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Sample size determination and power analysis using the G*Power software  
Hyun Kang
J Educ Eval Health Prof. 2021;18:17.   Published online July 30, 2021
DOI: https://doi.org/10.3352/jeehp.2021.18.17
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  • 267 Citations
AbstractAbstract PDFSupplementary Material
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.

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Technical report
Varying levels of difficulty index of skills-test items randomly selected by examinees on the Korean emergency medical technician licensing examination  
Bongyeun Koh, Sunggi Hong, Soon-Sim Kim, Jin-Sook Hyun, Milye Baek, Jundong Moon, Hayran Kwon, Gyoungyong Kim, Seonggi Min, Gu-Hyun Kang
J Educ Eval Health Prof. 2016;13:5.   Published online January 15, 2016
DOI: https://doi.org/10.3352/jeehp.2016.13.5
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AbstractAbstract PDF
Purpose
The goal of this study was to characterize the difficulty index of the items in the skills test components of the class I and II Korean emergency medical technician licensing examination (KEMTLE), which requires examinees to select items randomly.
Methods
The results of 1,309 class I KEMTLE examinations and 1,801 class II KEMTLE examinations in 2013 were subjected to analysis. Items from the basic and advanced skills test sections of the KEMTLE were compared to determine whether some were significantly more difficult than others.
Results
In the class I KEMTLE, all 4 of the items on the basic skills test showed significant variation in difficulty index (P< 0.01), as well as 4 of the 5 items on the advanced skills test (P< 0.05). In the class II KEMTLE, 4 of the 5 items on the basic skills test showed significantly different difficulty index (P< 0.01), as well as all 3 of the advanced skills test items (P< 0.01).
Conclusion
In the skills test components of the class I and II KEMTLE, the procedure in which examinees randomly select questions should be revised to require examinees to respond to a set of fixed items in order to improve the reliability of the national licensing examination.

Citations

Citations to this article as recorded by  
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JEEHP : Journal of Educational Evaluation for Health Professions