June 2025 Live Online Short Course

Advanced Multilevel Analysis II:
Panel Data, Consensus/Emergent Models,
and Dichotomous Outcomes
Dr. Paul Bliese

Session II: June 9-12 | 10:00 AM EDT – 3:00 PM EDT

Course Description

The CARMA “Advanced Multilevel Analysis II: Panel Data, Consensus/Emergent Models, and Dichotomous Outcomes” short course provides the (1) theoretical foundation, and (2) resources and skills necessary to conduct a variety of advanced multilevel and longitudinal analyses using the R mixed-effect modeling packages nlme and lme4. The course briefly reviews basic models (e.g., 2-level mixed and growth models) before addressing more advanced topics (econometric fixed-effect models for panel data, discontinuous growth models, consensus emergent models, and multilevel models for dichotomous outcomes). Practical exercises, with real-world research data are provided. Participants are encouraged to bring datasets to the course and apply the principles to their specific areas of research. The course is best suited for faculty and graduate students who have a foundational understanding of mixed-effects models.

Course Preview

Meet the Instructor

Paul D. Bliese is the Jeff B. Bates Professor of Management at the Darla Moore School of Business. He received a Ph.D. from Texas Tech University and a B.A. from Texas Lutheran University. After graduating in 1991, he worked for a year for the Bureau of Labor Statistics. In 1992, he joined the US Army, where he spent 22 years as a research psychologist at the Walter Reed Army Institute of Research. In his last military assignment, he served as the director of the Center for Military Psychiatry and Neuroscience and retired at the rank of Colonel in 2014. Over his military career, Bliese directed a large portfolio of research initiatives examining stress, leadership, well-being and performance. From 2007 to 2014, he oversaw the US Army’s Mental Health Advisory Team program assessing the morale and well-being of soldiers deployed to Iraq and Afghanistan. Throughout his professional career, Bliese has led efforts to advance statistical methods and apply analytics to complex organizational data. He developed and maintains the multilevel package for the open-source statistical programming language R, and his research has been influential in advancing organizational multilevel theory. He has published in numerous outlets and served on many editorial boards. He was an Associate Editor for the Journal of Applied Psychology from 2010 to 2017 and is the incoming Editor-in-Chief for Organizational Research