Certified Advanced Alcohol and Drug Counselor (CAADC) Practice Exam

When studying the effect of singing on learning sign language, which design helps eliminate pretest influences?

1. Multiple regression

2. Chi-square

3. ANOVA

4. Solomon four-group design

The correct answer is: Solomon four-group design

The Solomon four-group design is particularly effective in research settings where pretesting might introduce biases or confounding variables that could skew the results. This design includes four groups: two that receive the pretest and two that do not. By comparing the outcomes of both groups with and without pretesting, researchers can effectively assess whether any differences in results are attributable to the intervention rather than pretest influences. This design not only helps eliminate pretest effects but also strengthens the validity of the conclusions drawn from the study. In contrast, the other methods listed do not specifically account for the effects of pretesting. For instance, multiple regression could analyze several variables at once, but it doesn’t inherently address pretest bias. Chi-square tests are useful for categorical data, but they do not involve manipulation of groups, and ANOVA looks at differences across groups but does not control for pretesting confounds. Thus, the Solomon four-group design is the most suitable choice for isolating the impact of singing on learning sign language while mitigating pretest influences.