• Restorative Dentistry and Endodontics
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• v.49 no.2
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• pp.21.1-21.8
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• 2024

Objectives: This paper aims to serve as a useful guide for sample size determination for various correlation analyses that are based on effect sizes and confidence interval width. Materials and Methods: Sample size determinations are calculated for Pearson's correlation, Spearman's rank correlation, and Kendall's Tau-b correlation. Examples of sample size statements and their justification are also included. Results: Using the same effect sizes, there are differences between the sample size determination of the 3 statistical tests. Based on an empirical calculation, a minimum sample size of 149 is usually adequate for performing both parametric and non-parametric correlation analysis to determine at least a moderate to an excellent degree of correlation with acceptable confidence interval width. Conclusions: Determining data assumption(s) is one of the challenges to offering a valid technique to estimate the required sample size for correlation analyses. Sample size tables are provided and these will help researchers to estimate a minimum sample size requirement based on correlation analyses.

• Journal of the Korea Society of Computer and Information
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• v.22 no.4
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• pp.115-122
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• 2017

The purpose of this study was to evaluate the effect of job satisfaction on turnover intention and organizational commitment in nurses through a systematic literature review and meta-analysis. For the study purpose, 26 studies were selected through a systematic process of using several databases and used to estimate the effect size of correlation between 3 variables. Meta-analysis was applied by usingcrandom effects model, and effect sizes on three types were calculated. Results are as follows. First, the effect size of correlation between job satisfaction and turnover intention is -.58. Second, the effect size of correlation between job satisfaction and organizational commitment is .77. Third, for the organizational commitment and turnover intention relationship, the effect of correlation is -0.68. Furthermore, publication bias analysis were assessed the results by using the funnel plot, Egger's regression test, fail-safe N, and trim-and-fill test. Based on these results, implications for the study were discussed.

• Journal of the Korea Society of Computer and Information
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• v.23 no.10
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• pp.157-164
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• 2018

The purpose of this study was to investigate the effect of empowerment in nurses through a systematic literature review and meta-analysis. 23 studies were collected through a systematic process of using several databases such as NDSL, DBPIA, and KISS. Keywords included 'nurse', 'empowerment', and 'correlation' and the reviewed articles were published from 2002 to 2017. In order to estimate the effect size of correlation between empowerment, 3 variables (job satisfaction, organizational commitment, and nursing performance) were considered. Using the R program, meta-analysis was calculated by using random effects model, and effect sizes on three types were estimated. As the result, it was found, first, the effect size of correlation between job satisfaction and empowerment is .50. Second, the effect size of correlation between organizational commitment and empowerment is .45. Third, for the nursing performance and empowerment relationship, the effect of correlation is 0.50. Also, Egger's regression test, fail-safe N, trim-and-fill test, and funnel plot were showed to evaluate the results. These results highlights the need for appropriate policies of the relationship between empowerment and job satisfaction, organizational commitment and nursing performance in nurses.

• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.391-402
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• 2016

The purpose of this study is to use meta-analysis as a research method to investigate the correlation between early child teachers' teaching efficacy and their job satisfaction, and thereby look into the effect size of the two variables and their sub-variables. To achieve the purpose, this researcher chose a total of 37 theses for analysis and collected 289 data for analyzing the effect size. Based on the data, CMA(Comprehensive Meta Analysis) 2.0 was applied. According to the analysis, the correlation between early childhood teachers' teaching efficacy and their job satisfaction was higher than the medium effect size on the basis of Cohen(1992) research. In the sub-variables of teaching efficacy, the correlation of personal teaching efficacy with job satisfaction showed higher effect size than that of general teaching efficacy. In the sub-variables of job satisfaction, the correlation between the belief in job and teaching efficacy showed the highest effect size. In terms of thesis type as a moderating variable, Ph.D dissertations showed higher effect size than journals or M.A. theses. As the result of the meta-analysis on publishing year and the number of samples, there was no statistical significance. On the basis of the analysis results, discussions and limitations of this study were suggested.

• Journal of Power System Engineering
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• v.4 no.2
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• pp.40-45
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• 2000

Some engineering materials are often known to have considerable spatial variation in their resisting strength and other properties. The objective of this study is to investigate the averaging effect and the applicability of extremal statistic for the statistical size effect. In the present study, it is assumed that the material property is a stationary random process in space. The theoretical autocorrelation function of the material strength are discussed for several correlation lengths. And, in order to investigate the statistical size effect, the material properties was simulated by using the non-Gaussian random process method. The material properties were plotted on the Weibull probability papers. The main results are summarized as follows: The autocorrelation function of the material properties are almost independent of the averaging length. The variance decreases with increasing the averaging length. As correlation length is smaller, the slope is larger. And also, it was found that Weibull statistics based on the weakest-link model could not explain the spatial variation of material properties with respect to the size effect satisfactory.

