A methodologist at the intersection of design, measurement, and analysis for human-centered research
I develop and improve methods for human-centered research from foundational areas in psychology to applied analytics in business.
My work advances how to design studies, measure constructs, and analyze data, particularly in organizational contexts and digital environments. My work aims to make human-centered science better by bridging rigorous methods with important applications to help ask better questions and make more scientifically valid conclusions.
I believe the quality of our insights depends on the quality of our methods. My work crosses traditional disciplinary boundaries because understanding the human condition requires diverse perspectives. The entire effort is in the data science space, particularly from the psychometric and statistical traditions of framing inferential questions.
My collaborations with substantive researchers help improve research by applying advanced and non-standard methods or developing new methods to more effectively address important research questions. This applied work involves trying to improve the way in which questions are framed, data is collected, and rigorous analysis in ways that yield stronger scientific conclusions. My goal is to make rigorous methods accessible and useful, not just theoretically elegant.
Contact Information
-
Ken Kelley, PhD
Edward F. Sorin Society Professor of IT, Analytics, Operations -
Mendoza College of Business,
University of Notre Dame,
Notre Dame, Indiana 46556 -
KKelley@ND.Edu
nd.edu/~kkelley
574-631-1459
My methodological work centers on research design, particularly the interplay between effect size, confidence intervals, statistical significance, and sample size planning. I developed the Accuracy in Parameter Estimation (AIPE) framework, which shifts focus from statistical power to precision in parameter estimates—operationalized through narrow confidence intervals for parameters of interest. This approach has reshaped how researchers plan studies when their goal is estimation rather than hypothesis testing.
My work extends to psychometrics and structural equation modeling, mediation analysis for understanding causal pathways, and mixed-effects (multilevel and longitudinal) methods. Across these areas, I focus on practical improvements that strengthen researchers' ability to make principled scientific inferences from their data.
Given the growing influence of AI, technology platforms, and digital environments, understanding how these artifacts affect individuals, teams, and organizations has become critical. This focus aligns with the Human-centered Analytics Lab (HAL), which I co-direct with Ahmed Abbasi. HAL transcends traditional disciplinary boundaries, merging psychology, information technology, statistics, and business into an interdisciplinary approach for addressing complex problems in the digital age.
My work has been cited around 20,000 times (h-index: 48; i10-index: 84), and since 2020, I've been recognized among the "Top 2% of Scientists Worldwide" in Social Science Methods by Elsevier's Science-wide Author Database. I am a Fellow of both the Association for Psychological Science, the American Psychological Association, and an elected member of the Society of Multivariate Experimental Psychology, which is an honor limited to 65 active members.
Statistical computing is fundamental to my approach. I believe methods should be usable, not merely readable, so I develop R packages that translate theoretical advances into practical tools. My MBESS package has been downloaded over 870,000 times, and BUCCS over 46,000 times, according to analyses by Data Science Meta. The companion website DesigningExperiments.com for our textbook Designing Experiments and Analyzing Data (Maxwell, Delaney, & Kelley, 2018; 4th ed. forthcoming 2026) attracts substantial traffic, particularly for its interactive Shiny apps that make complex methods accessible to practitioners.
As Co-director of the Human-Centered Analytics Lab (HAL) with Ahmed Abbasi, I lead an interdisciplinary research environment that rigorously examines how people interact with technology in our increasingly digital world. HAL transcends traditional academic silos by integrating computer science, statistics, psychology, and information systems. Our "T-shaped" structure combines broad theoretical foundations with deep methodological expertise, enabling us to develop and apply rigorous analytical methods that address real-world challenges at the intersection of technology and human behavior.
An important application of my work is business analytics, where psychological, behavioral, and social data are often combined to model or explain some aspect of business or organizations
I regard business analytics as the translational arm of data science in the context of business, where my work is concerned most often with the person in organizations.
Given the importance of AI, technology platforms, and the digital space broadly considered, the way in which these impact persons is of growing importance. This area aligns with the Human-centered Analytics Lab(HAL), where I am co-director with Ahmed Abbasi. HAL is a lab like no other I am familiar with, in which disciplinary boundaries do not apply and multiple fields usually isolated from one another are merged into an interdisciplinary mash-up of psychology, information technology, statistics, and business.
Consider a PhD at Notre Dame
Consider the doctoral minor in Advanced Quantitative Social Science.
Research
My research program has been about making improvements to the scientific methods used in the social and behavioral sciences.
Teaching
I teach or have taught in a variety of business statistics / business analytics / quantitative analysis courses in most of our programs over the years.
I am now focused on teaching Human-centered Analytics: Design, Measurement, Analysis for our doctoral programs, which also serves the minor in Advanced Quantitative Social Science.
Methods and Applications
In addition to research design (sample size planning, improving statistical power, sequential estimation) and statistical analysis (e.g., effect size estimation, confidence interval formation), contributions I have been involved in concern mediation models, in which causal pathways are considered to explain process, and longitudinal methods (analysis of change, repeated measures), in which the same individuals are measured over time in an effort to understand intraindividual change and change in interindividual differences. Recent work considers machine learning methods and heterogenious treatment effects.
I collaborate on a variety of areas in which I develop needed or apply advanced or nonstandard methods to best address questions. I have made methodological contributions in the areas of management information systems, information technology, operations management, organizational behavior, human resources management, education, cognitive psychology, among others. In each instance, I developed needed or applied advanced and non-standard methods to address the question of interest.
Designing Experiments and Analyzing Data: A Model Comparison Perspective
Winner of the Barbara Byrne Award for Outstanding Book or Edited Volume.
Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. This book is widely used in doctoral programs in the human sciences as a first or second course in research design and analysis, as well as a reference for researchers.
See the accompanying website, DesigningExperiments.com. Feel free to email me with suggestions or comments.
The book is available from Routledge. Instructors who are considering adopting the book for their course may request a complimentary copy here.
Human-centered Analytics Lab
This is a broad framing of a research lab that is interdisciplinary by design and pragmatic in approach. The HAL combines disparate skillsets and foundational disciplines to solve problems in an effort to improve understanding of the human condition in the context of the digital life of persons.
Co-directed with Ahmed Abbasi, HAL provides a framework for development of methods, application of AI, and the use of and analytics for substantive research.
Associations
- Association for Psychological Science, Fellow
- American Psychological Association, Fellow
- Society of Multivariate Experimental Psychology, Elected Member
- Accredited Professional Statistician™ (PStat®) by the American Statistical Association