | yizezhao.com — Yale University Check out how each of us is improving and advancing the profession of statistics and data science here: https://lnkd.in/gGgyj8Tt Every year, the Committee of Presidents of Statistical Societies (COPSS) distributes a number of awards. The purpose of the COPSS Emerging Leader Award For Emerging Leaders in Statistics is “to recognize early career statistical scientists who show evidence of and potential for leadership and who will help shape and strengthen the field. … COPSS recognizes the increasingly important role that early career statistical scientists are playing in shaping the future of the discipline. The award is designed both to call attention to the efforts of these individuals and to provide a mechanism for them to share their vision for the field with each other and the statistical community.” Winning this award will help me champion the important work our methodological community is doing at Stats-of-1 | Inference for the Individual (statsof1.org)—to advance personalized #digitalhealth and medicine through the urgently needed new field of #esametry (https://lnkd.in/gBV9AQ3P). It will also help support our critical work at the JEDI Outreach Group (datascijedi.org) of the American Statistical Association - ASA (amstat.org), as well as the ASA-based #Pinoy-SEA Statisticians community, to build a more inclusive profession for all statisticians and data scientists. I thank Professor Edsel Pena for making me aware of this award, David J Corliss, PhD for guiding me on how to compete for it, my award nominator Professor Amy Herring, and my award letter-of-support writers Professors Hernando Ombao, Kim Sellers, Michael Baiocchi, and Christopher Schmid. "Uncertain times call for certain measurements." — Eric J. Daza, Science: NextGen voices: Advocacy in brief (April 7, 2017)
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? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
Associate Professor Jane Nikles' and Professor Geoff Mitchell’s pioneering book on N of 1 Trials, ‘The Essential Guide to N-of-1 Trials in Health’, represents a significant contribution to the field of personalised medicine and healthcare. With key contributions from world leaders of the field like Gordon Guyatt, Larissa Shamseer, James McGree, Kerrie Mengersen, Christopher Schmid, Paul Scuffham, Hugh Senior and joshua byrnes, the book is a seminal piece of work. As one of the first comprehensive collections of chapters from leading experts in the field, this book lays the foundation for using N of 1 trials and single case designs to rigorously test treatments at the individual patient level. At N-of-1 Hub, we are privileged to have Dr. Nikles as a vital part of our leadership team. Her unparalleled expertise and ground-breaking research has profoundly shaped the field, driving innovation in clinical trial methodology and personalised medicine. Book a consultation if you’re looking to explore or implement N of 1 trials in your research or clinical practice: https://lnkd.in/gdX3BExZ.
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New episode! "Decoding Walking Patterns" with Professor Jaroslaw Harezlak Dr. Harezlak, a biostatistician from Indiana University, delves into the nuanced world of human walking. Dr. Harezlak highlights how walking patterns can reveal significant insights into individual health, such as aging and physical performance. The discussion extends to the realm of competitive sports, exploring how analyzing head impacts in American college football players can lead to more personalized concussion research. This episode invites listeners to rethink how individualized data can revolutionize scientific understanding and health interventions. https://lnkd.in/g7up_eVf *** ? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
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? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
Digital Innovation in Clinical Trials I RWE data and Quality I Startup Advisory& Mentorship
? Exploring Clinical Trials for Rare Diseases in the UAE ? At the 1st edition of the Abu Dhabi Global Health Week, a panel shed light on the UAE's approach to #ClinicalTrial for #RareDiseases. Key topics covered in the session included unique challenges and considerations essential for ensuring the integrity, compliance, and success of such trials: ?? Rigorous Study Design and Protocol Development In the realm of rare diseases, where patient populations are limited, adaptive trial designs and innovative statistical methods like Bayesian approaches play a crucial role in deriving meaningful insights. ?? Enhanced Data Integrity and Management Given the scarcity of data points, meticulous attention to data integrity is paramount. Quality assurance (QA) plays a vital role in validating and securing electronic data capture (EDC) systems to ensure the accuracy and quality of data. ?? Specialized Training and Investigator Expertise Rare disease trials demand specialized knowledge. Thorough training of investigators and site personnel on disease specifics, protocol intricacies, and the unique characteristics of rare patient populations is indispensable for success. ?? Orphan Drug and Regulatory Guidance Many rare disease trials operate under orphan drug programs or specialized regulatory pathways. QA efforts are crucial in ensuring compliance with regulatory requirements, including expedited reviews and specific documentation mandates. By focusing on these critical areas, quality assurance endeavors contribute significantly to addressing the inherent challenges of conducting rare disease clinical trials, thereby upholding safety, ethics, and regulatory compliance throughout the research process.
