Are you trying to understand data from your research? Learn how and when to conduct mediation, moderation, and conditional indirect effects analyses? Or, perhaps, how to theorize and test your theoretical models? If so, this is the course for you! We will walk you through the steps of conducting multilevel analyses using a real dataset and provide articles and templates designed to facilitate your learning. You'll leave with the tools you need to analyze and interpret the results of the datasets you collect as a researcher.
By the end of this course, you will understand the differences between mediation and moderation and between moderated mediation and mediated moderation models (conditional indirect effects), and the importance of multilevel analysis. Most important, you will be able to run mediation, moderation, conditional indirect effect and multilevel models and interpret the results.
This course is supported by the BRAD Lab at the Darden School of Business, which studies organizational behavior, marketing, business ethics, judgment and decision-making, behavioral operations, and entrepreneurship, among other areas. More: http://www.darden.virginia.edu/brad-lab/

From the lesson

Multilevel Analysis

Now that you know how to run mediation, moderation, and conditional indirect effect analyses, we can turn our attention to multilevel models. Multilevel models are statistical models of parameters that vary at more than one level. Think about employees nested in departments, or departments nested in firms. You will learn the importance of multilevel analysis to your research and get familiar with multilevel analysis language. By the end of this module, you will be able to use HLM software to run multilevel models and interpret the results.