• Korean Journal of Child Education & Care
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• v.19 no.3
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• pp.1-12
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• 2019

Objective: This study aims to thoroughly analyze the correlation effect size between domestic violence and school violence by meta-analyzing previous studies on the correlation between school and domestic violence. Methods: For this purpose, meta-analysis was performed on the selected research material, which consists of national research data collected from various databases from 2001 to April, 2019. 16 thesis and 9 papers on the correlation between school and domestic violence were selected. A random effect model analysis based on the homogeneity examination results was performed on the selected data. Results: The results showed, just as Cohen (1977) proposed, that the correlation effect size between domestic and school violence was 0.25, which is moderate. This is a somewhat lower number than the previous studies on the same subject presented. Of the sub-categories of domestic violence, physical violence and psychological violence appeared to have a correlation effect size of 0.34 and 0.28, respectively, with physical violence showing the highest correlation effect size. Of the types of domestic violence, witnessing spouse violence and experiencing neglect appeared to have a moderate correlation size effect of 0.24. All of these results were statistically significant. Conclusion/Implications: This study utilized meta-analysis as a comprehensive and systematic method to analyze the correlation effect between domestic and school violence. The results presented may lead to discussions on the subject's social implications, limits, and propositions for future studies.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.6
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• pp.805-813
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• 2013

In this study, molecular size distribution of natural organic matter (NOM) after ozonation was measured and its effect on adsorption capacity of activated carbon was investigated. According to the results, the molecular size of NOM was limitedly changed. Specifically, the molecular size of NOM between 5,000 to 10,000 Da were slightly decreased with increasing ozone doses. The adsorption capacity after ozonation was evaluated using Freundlich isotherm with ideal adsorbed solution theory (IAST) which simulated the multi components adsorption. Further, mini-column test was conducted. The Freundlich constant, K was reduced after ozonation and the non-adsorbable fraction was increased with ozonation. However, no correlation between K and ozone doses was found. The present study also agreed with the correlation between adsorption capacity and pore size characteristics of activated carbon.

• Korean Journal of Child Studies
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• v.37 no.4
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• pp.83-99
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• 2016

Objective: The purpose of this study was to analyze correlation effect size between Basic Psychological Needs (BPN) and factors affecting BPN. Methods: This research was reviewed and synthesized systematically by meta-analyse. Fifty-eight published studies between 2008 and 2016 were sampled and the effect sizes were acquired. Results: The major findings were as follows. In general, medium correlation effect sizes were found. Competency among sub-factors of BPN showed highest effects. Parental factor was more related to BPN than school and individual factors. Parenting behavior and family psychological backgrounds were the most crucial factors in the parental factors. School adjustment was the most critical factor in the school factors. In school grade, the elementary school was more related to BPN than junior high school and high school. Conclusion: Based on these results, we suggest a number of components for parent-education programs, and information for future research.

• Asia-Pacific Journal of Business
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• v.9 no.3
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• pp.117-137
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• 2018

Lots of the studies about the relationship between coaching leadership and organizational effectiveness have been conducted and reported that coaching leadership is one of the main factors which impact organizational effectiveness. The purpose of this study was to synthesize the relationship between coaching leadership and organizational effectiveness. For that purpose, 32 correlation effect sizes from 25 studies were analyzed by the CMA (Comprehensive Meta-analysis) Program. The study calculated the overall effect size of the relationship between coaching leadership and organizational effectiveness. Then, it also calculated the effect size of the relationship between coaching leadership and each sub-variable of organizational effectiveness. The analysis results are as follows: First, the overall effect size about the relationship between coaching leadership and organizational effectiveness was .519, which means that coaching leadership has over lager relationship with organizational effectiveness. In addition, the effect sizes of sub-variables of the organization are .556 (organizational commitment) .542 (job satisfaction), 509 (organizational citizen behavior), and .401 (innovative behavior). The study tested the mediating effects of measurements, organizational size, types of publication, and published year. The result showed that only the measurement made significant differences among effect sizes of studies.

• Journal of Korean Academy of Nursing
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• v.45 no.5
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• pp.641-649
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• 2015

Purpose: The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. Methods: For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Results: Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. Conclusion: It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.