Which statistical method is used to compare means across multiple groups?

The use of ANOVA, or Analysis of Variance, is specifically designed to compare the means of three or more groups to determine if at least one group mean is significantly different from the others. This statistical method is particularly useful when researchers want to assess the effects of one or more independent categorical variables on a continuous dependent variable. By employing ANOVA, researchers can analyze the variance within groups and between groups, thereby providing insights into group differences while controlling for potential Type I errors that could arise if multiple t-tests were used instead.

ANOVA can help identify whether differences exist and indicate where they may lie without the need for pairwise comparisons unless a significant effect is found. The versatility of ANOVA extends to various types, such as one-way ANOVA for comparing means across one independent variable or two-way ANOVA for analyzing the impact of two independent variables simultaneously.

Using ANOVA is crucial in research settings, particularly within clinical psychology, as it allows psychometricians and researchers to derive meaningful conclusions from complex data involving multiple groups, such as treatment groups in clinical trials.