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Review
. 2021:18:17.
doi: 10.3352/jeehp.2021.18.17. Epub 2021 Jul 30.

Sample size determination and power analysis using the G*Power software

Affiliations
Review

Sample size determination and power analysis using the G*Power software

Hyun Kang. J Educ Eval Health Prof. 2021.

Abstract

Appropriate sample size calculation and power analysis have become major issues in research and publication processes. However, the complexity and difficulty of calculating sample size and power require broad statistical knowledge, there is a shortage of personnel with programming skills, and commercial programs are often too expensive to use in practice. The review article aimed to explain the basic concepts of sample size calculation and power analysis; the process of sample estimation; and how to calculate sample size using G*Power software (latest ver. 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany) with 5 statistical examples. The null and alternative hypothesis, effect size, power, alpha, type I error, and type II error should be described when calculating the sample size or power. G*Power is recommended for sample size and power calculations for various statistical methods (F, t, χ2, Z, and exact tests), because it is easy to use and free. The process of sample estimation consists of establishing research goals and hypotheses, choosing appropriate statistical tests, choosing one of 5 possible power analysis methods, inputting the required variables for analysis, and selecting the “calculate” button. The G*Power software supports sample size and power calculation for various statistical methods (F, t, χ2, z, and exact tests). This software is helpful for researchers to estimate the sample size and to conduct power analysis.

Keywords: Biometry; Correlation of data; Research personnel; Sample size; Software.

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Conflict of interest statement

Conflict of interest

No potential conflict of interest relevant to this article was reported.

Figures

Fig. 1.
Fig. 1.
Using the G*Power software for the 2-independent sample t-test. (A) Main window before a priori sample size calculation using an effect size, (B) main window after a priori sample size calculation using an effect size, (C) main window showing the protocol for power analyses, (D) effect size calculator window, (E) plot window, (F) main window before a priori sample size calculation not using an effect size, (G) main window after a priori sample size calculation not using an effect size, and (H) main window before post-hoc power analysis.
Fig. 2.
Fig. 2.
Using the G*Power software for the dependent t-test. (A) Main window before a priori sample size calculation using an effect size, (B) main window after a priori sample size calculation using an effect size, and (C) effect size calculator window.

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