Main effects can be defined as the average differences between one independent variable (or factor) and the other levels of one or more independent variables. In other words, investigators identify main effects, or how one independent variable influences the dependent variable, by ignoring or constraining the other independent variables in a model. For instance, let us say there is a difference between two levels of independent variable A and differences between three levels of independent variable B. Consequently, researchers can study the presence of both factors separately, as in single-factor experiments. Thus, main effects can be determined in either single-factor experiments or factorial design experiments. In addition, main effects can be interpreted meaningfully only if the interaction effect is absent. This entry focuses on main ...
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