What does the term 'main effect' refer to in a two-way ANOVA?

What does the term 'main effect' refer to in a two-way ANOVA?

• A. The interaction between two independent variables
• B. The effect of each independent variable on the dependent variable
• C. The overall mean of the dependent variable
• D. The difference between the highest and lowest means

Answer: (B)

The term 'main effect' in a two-way ANOVA specifically refers to the impact of each independent variable on the dependent variable, considered separately from the other independent variables. When assessing main effects, researchers are interested in how changes in one independent variable lead to variations in the dependent variable, while holding the other independent variable constant. For instance, in a study examining the effects of different treatment types and different age groups on patient outcomes, the main effect of treatment would look at how patient outcomes change across the different treatment types, irrespective of age. Each independent variable can produce a main effect, offering insights into its individual contribution to any observed differences in the dependent variable. This understanding enables researchers to discern not just the interactions between variables (which is a different concept), but also the straightforward influence of each independent variable by itself, thereby enhancing the clarity in interpreting the results of a two-way ANOVA.

The term 'main effect' in a two-way ANOVA specifically refers to the impact of each independent variable on the dependent variable, considered separately from the other independent variables. When assessing main effects, researchers are interested in how changes in one independent variable lead to variations in the dependent variable, while holding the other independent variable constant.

For instance, in a study examining the effects of different treatment types and different age groups on patient outcomes, the main effect of treatment would look at how patient outcomes change across the different treatment types, irrespective of age. Each independent variable can produce a main effect, offering insights into its individual contribution to any observed differences in the dependent variable.

This understanding enables researchers to discern not just the interactions between variables (which is a different concept), but also the straightforward influence of each independent variable by itself, thereby enhancing the clarity in interpreting the results of a two-way ANOVA.