Analysis of variance (ANOVA) designs typically use what is referred to as crossed design to test for differences between means of groups. In a balanced, or crossed, one-way ANOVA, each student (unit of analysis) would have a score in each of the experimental conditions. In a two-way design, the analysis is considered crossed if each level from one way is contained in each level of the other way. In this design, every person (unit of analysis) has a score in every cell. Many experimental designs in the behavioral sciences do not qualify as a crossed design. Units of measurement are rather "nested" inside other factors. A crossed experimental design would neglect the hierarchical structure of the data and produce incorrect interpretations of results. Neglecting a nested design when one actually exists will make the researcher: (1) wrongly attribute a main effect to an interaction effect when, in fact, no interaction exists; (2) divide by the wrong degrees of freedom when determining the mean square and F-value (and the statistical significance of the F-value); and (3) assume that a main effect has a smaller effect size (eta-squared) because the sum of squares for that effect is being partly attributed to the interaction effect. (SLD)