• Journal of Korean Academy of Fundamentals of Nursing
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• v.22 no.4
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• pp.452-457
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• 2015

Purpose: In nursing research, studies using statistical methods are required and have increased. In this study, some statistical methods using in nursing study are summarized and appropriate usage is proposed. Methods: Twenty-five original articles from the Journal of Korean Academy of Fundamentals Nursing were reviewed. Statistical methods used in the Journal of Fundamentals Nursing were classified and common errors were presented. Results: Seventy-six statistical analysis were performed in the 25 studies. Among the articles, 28 cases contained errors. Most errors occurred in linear regression analysis and nonparametric analysis. Conclusion: When the use of statistical method is applied inappropriately, the result bring out a serious error. In order to ensure reliability and validity of study, researchers should recognize clear application and usage of statistical methods.

• The Korean Journal of Pain
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• v.23 no.1
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• pp.35-41
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• 2010

Background: Statistical analysis is essential in regard to obtaining objective reliability for medical research. However, medical researchers do not have enough statistical knowledge to properly analyze their study data. To help understand and potentially alleviate this problem, we have analyzed the statistical methods and errors of articles published in the Korean Journal of Pain (KJP), with the intention to improve the statistical quality of the journal. Methods: All the articles, except case reports and editorials, published from 2004 to 2008 in the KJP were reviewed. The types of applied statistical methods and errors in the articles were evaluated. Results: One hundred and thirty-nine original articles were reviewed. Inferential statistics and descriptive statistics were used in 119 papers and 20 papers, respectively. Only 20.9% of the papers were free from statistical errors. The most commonly adopted statistical method was the t-test (21.0%) followed by the chi-square test (15.9%). Errors of omission were encountered 101 times in 70 papers. Among the errors of omission, "no statistics used even though statistical methods were required" was the most common (40.6%). The errors of commission were encountered 165 times in 86 papers, among which "parametric inference for nonparametric data" was the most common (33.9%). Conclusions: We found various types of statistical errors in the articles published in the KJP. This suggests that meticulous attention should be given not only in the applying statistical procedures but also in the reviewing process to improve the value of the article.

• Journal of Korean Academy of Nursing Administration
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• v.19 no.1
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• pp.146-154
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• 2013

Purpose: To do nursing research effectively requires an understanding of fundamental principles of statistical methods. In this article, some key statistical methods which are commonly used in nursing research are identified and summarized. Methods: Ninety-two original articles from the Journal of Korean Academy of Nursing Administration were reviewed. Statistical methods were classified and summarized for usage in research and occurrence of common errors. Results: Among the original articles reviewed, 58 statistical usages contained errors. Most errors were found in linear regression analysis, Pearson correlation analysis, and chi-square test. From the detection of statistical errors in usage, suggestions for appropriate statistical methods were made. Conclusion: In order to improve validity of original articles in the Journal of Korean Academy of Nursing Administration, clearly stated statistical usage and close editorial attention to statistical methods are needed. Understanding statistical methods is part of the process that researchers must use to determine both quality and usefulness of the research. Research findings will be used to guide nursing practice and reduce uncertainty in decision making. However, to understand how to interpret research results, it is important to be able to understand basic statistical concepts. Researchers should also choose statistical methods that match their purposes.

• Journal of Korean Medicine Rehabilitation
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• v.20 no.4
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• pp.105-130
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• 2010

Objectives : The purpose of this study was to assess the statistical methods errors used in the journal of Oriental Rehabilitation Medicine(JORM) and to identify the types of errors in statistical analysis. Methods : We reviewed quantitative articles that were published in the JORM from January 2005 through October 2009. Those were not used by statistical analysis such as literature studies, case study, review articles were not included in this analysis. A total of 296 articles was reviewed. We evaluated the adequacy and the validity of the statistical techniques with our checklist established be modified Lee's checklist, and three statistical evaluators assessed together to minimize bias. Results : Of the 222 articles, 213 were used in inferential and descriptive statistics. Of those 80% of articles adopting descriptive and inferential statistics were detected having statistical errors. One articles used 1.7 statistical method unit generally. Most frequently employed statistics were student t-test, one way ANOVA. pearson correlation analysis, Mann-whitney U test, paired t-test, and chi-square test in their order. However, most frequent statistics having errors were similar in order. The most common statistic errors were as follow: 1. absence of normality test, 2. misuse between paired test and unpaired test, 3. wrong choice of repeated measures analysis without consideration of time variables, 4, increase of Type I error by using inappropriate multiple test, 5. inappropriate application of discrete or categorical data instead of continuous data in correlation analysis, 6. poor consideration of basic consumption in chi-square test, 7. confusion between frequency comparison and average comparison, 8. mentioning the statistical technique without using it. Conclusions : We found various mistake or misuses in the applications of statistical methodologies in the articles published in the JORM. Careful consideration of statistical use and review from the specialist of statistics are warranted for improving the quality of JORM.

