Linear Regression: Introduction, Mediation, and Moderation


Livestream: December 1-3, 2021
Replay Access: 6 months from end of workshop
Instructors: Dan Bauer & Patrick Curran

Student: $475
Professional: $595



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The linear regression model is arguably the most important data analysis and hypothesis testing framework in the behavioral, health, and social sciences. Not only is the regression model extremely powerful in its own right, it also serves as the foundation for many more advanced methods and applications. This three-day workshop is designed to provide a thorough introduction to the many strengths of the linear regression model. We build from a simple single-predictor model to the multiple regression model with two or more continuous or categorical predictors (explicating how the latter are represented via numerical coding variables). We emphasize how to test and interpret both unique and joint effects of predictors, including standardized measures of effect size. We then show how the regression model can be extended to provide tests of both interaction/moderation (allowing for insights into under what conditions an effect might hold) and mediation/process (allowing for insights into why an effect might hold). We place an equal emphasis on describing the underlying statistical model and how it can be applied in practice to rigorously test real research questions. Live software demonstrations are conducted using R, SPSS, and SAS, including use of the PROCESS macro (Hayes, 2022) where relevant. Upon completion, participants will be able to confidently apply the linear regression model to test a broad array of research hypotheses with their own data.