This paper focuses on the treatment of statistical interactions (i.e., non-additivity) within the framework of multiple regression. The nature of statistical interactions in relation to other types of effects and the implications of interactions for analysis and interpretation are discussed. We argue that researchers using regression analyses (1) often either fail to test for interactions (2) or use inadequate methods for testing for interactions (3) and, consequently may make faulty conclusions about their data. We outline several methods of dealing with interactions with regression and discuss the strengths and weaknesses of each. Recommendations are made for the detection and treatment of interactions within regression. © 1991, Taylor & Francis Group, LLC. All rights reserved.