• Journal of Sasang Constitutional Medicine
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• v.28 no.1
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• pp.51-56
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• 2016

Objectives This study was to identify the types of errors in the statistical analysis and trends of previous reported papers that used various statistical techniques.Methods We have selected 118 original articles for statistical review from the OASIS(http://oasis.kiom.re.kr) and the Pubmed(http://www.pubmed.gov) in the field of Sasang constitutional medicine. Published year was restricted from 2011 to 2015.Results 1. The ANOVA(25.72%) was the statistic of choice overall, followed by the chi-square test(21.74%), regression analysis(14.13%), t-test(11.59%), and etc. 2. By examining the errors of the statistical methods, there were 42(59.2%) thesis with errors among 71 thesis using ANOVA, 19(31.7%) thesis among 60 thesis using chi-square test, and 35(89.7%) over 39 thesis using regression analysis.Conclusions To improve the quality of Sasang Constitution, the participation of statisticians in research design will reduce the significant errors in statistical interpretation of the results.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.219-224
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• 2003

Translation errors in the statistical funtions of the Korean Excel 2002 software are analyzed into three categories: Pure translation mistakes; Vague translation; Inconsistent translation. These errors have not been corrected at least for the last ten years and therefore, it is suspicious that the Korean agents for foreign software companies are more interested in marketing with monololy power than in improving quality of their products

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.95-100
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• 2005

In this paper a class of multifactor designs for estimating the slope of second order response surface regression models with correlated errors is considered. General conditions for second order slope rotatability over all directions and also with respect to the maximum directional variance in case of k=2 have been derived assuming errors have a general correlated error structure. And we consider the measures for evaluating slope rotatability with correlated errors similar to in case of uncorrelated error structures.

• The Journal of Korean Obstetrics and Gynecology
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• v.25 no.1
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• pp.70-78
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• 2012

Objectives: The purpose of this article is not until to investigate the changes and types of statistical methods and to point out the statistical errors after analyzing the method of articles that improve the quality of the statistical analysis of papers published in the Journal of Oriental Obstetrics and Gynecology. Methods: Papers published in the Journal of Oriental Obstetrics and Gynecology from 2009 to 2011 were reviewed for methodological and statistical validity using a modified version of Ahn's checklist. A statistician reviewed individual papers and evaluated the list items in the checklist for each paper. To avoid the potential assessment error by the statistician who lacks expertise in the field of Oriental Obstetrics and Gynecology. Results: A total of 190 papers including 64 original articles, 40 reviews article, 58 case report and 28 brief communication were reviewed. Statistics methods used in 121 papers were composed of t-test(58.7%), ANOVA test(19.8%) and ${\chi}^2$- test (14.0%) et al. Whereas only 14.9% of papers were free of statistical errors, the number of omission errors was 58 and the number of commission errors was 149 each. Conclusions: A variety of statistical errors were encountered in papers published in the Journal of Oriental Obstetrics and Gynecology. Accordingly, researchers should be more careful when it comes to describing and applying statistical methods.

• Journal of Sasang Constitutional Medicine
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• v.22 no.4
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• pp.49-55
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• 2010

1. Objectives The purpose of this study is to assess the statistical methods used in the Journal of Sasang Constitutional Medicine and to identify the types of errors in the statistical analysis. 2. Methods We have reviewed quantitative articles published in the Journal of Sasang Constitutional Medicine from 2000 to 2009. Except for the case report, a total of 505 articles was reviewed by year. We focused on the methods of statistics in these articles. We have analysed the number of thesis used the statistical methods, the number of the statistical methods, the types of the statistical methods, and the errors of the statistical methods with the object of 202 thesis used the statistical method. 3. Results 1. Of the 370 articles, 202 used inferential statistics. 2. The most dominant was the thesis with one type of the statistical method forming 61.9% (125 thesis) of the total. 3. The ANOVA was the statistic of choice overall (40.1%), followed by the t-test (35.6%). 4. By examining the errors of the statistical methods, there were 49 thesis with errors among 81 thesis using ANOVA, 25 thesis among 72 thesis using t-test, and 18 over 62 thesis using chi-squared test. 4. Conclusions We have found various mistakes or misuses in the applications of statistical methodologies in the articles published in the Journal of Sasang Constitutional Medicine. It is necessary to present the cases of inappropriate statistical methods in order to improve the quality of academic researches. So long as Sasang constitutional medicine uses the statistical methods, researchers should fully examine and be aware of the statistical methods which they wish to use through other research articles, and statistic publications.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.793-798
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• 2012

In this paper, we propose regression methods based on the likelihood function. We assume Arnold-Beaver Skew Normal(ABSN) errors in a simple linear regression model. It was shown that the novel method performs better with an asymmetric data set compared to the usual regression model with the Gaussian errors. The utility of a novel method is demonstrated through simulation and real data sets.