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KMID : 0615720030200010144
Jouranl of Korean Acupuncture and Moxibustion society
2003 Volume.20 No. 1 p.144 ~ p.158
Analysis of various statistical techniques used in the articles published during last 19 years in The Journal of Korean Acupuncture & Moxibusition Society


Abstract
This study was carried out to investigate what kinds of statistical techniques have been used to analyze data from oriental medicine research, For study, 551 original articles which used statistical techniques in their data analysis were selected form the articles published in The journal of Korean Acupuncture & Moxibustion Society(JKAMS) between 1984 to 2002. among them, 122 articles used descriptive statistics while 429 articles used inferential statistics for data analysis. For that 429 articles, t-test (189 articles), analysis fo variance (111 articles), chi-square test (14 articles), correlation (10 articles), regression analysis (4 articles), factor analysis(5 articles), or nonparametric test (23 articles) were chose to analyze the data. Nonparametric approach has substantial power in case data do not meet the assumption of normality. This method is not only easy to use ut also provides measures of the statistical variation of nominal and ordinal scale. This study shows that more and more recent papers use nonparametric test compared to the old articles. nine different statistical software or packages (SAS, SPSS, Statview, Minitab, Sigma plot, ISP, Graphpad prism, Excel, Access) have been used in the articles published JKMAS. High level statistical techniques such as SAS, SpSS, and Statview are user friendly and used most for acupuncture and Moxibustion research. Including tables and plots in an article facilitates understanding family process data from a descriptive standpoint, minimized erroneous statistical conclusions, and clarifies theoretically important relationships among variables. Table and plots have been used 500 and 233 articles, respectively. A computer procedure is proposed and illustrated with statistical packages using SAS, SPSS, Statview and ISP.
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