Effect-size measures and meta-analytic thinking in counseling psychology research

Effect sizes are critical to result interpretation and synthesis across studies. Although statistical significance testing has historically dominated the determination of result importance, modern views emphasize the role of effect sizes and confidence intervals. This article accessibly discusses how to calculate and interpret the effect sizes that counseling psychologists use most frequently. To provide context, the author presents a brief history of statistical significance tests. Second, the author discusses the difference between statistical, practical, and clinical significance. Third, the author reviews and graphically demonstrates two common types of effect sizes, commenting on multivari-ate and corrected effect sizes. Fourth, the author emphasizes meta-analytic thinking and the potential role of confidence intervals around effect sizes. Finally, the author gives a hypothetical example of how to report and potentially interpret some effect sizes. For the past 50 or so years, statistical significance testing has dominated how psychologists have evaluated research outcomes. For example, Hubbard and Ryan (2000) observed that the null hypothesis significance test (NHST) was the analytic approach of choice in a historical review of 12 American Psychological Association (APA) journals. Historical use notwithstanding, researchers often misunderstand or misinterpret NHST