U.A.E. Research Landscape for Clinical Trials in Rare Diseases | M42
https://www.youtube.com/
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? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
World Top 0.14% Scientist | Unlocking the Power of #Data| #OfficialStatistics, #BigData, #AI, #ML, #DigitalTwins
White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting Authors: Hossein Hassani, Leila Marvian, Manuela Royer-Carenzi, Mohammad Reza Yeganegi, and Nadejda Komendantova Our study challenges conventional approaches and provides practical implications for researchers and practitioners in time series analysis, forecasting, statistics, econometrics, finance, signal processing, ..... Key Highlights: ? A critical examination of white noise assumptions in time series analysis. ? New insights into Hassani's -1/2 theorem and its impact on autocorrelation functions. ? How common diagnostic tests like the Ljung-Box may mislead model selection. ? Empirical evidence showing how misidentified white noise affects forecasting accuracy. Read the full paper here: https://lnkd.in/dbM5itmf More on this soon. We are looking forward to hearing from fellow researchers and industry experts. #TimeSeries #Forecasting #SignalProcessing International Institute for Applied Systems Analysis (IIASA) Digital MDPI
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? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
If personalized medicine is so powerful, why isn’t it standard practice? Because today’s evidence-based medicine is built for populations—not individuals. Clinical trials rely on averages across large groups—but don’t account for personal health baselines. Doctors need hard data to prescribe treatments—personalized medicine often lacks the same level of rigorous testing. The fix? AI-driven N-of-1 trials. AI can run individualized experiments by passively tracking patient data over time, identifying patterns that traditional trials miss. ?? For personalized medicine to go mainstream, it must meet the same scientific standards as population health. AI is how we get there. ?? Full article on why AI needs to reinvent how we test treatments: https://lnkd.in/g8ei56uY (h/t to Eric J. Daza, DrPH, MPS and his excellent website on n-1 experiments! https://statsof1.org/)
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Make sure to follow N-of-1 Hub for content and community! *** ? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)
We saw a real whitespace in the N of 1 Trials and SCED community. There was a genuine dearth of quality introductory content that could help researchers, clinicians, academics and other stakeholders interested in learning more about this space. Working on this insight, N-of-1 Hub is proud to launch a new article series, backed by quality research papers and illustrations to assist and promote learning in this exciting space. The series has an educational focus with an aim to dispel common myths and misconceptions To check out our first few articles, simply click below: https://lnkd.in/gZR-9DpW
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MRTs are very close cousins to n-of-1 and single-case approaches. Consider attending this webinar! (h/t Himel Mallick, PhD, FASA for sharing) "Mobile health (mHealth) – or more broadly, digital health – interventions (e.g., motivational text-messages or nudges to promote healthy behaviors) are becoming increasingly common in tandem with advances in mobile and wearable sensor technologies. In this talk, we will discuss an innovative trial design arising in mHealth, namely, the micro-randomized trial (MRT) that involves sequential, within-person randomization over many instances. The basic MRT design can be further improved to make it adaptive, thereby enabling it to learn from accumulated data as the trial progresses. This is appealing from an ethical perspective since the adaptive learning tends to make better interventions available to the trial participants. Adaptive learning in such trial designs is often operationalized via short-horizon Reinforcement Learning algorithms or contextual bandit algorithms. Specifically, we will discuss the role of a particular algorithm called Thompson sampling in designing adaptive MRTs. Theoretical as well as simulation results will be shown to validate the proposed approach. mHealth trials from the USA and the UK will be discussed as case studies." Speaker: Professor Bibhas Chakraborty *** ? Subscribe to statsof1.org for more n-of-1 posts and podcast episodes (https://lnkd.in/gtkb3WjV). ? ?? N-of-1 / SCD resources (papers, links, etc.)—and how to add your own: statsof1.org/resources ?? (How to cite our resources page: https://lnkd.in/g3yHwXP6)