Delivery: Live and virtual

Connect the way research data is structured to the statistical models used to analyze it. Designed primarily for doctoral students building their methods foundation

What to Expect

Data analyzed in organizational research frequently violates the basic regression assumption that errors are independent and unrelated to predictors. This tutorial uses examples and simple illustrations to show why this non-independence can be problematic in both cross-sectional and longitudinal data. The tutorial also gives a high-level overview of common ways to address non-independence, with a focus on how addressing non-independence can expand a researcher’s research methods repertoire and strengthen the theory-methods-data link.

Presenter

Dr. Paul Bliese, University of South Carolina

Paul D. Bliese is the Department Chair and Jeff B. Bates Chaired Professor in the Management Department at the Darla Moore School of Business at the University of South Carolina. He received a Ph.D. from Texas Tech University. After graduate school, he worked for 22 years at the Walter Reed Army Institute of Research and retired as a Colonel. Throughout his career, Dr. Bliese has led efforts to use statistical methods to answer complex organizational problems and advance theory and practice. He developed and maintains the multilevel package for R and has published in a variety of journals, including the Academy of Management Journal, the Journal of Applied Psychology, the Journal of Management, Organizational Research Methods, and Organization Science. He served as an Associate Editor for the Journal of Applied Psychology from 2010 to 2017 and as the Editor in Chief for Organizational Research Methods from 2017 to 2021. In 2024, he began a new role as the first Deputy Editor for Research Methods for the Academy of Management Journal.

Register for the tutorial series

One registration includes all four live tutorials, their released resources, and related program activities.