I am a methodologist working at the intersection of design, measurement, 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, such as organizational behavior and information technology. 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 and understand human-centered research. 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). 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. In addition to methodological work, I collaborate in a variety of areas in which I develop needed or apply advanced or nonstandard methods to best address questions. 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 for business problems, where my work is concerned most often 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 am 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, in which disciplinary boundaries do not apply and multiple fields usually isolated from one another are merged into an interdisciplinary mash-up of information technology, psychology, methodology, and business.

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