Understanding Effect Sizes

Francis Sahngun Nahm

doi:10.7599/hmr.2015.35.1.40

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Nahm: Understanding Effect Sizes

Review Article

Hanyang Medical Reviews 2015; 35(1): 40-43.

Published online: 26 February 2015

DOI: https://doi.org/10.7599/hmr.2015.35.1.40

Understanding Effect Sizes

Francis Sahngun Nahm

Department of Anesthesiology and Pain Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.

Correspondence to: Francis Sahngun Nahm. Department of Anesthesiology and Pain Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro 173 beon-gil, Bundang-gu, Seongnam 463-707, Korea. Tel: +82-31-787-7499, Fax: +82-31-787-4063, hiitsme@snubh.org

Received 30 November 2014 Revised 14 December 2014 Accepted 31 December 2014

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In most medical research the P value is commonly used to describe test results. Because the power of statistical test is influenced by sample size, the null hypothesis can be rejected (P<0.05) in most cases if the sample size is tremendously big even if the real difference (or relationship) is extremly small. To overcome the weakness of using the P value, effect size can be used in the statistical analysis. Effect size can be defined as the "degree to which the phenomenon (difference or relationship) is present in the population". The effect size is used in sample size calculation, data interpretation and conducting meta-analysis. This manuscript describes limitations in using the P value and further introduces the concept of effect size.

Keywords: Data Interpretation, Statistical, Meta-Analysis, Research Design

Figures and Tables

Fig. 1

Example of effect size=1.96. The mean of the treatment group is in the range of upper 5% of the control group.

Table 1

Various types of effect sizes [5]

References

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2. Olejnik S, Algina J. Measures of effect size for comparative studies: applications, interpretations, and limitations. Contemp Educ Psychol. 2000; 25:241–286.

3. Anderson DR, Burnham KP, Thompson WL. Null hypothesis testing: problems, prevalence, and an alternative. J wildl Manage. 2000; 64:912–923.

4. McGraw KO, Wong SP. A common language effect size statistic. Psychol Bull. 1992; 111:361–365.

5. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. New York: Lawrence Erlbaum Associates;1988.

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