Understanding Your Data: Analytical Tools
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/
Mediation and Moderation
Welcome to the first week of our research methods course! We’ll start with mediation analysis, following by parallel mediation, serial mediation, and moderation. Mediation is all about the mechanisms connecting the independent variable and dependent variable. Moderation refers to the circumstances under which the independent variable influences the dependent variable. By the end of this week, you will know how, when, and where the independent variable influences the dependent variable and how to theorize and conduct analysis using SPSS.
Conditional Indirect Effects
Now that you know more about mediation and moderation, let’s take a look at conditional indirect effects models, which are a combination of mediation and moderation models. First we will get to the heart of the differences between moderated mediation and mediated moderation models.This will allow you to fully understand the relationships between independent variables and dependent variables. By the end of the module, you will be able to theorize about conditional indirect effect models on SPSS and to test which path of the mediation model is affected by the moderator. Then you’ll dive into SPSS, run different models, and learn how to interpret the results.
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.
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