I am a methodologist working at the intersection of measurement, design, and analysis. My work seeks to improve the methods used in human-centered research, from the foundational area of psychology to applied areas in business. My work crosses several traditional disciplinary boundaries, which I believe is important for considering various aspects of the human condition. More specifically, I evaluate, improve, and develop methods to better study human-centered research from a methodological perspective. The entire effort is in the data science space, particularly from the psychometric and statistical traditions of framing inferential questions. My most significant methodological contributions are in research design involving the interplay between effect size, confidence intervals, statistical significance, and sample size planning. My work depends heavily on statistical computing, with most of the methods I have developed implemented in R packages (e.g., MBESS, BUCCS, SMRD). In addition to methodological work, I collaborate in a variety of human-centered areas in which I develop needed or apply advanced or nonstandard methods to best address questions. Other methodological contributions I have been involved in concern mediation models, in which causal pathways are considered to explain process, and repeated or longitudinal methods, in which the same individuals are measured over some time period in an effort to understand intraindividual change and interindividual differences in change. An important application of my work is business analytics, where psychological, behavioral, and social data are often combined to help model and explain some aspect of business. In this way, I regard business analytics as the translational arm of data science concerned with the person in organizations or markets.


More recently, I have moved more fully into application of these and other methods in the digital space, where I co-director of the Human-centered Analytics Lab (HAL) in the IT, Analytics, and Operations Department within the Mendoza College of Business. HAL is a lab like no other I am familiar with, where disciplinary boundaries do not apply and multiple fields usually isolated from one another are merged into an interdisciplinary mash-up of technology, psychology, methodology, and business.


See Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) and its accompanying website at DesigningExperiments.Com.

                    Ken Kelley, PhD

Edward F. Sorin Society Professor of

IT, Analytics, and Operations and

Senior Associate Dean for Faculty and Research

         Mendoza College of Business

             University of Notre Dame

           Notre Dame, Indiana 46556


                    KKelley@ND.Edu

                     nd.edu/~kkelley

                      574-631-1459