Understanding Interaction Effects and Type IV Errors.

Aptitude-treatment interaction (ATI) studies have been used with some frequency, yet many researchers do not understand fully what interaction effects are. Because the means for interactions involve fewer persons per mean, power to detect interaction effects is typically smallest for the highest-order interaction in a given design. This phenomenon has been formalized by some methodologists as the Type IV error--the failure to detect statistical significance for the interaction null hypotheses that really should be rejected. This paper reviews the concept of the interaction effect. Small heuristic data sets are used to make the discussion more concrete. The concept of interaction is important because it links the two-way factorial designs with designs involving three or more independent variables. An appendix illustrates the analysis of variance technique. (Contains 4 figures, 5 tables, and 12 references.) (Author/SLD)