True or False: If a combination of variables yields a significant result, it must be a main effect.

A combination of variables yielding a significant result does not necessarily indicate that it must be a main effect, which is why the statement is false. In factorial designs, significant results can arise from interactions between variables rather than just main effects.

A main effect refers to the individual influence of an independent variable on a dependent variable, assessed while averaging over the levels of other independent variables. In contrast, an interaction occurs when the effect of one independent variable on the dependent variable differs depending on the level of another independent variable. Therefore, a significant result could indicate an interaction effect rather than a clear main effect.

In practical terms, researchers must look at the specific nature of the analysis (such as ANOVA) to understand whether a significant outcome is entirely due to main effects, interactions, or both. This highlights the importance of interpreting results within the context of the study design and the variables involved.