June 10-12 Short Courses
Introduction to Multilevel Analysis
Dr. James LeBreton
Course Description
The CARMA Introduction to Multilevel Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct basic multilevel analyses. Emphasis will be placed on techniques for traditional, hierarchically nested data (e.g., children in classrooms; employees in teams). The first part of the course introduces issues related to multilevel theory (e.g., multilevel constructs; principles of multilevel theory building; cross-level inferences and cross-level biases). The second part of the course discusses issues related to multilevel measurement (e.g., aggregation; aggregation bias; composition and compilation models of emergence; estimating within-group agreement). The last part of the course focuses on the specification of basic 2-level models (e.g., soldiers nested in platoons; employees nested within work teams) analyzed via multilevel regression (i.e., random coefficient regression; hierarchical linear model; mixed effects model). All analyses will be undertaking using R and RStudio. The course is best suited for faculty and graduate students who are familiar with traditional (i.e., single-level) multiple regression analysis, but have little (if any) expertise related to conducting multilevel analyses.
Required Software: R ( https://www.r-project.org ), RStudio (https://www.rstudio.com )
Event Information
June 10-12, 2024
Mon/Tues/Wed: Daily from 10:00 AM EDT – 4:00 PM EDT with a 30-minute lunch break and other breaks as needed.
CARMA’s Live Online Global Classroom
Meet the Instructor
James M. LeBreton is a Professor of Psychology and Social Data Analytics at Pennsylvania State University. Over the last 20 years he has been involved with developing, testing, and revising the Conditional Reasoning Theory of Personality. This theory is anchored to the concept of motivated reasoning. Specifically, individuals with strong personality motives (e.g., motive to aggress) develop cognitive biases (e.g., hostile attribution bias) that they use to help rationalize the pursuit of behaviors satisfying the underlying motives (e.g., harming others). As part of this research program, James has helped develop and validate measures assessing the motive to aggress, the motive to achieve, and the motive for power. Using these new measures, he has tested hypotheses linking personality to an array of organizational outcomes including: counterproductive work behavior, leadership, team processes & performance, and job attitudes. In addition, James’ methodological research program has examined issues related to variable importance (e.g., relative weights analysis), multilevel research (e.g., data aggregation, dyadic analysis), and general topics in measurement (e.g., test development & validation, measurement invariance, test bias & fairness). James is a former associate editor (2010-2013) and editor-in-chief (2014-2018) of Organizational Research Methods; and, he also co-edited the APA Handbook of Multilevel Theory, Measurement, and Analysis (2019). James is a fellow of the American Psychological Association, the Association for Psychological Science, the Society for Industrial and Organizational Psychology, and the Consortium for the Advancement of Research Methods and Analyses. Recently, James was awarded the 2023 Distinguished Career Contributions Award by the Research Methods Division of the Academy of Management.
Video Introduction
